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Own your branded search: Building a competitive PPC defense

Own your branded search: Building a competitive PPC defense

If you’re not actively managing your branded search campaigns, you’re leaving money on the table and your reputation in the hands of competitors, review aggregators, and affiliate marketers. 

Brand protection through PPC isn’t just about bidding on your own name. It’s a strategy that spans defensive bidding, query monitoring, ad copy testing, and reputation management across the entire customer research journey.

Why brand search deserves more than basic defense

Most PPC managers treat brand campaigns as an afterthought. Set up a campaign, bid on the exact brand name, maybe add some close variants, and call it done. 

But the reality is far more complex, especially when we’re talking about bigger, well-known brands. Your brand exists across dozens of query contexts, each representing a different stage of the customer journey and requiring a different strategic approach.

Consider what happens when someone searches for your brand. They’re not just typing your company name, they’re asking questions, seeking validation, comparing alternatives, and researching specific features. 

If you’re only covering exact-match brand terms, you’re missing the majority of brand-related searches and leaving those high-intent users exposed to competitor messaging.

Third-party sites like review aggregators and affiliate comparison websites actively bid on your brand terms to capture traffic and redirect it to their comparison pages, where your competitors pay for prominence. 

The cost? Your brand equity, customer trust, and ultimately, conversion rates.

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4 categories of branded searches you need to cover

Based on user intent and competitive vulnerability, branded searches fall into four strategic categories. Each requires different bid strategies, ad copy approaches, and landing page experiences. 

Let’s break down each category and the specific PPC tactics that can work.

Brand trust and reputation queries

  • “Is [Brand] good?”
  • “[Brand] reviews.”
  • “Is [Brand] legit?”
  • “Is [Brand] worth it?”

These searchers are in the validation phase. They’ve heard of your brand but want social proof before committing. 

The competitive threat here comes from review aggregators and affiliate sites that will happily show your reviews alongside competitor CTAs.

PPC strategy

  • Bid aggressively — these are high-intent users who are close to converting.
  • Use review extensions and star ratings in your ads.
  • Highlight trust signals in ad copy (years in business, customer count, awards).
  • Send users to dedicated testimonial or case study landing pages, not your homepage.
  • Test callout extensions with specific proof points.

Product features queries

  • “What is [Brand] known for?”
  • “Pros and cons of [Brand].”
  • “Does [Brand] offer [feature]?”

Users searching for feature-specific information are evaluating whether your solution meets their requirements. Competitors often bid on these queries with ads suggesting they offer superior features.

PPC strategy

  • Create feature-specific ad groups with tailored ad copy.
  • Use sitelink extensions to direct users to specific feature pages.
  • Address the specific feature in headline 1, don’t waste space on your brand name.
  • Include feature demos or video on the landing page.
  • Test whether these queries warrant higher bids than core brand terms.

Comparison queries

  • “Alternatives to [Brand].”
  • “How does [Brand] compare?”
  • “Is [Brand] better than [Competitor]?”
  • “Is [Brand] right for [use case]?”

This is the most competitive category. Users are actively comparing you to alternatives, and both direct competitors and third-party comparison sites are bidding heavily. This is where you’re most vulnerable to losing customers who were already considering you.

PPC strategy

  • Bid at or above top-of-page estimates to maintain Position 1.
  • Create dedicated comparison landing pages for each major competitor.
  • Include pricing transparency if it’s a competitive advantage.
  • Monitor auction insights obsessively to identify new competitive threats.
  • Consider category-level comparison ads for “best [category] tools/products” searches.

Niche questions

  • “Is [Brand] expensive?”
  • “Does [Brand] offer discounts?”
  • “Is [Brand] secure?”

These queries reveal specific concerns or evaluation criteria. They’re often low-volume but extremely high-intent because they represent genuine decision-making criteria.

PPC strategy

  • Develop FAQ landing pages that address multiple related concerns.
  • Test lower bids — these queries often have less competition.
  • Use search query reports to identify emerging concerns and address them proactively.

Dig deeper: How to benchmark PPC competitors: The definitive guide

Advanced brand campaign architecture

The traditional single-brand campaign approach doesn’t give you enough control or insight at scale. Instead, structure your brand defense across four specialized campaigns, each targeting different intent signals and requiring distinct bid strategies.

Core brand defense 

This covers exact-match brand terms and common misspellings with aggressive bidding to maintain 95%+ impression share and top positions. Never let this campaign be budget-limited. 

Use multiple RSAs to test different value propositions. Monitor lost impression share due to rank as your primary competitive threat indicator.

Brand + category 

Capture phrase-match queries like “[Brand] CRM” or “[Brand] for [use case],” where users are researching you within a specific product context. 

Bid slightly lower than core brand terms, but ensure ad copy acknowledges the category and emphasizes your category leadership. Test whether category-specific landing pages outperform your homepage for these queries.

Brand reputation and reviews

These intercept validation-phase users searching “[Brand] reviews,” “[Brand] ratings,” or “is [Brand] good” before they click through to third-party aggregators. Bid aggressively here — these comparison-shopping clicks are worth more than core brand searches. 

Use review extensions prominently, include specific social proof metrics in ad copy (4.8 stars, 10,000+ reviews), and send traffic to dedicated testimonial pages rather than your homepage. Test video testimonials on landing pages.

Competitive comparison defense

Control the narrative for queries like “[Brand] vs [Competitor],” “[Brand] alternative,” or “better than [Brand].” These are users you’re at risk of losing, so pay up to your maximum acceptable CPA. 

Create unique landing pages for each major competitor with honest comparisons that emphasize your advantages, include side-by-side feature tables, and offer special conversion incentives like extended trials or migration assistance.

Defensive tactics against third-party aggregators

Sites like G2, Capterra, and other affiliate comparison sites actively bid on your brand terms without violating trademark policy because they legitimately have content about your brand. 

But they’re siphoning off your traffic and often presenting biased or incomplete information. Your defense requires three coordinated approaches.

Bid aggressively on review keywords

Review aggregators bid heavily on “[Brand] reviews” and “[Brand] ratings” because these are their money keywords, so you need to bid even higher. 

Run the math: If a review aggregator click costs you $3 but sends that user to a page where your competitor’s ad costs $50, you’re getting a deal at $10 per click on your own review keywords. 

Calculate the lifetime value of a customer versus the cost of letting them click to a third-party site where competitors can advertise. Also, keep in mind it’s cheaper for you to bid on your own brand than for competitors to outbid you.

Claim and optimize your profiles on major review platforms you want to work with

Even if you can’t prevent them from bidding on your brand, ensure that when users click through, they see optimized content, strong ratings, and an active presence with responses to reviews. 

Many review platforms offer advertising options — test running ads on your own profile pages to capture users who arrive via organic search or competitor ads.

Build dedicated testimonial and customer story pages 

Make yours more compelling than third-party review aggregators. Include video testimonials, detailed case studies with metrics, filterable reviews by industry or use case, and verified customer badges. 

Then use your PPC ads to drive users to these owned properties instead of letting them discover review aggregators organically.

Dig deeper: When to use branded and competitor keywords in PPC

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Ad copy strategies for brand protection

Your brand campaign ad copy needs to do more than confirm your brand name. It needs to preempt objections, differentiate from competitors, and provide compelling reasons to click your ad instead of a competitor’s or third-party site. Three frameworks deliver results.

The preemptive strike 

Identify the top 3-5 objections that come up in your sales process and address them directly in your ad copy before users encounter them on competitor or review sites. 

  • If implementation time is a concern, use “Live in 5 days, not 5 months.” 
  • If pricing is opaque, try “Transparent pricing, no hidden fees.” 
  • If enterprise readiness is questioned, lead with “Trusted by 500+ enterprise customers.” 
  • If ease of use is a concern, emphasize “No training required, start today.”

The competitive differentiator

Don’t just state features, state features your competitors don’t have or can’t match. This is especially critical for comparison queries where you know competitors are showing ads. Examples include: 

  • “Only platform with native [unique integration].” 
  • “Industry’s fastest performance, verified by [third party].” 
  • “Patent-pending [technology] competitors can’t replicate.” 

If you can’t identify any unique features or USPs, that’s a signal to improve your product positioning or capabilities. Without clear differentiation, PPC alone won’t drive sustainable conversions.

Social proof stacking

Combine multiple types of social proof to build credibility quickly. Don’t just pick one element, stack them. Try 

  • “4.8 stars from 10,000+ reviews. G2 leader 5 years running.” 
  • “Join 50,000+ companies. Featured in Forbes and TechCrunch.”
  • “Winner: Best [category] 2025. 98% customer satisfaction.”

Dig deeper: How to write paid search ads that outperform your competitors

Landing page strategy for brand campaigns

Sending all brand traffic to your homepage is a missed opportunity. Different branded queries represent different user intents and concerns, and your landing pages should address those specific intents.

Feature-specific pages

When users search “[Brand] + [feature],” send them to dedicated pages that explain the feature in detail, show it in action, and provide clear next steps. 

Include a hero section explaining the feature in one sentence, a video demo or animated screenshot, technical specifications for enterprise buyers, integration details if relevant, and customer examples using this specific feature.

Comparison pages 

Create dedicated comparison landing pages for each major competitor. Be honest about differences while emphasizing your advantages. Include side-by-side feature tables, pricing comparisons if advantageous, and customer testimonials from switchers. 

Acknowledge competitor strengths without being dismissive, highlight 3-5 key differentiators where you excel, and offer migration assistance or switch incentives. Make your CTA clear and prominent, offering a trial or demo.

Trust and validation pages

For review and reputation queries, create dedicated pages that aggregate social proof rather than linking to your G2 profile or hoping users browse scattered testimonials. 

Display aggregate ratings prominently (average of G2, Capterra, etc.), place video testimonials above the fold, show recent reviews with verified badges, make reviews filterable by industry, company size, and use case, include case studies with concrete metrics, and highlight third-party awards and recognition.

Monitoring and optimization: The ongoing battle

Brand protection isn’t a set-it-and-forget-it strategy. The competitive landscape constantly evolves, new competitors emerge, third-party sites adjust their strategies, and user search behavior shifts. You need systematic monitoring and rapid response capabilities across three time horizons.

Weekly monitoring 

Review:

  • Search term reports to identify new query patterns.
  • Auction insights for increased competitor presence.
  • Impression share metrics to diagnose declining performance.
  • Lost impression share breakdowns by budget and rank.
  • Manual searches of your top 10 brand queries to see what ads are showing.
  • Quality score checks for brand keywords to diagnose landing page or ad relevance issues.

Monthly deep dives 

  • Analyze conversion paths to understand how brand search fits into the broader customer journey.
  • Review assisted conversions since brand campaigns often contribute to non-brand conversions.
  • Audit landing pages for relevance and conversion performance. 
  • Gather competitive intelligence on what landing pages competitors use for brand conquesting.
  • Test new ad copy variations focused on emerging objections or competitive threats. 
  • Analyze search impression share by device and location to identify gaps.

Quarterly strategic reviews 

  • Audit your complete branded query coverage to identify missing categories or query types. 
  • Assess whether your coverage across the four query categories remains comprehensive.
  • Conduct competitive conquest analysis to determine which competitors most aggressively target your brand.
  • Evaluate ROI of different brand campaign types to optimize budget allocation.
  • Review third-party aggregator presence for new sites bidding on your brand.

Advanced tactics for sophisticated brand protection

Dynamic keyword insertion

For validation queries like “is [Brand] good” or “does [Brand] work,” use dynamic keyword insertion to echo the user’s specific question in your ad copy, creating higher relevance and click-through rates. Try headlines like “Yes, {KeyWord:[Brand]} Is Excellent” or “Absolutely, {KeyWord:[Brand]} Works.”

Geo-modified campaigns

If you have location-specific offerings or competitors vary by geography, create geo-modified brand campaigns. Users searching “[Brand] New York” or “[Brand] enterprise” may have different needs than general brand searchers.

Audience layering

Apply audience segments to brand campaigns to adjust bids based on user quality. Users who’ve visited your pricing page before should get higher bids on brand searches than first-time visitors. Similarly, prioritize users who match your ideal customer profile demographics.

Trademark enforcement

While Google generally allows competitors to bid on your brand terms, using your trademarked brand name in their ad copy is often prohibited. 

Monitor competitor ads and file trademark complaints when they use your brand name in headlines or descriptions. This is particularly effective against smaller competitors and affiliates who may not realize they’re violating policy.

Problem/solution queries

Capture queries where users are researching whether your solution addresses a specific problem. These are often high-intent and represent clear use case alignment. 

Target queries like: 

  • “[Brand] for [problem].” 
  • “How to [solve problem] with [Brand].” 
  • “[Brand] [use case] solution.”
  • “Can [Brand] help with [challenge].”

Budget allocation and ROI considerations

How much should you invest in brand protection versus acquisition campaigns? The answer depends on three factors: 

  • Competitive pressure.
  • Brand strength.
  • Customer lifetime value.

If you operate in a highly competitive category where multiple well-funded competitors actively bid on your brand terms, invest more in brand protection. Run auction insights weekly to monthly to quantify competitive presence. 

If competitors show in 40% or more of your brand auctions, this is a high-threat environment requiring aggressive defense. Stronger brands with dominant organic presence can afford to spend less on core brand defense because their organic listings provide natural protection. This doesn’t apply to reputation and comparison queries where third-party sites rank organically.

High LTV businesses should invest more aggressively in brand protection because the cost of losing a customer to a competitor or having them influenced by negative review sites is substantial. If your average customer is worth $50,000 over their lifetime, paying $50 per click to defend against comparison queries is economically rational.

For most B2B SaaS and high-consideration products, allocate approximately 15-25% of total paid search budget to comprehensive brand protection. Within that allocation, dedicate 40% to core brand defense (exact match), 25% to competitive comparison defense, 20% to reputation and review queries, and 15% to feature and niche question queries.

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Brand protection as competitive moat

Brand protection through PPC isn’t just defensive marketing. It’s a competitive moat. When you control the narrative across branded search contexts, you ensure high-intent users see accurate information instead of competitor ads or third-party pages monetizing your brand equity.

The brands that win treat this as strategy, not maintenance. They segment branded queries by intent, build landing pages to match, monitor threats continuously, and defend high-value search real estate aggressively.

Start with an audit using the four-category framework. Close coverage gaps, align campaigns and landing pages to intent, and commit to weekly monitoring, monthly optimization, and quarterly strategic reviews.

If you don’t own your branded searches, someone else will.

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Recap of the February 2026 SEO Update by Yoast

The February 2026 SEO Update by Yoast is part of our monthly webinar series covering the latest developments in search and AI. In each session, we review the most important news from the past month and explore how it affects your search strategy.

Hosted by Carolyn Shelby and Alex Moss, this month’s update focused on AI-driven shifts in search, emerging agentic workflows, and Google’s latest core updates. Below is a recap of the topics discussed and what they mean for your strategy.

Watch the full recap on YouTube to hear Carolyn and Alex dive deeper into these topics, answer audience questions, and share real-world examples.

SEO and AI news from February 2026

Search engines expand AI reporting and website controls

Google and Bing introduced new tools for publishers to manage AI interactions. Bing’s AI Performance Report shows how often Copilot cites your site, including citation counts and queries. Google now allows publishers to control AI access via robots.txt using Google-Extended.

Actionable takeaway:

  • Monitor AI citation reports in Bing Webmaster Tools to track visibility
  • Review your robots.txt and AI access settings to align with your strategy

Debate over Markdown, AI agents, and machine-readable content

OpenAI launched the Codex app, enabling users to manage multiple AI agents for complex tasks. WordPress co-founder Matt Mullenweg proposed making content available in Markdown format to improve AI comprehension, while Cloudflare introduced a Markdown-based approach for AI bots. However, Google’s John Mueller dismissed Markdown files as increasing crawl load.

Actionable takeaway:

  • Simplify your site’s structure to make content more accessible to AI agents
  • If your site is overly complex, explore Markdown or structured data alternatives, but prioritize fixing underlying issues first

Is Google cracking down on self-promotional listicles?

Lily Ray identified a pattern of sites losing visibility due to self-promotional listicles (e.g., “Top 20 SEO Agencies in the US,” with the publisher ranked #1). Google appears to be penalizing manipulative tactics.

Actionable takeaway:

  • Avoid self-serving listicles. If creating comparison content, use objective criteria and transparent methodology

Microsoft’s vision for a sustainable agentic web

Microsoft outlined its approach to agentic search, emphasizing structured data, concise content, and publisher compensation for AI-driven traffic. The shift from human clicks to AI-driven retrieval was highlighted as a major trend.

Actionable takeaway:

  • Optimize for machine-readable actions (e.g., structured data, clear CTAs)
  • Prepare for AI-driven monetization models (e.g., compensation for citations)

Meta’s Avacado agent and OpenClaw integration

Meta is testing Avacado, a new AI agent integrating OpenClaw and Manus for workflow automation. This reflects a broader push toward omnichannel AI interactions.

Actionable takeaway:

  • Ensure consistent messaging across all platforms (website, social, email) to reinforce AI comprehension

ChatGPT rolls out ads

ChatGPT began serving ads to free users, with OpenAI charging advertisers based on ad impressions rather than clicks. The move mirrors traditional search ad models but raises concerns about user experience.

Actionable takeaway:

  • Monitor how AI-driven ad placements impact user engagement and brand visibility

WebMCP is a new protocol for AI agents

Chrome introduced WebMCP, a protocol that enables AI agents to interact with websites via machine-readable actions (e.g., form submissions). Early adoption is limited, but it signals a shift toward agent-first web design.

Actionable takeaway:

  • Audit your site’s underlying code for clarity (e.g., semantic HTML, structured data)
  • Proceed cautiously. WebMCP is experimental and could pose security risks if misconfigured

Bing Webmaster Tools launches AI Performance Report

Bing’s AI Performance Report now shows how often Copilot cites your site, including queries and cited pages. The tool bridges traditional SEO metrics with AI-driven search.

Actionable takeaway:

  • Set up Bing Webmaster Tools if you haven’t already
  • Compare Bing’s AI data with Google Search Console to identify gaps

Google AI Mode introduces UCP-powered checkout

Google’s AI mode now supports UCP-powered checkout, allowing agents to complete purchases on behalf of users. Early adopters include Etsy, Wayfair, and Walmart.

Actionable takeaway:

  • If you’re in e-commerce, prioritize structured product data and fast load times to capitalize on agentic commerce

OpenClaw, OpenAI, and the future of AI agents

The rise of OpenClaw and OpenAI’s advancements underscores a shift toward websites exposing capabilities (not just pages) to AI agents. Early experiments show agents interacting with sites via machine-readable actions.

Actionable takeaway:

  • Focus on clear site structure and consistent data to ensure reliable AI interpretation

What to focus on in 2026

The February SEO Update by Yoast highlighted four key priorities:

  1. Optimize for AI-driven search: Use structured data and markdown to improve AI comprehension
  2. Build brand authority across channels: Ensure consistent messaging for AI agents to reinforce
  3. Prepare for agentic commerce: Prioritize structured product data and fast load times
  4. Avoid low-quality AI content: Google is cracking down on manipulative tactics like self-promotional listicles

Sign up for the next SEO Update by Yoast

The next SEO Update by Yoast is on March 24, 2026, at 4 PM CET / 10 AM EST. Sign up here to join the live discussion or receive the recording.

The post Recap of the February 2026 SEO Update by Yoast appeared first on Yoast.

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Inbound Marketing Strategy: How to Grow Your Brand

Inbound marketing is a method of growing your business by building lasting relationships with consumers, prospects, and clients through “pulling” tactics such as SEO, content marketing, social media, video marketing, and more. These practices inherently build more trust than outbound “awareness style” marketing and, as a result, create 54% more leads.

What’s even more interesting is that consistent inbound marketing (over a period of about 5 months) can drop your overall lead cost by 80%. These stats are powerful, but they barely scratch the surface of why it’s important to understand inbound marketing and do it well.

To start, you need to understand that inbound marketing is generally divided into four stages: attract, convert, close, and delight.

 inbound marketing method infographic

The four stages of this process are powerful because, when done right, they create “pull power.” Instead of advertising to the customer, as traditional outbound marketing does, inbound marketing focuses on creating reasons for the customer to come to you. 

You can do this by publishing helpful content or personalizing your social media pages and website copy. Almost all marketers (93%) say incorporating some level of personalization improves lead quality or purchases. And, with the help of AI, it’s easier for brands to personalize the customer journey now more than ever. 

Big brands like HubSpot, Airbnb, and Slack are experiencing success with these strategies. By creating educational content in-house or leveraging user-generated content (UGC) across socials, these big names have boosted bookings and conversions by building trust and showing their audience how relatable and authentic they truly are. 

Let’s talk about what inbound marketing is, the most effective inbound marketing strategies, and how you can use these to grow your business or startup.

Key Takeaways

  • Inbound marketing wins by “pulling,” not pushing. You attract people with SEO + helpful content, then convert them with clear CTAs, forms, and email nurture—value first, sale second.
  • Tie inbound goals to revenue outcomes, not traffic. Track things like qualified leads, demo requests, and repeat purchases so you’re building a pipeline, not just pageviews.
  • Match content to intent across the journey. Use TOFU to earn attention, MOFU to build trust, and BOFU to prove you’re the right choice, because one blog post won’t close the deal.
  • AI is collapsing the funnel, so your content must “prove,” not just educate. Make buying questions easy to answer fast with comparisons, case studies, pricing info, and strong proof points.
  • Measure what matters and iterate. Watch qualified leads, conversion rates by step, cost per lead, and assisted revenue over 30–90 day trends, then adjust content, offers, and distribution accordingly.

What Is Inbound Marketing?

Inbound marketing is a marketing strategy that attracts customers and clients to you. One of the most popular ways of attracting and retaining visits is through valuable content. Marketers who focus on providing high-quality content consistently may notice growth in repeat visits and user engagement. 

For example, if I work in graphic design and want to attract people who need assistance in that field, I’d focus on creating content relevant to them. That could include design how-tos, YouTube videos about the best design practices, or a niche subject newsletter.  

One of the best things about inbound marketing is that it can work across business sectors. These strategies are great for:

Established enterprises: Inbound scales across teams with consistent messaging and evergreen content.

Service businesses (agencies, consultants, local pros): Educational content, reviews, and case studies pull in leads who are already looking for help.

E-commerce brands: UGC or email flows can turn “window shoppers” into repeat buyers.

B2B companies: Educational content like thought leadership pieces and webinars, and nurture sequences, build trust across long buying cycles and multiple stakeholders.

SaaS and subscription brands: Product-led content (templates, playbooks, onboarding emails) attracts users and increases retention.

What Is the Purpose of Inbound Marketing? Why is it Important?

Inbound marketing reduces the need for you to go out and seek new users. When customers come to you organically, you no longer have to spend a lot of time and money chasing potential buyers. 

This strategy can also increase customer trust. Almost three-quarters (72 percent) of customers conduct online research before deciding what to buy. If you present your company as an authoritative source in your industry, users may be more likely to pick you.

Inbound marketing is important because it builds trust before the sale. Instead of meeting prospects with a pitch, you meet them with answers via guides, tools, and examples that help them decide on their own terms.

It also scales better than relying solely on paid acquisition. Ads stop the moment you pause the budget. A strong content and SEO foundation keeps generating traffic and leads over time, which typically lowers your cost per acquisition as it compounds.

And it’s especially valuable for long buying cycles (common in B2B and higher-ticket services). You can educate stakeholders over weeks or months with email sequences, webinars, and case studies, so you’re the obvious choice when they’re ready.
The key is tailoring everything to your target audience. When your content matches real questions and intent, inbound works whether you’re a startup or an enterprise team.

Practical Inbound Marketing Examples

Let’s come back to our brand examples from earlier. Here are how three big brand names used inbound marketing to improve their already-stellar results:

HubSpot

They didn’t just talk about inbound — they built an engine around it. HubSpot pumped out helpful guides, templates, and blog content that pulled in a massive audience, then funneled that traffic into leads through smart offers and forms. The result: more people engaging with lead capture pages and a big jump in conversions.

HubSpot's marketing statistics report.

Source: https://www.hubspot.com/marketing-statistics

Airbnb

Airbnb lets customers handle much of the marketing for them. By spotlighting real guest and host stories, photos, and reviews, they made the brand feel trustworthy and “real.” That kind of user-generated content works like social proof on steroids, helping drive more bookings and repeat engagement.

AirBNB on TikTok.

Source: https://www.tiktok.com/@lucilleugc/video/7291577953496861958

Slack

Slack focused heavily on education to remove friction. Webinars, tutorials, and onboarding resources helped teams understand the value quickly, which sped up adoption. Once people “got it,” Slack’s product spread inside companies through internal champions and word of mouth.

Slack's Help Center.

Source: https://slack.com/help/categories/360000049063

Inbound Marketing Versus Outbound Marketing

Inbound and outbound marketing techniques differ in how they approach the customer. They also produce different results. 

Outbound marketing requires proactively reaching out to potential customers to gauge their interest in your products. For example, you may launch social media sale campaigns, engage in door-to-door sales, or cold-call people.

Inbound marketing, on the other hand, focuses on bringing the customer to you. Like we discussed earlier, this can include creating content that resonates with your desired audience. 

Once brand awareness and long-term trust are established, people may be more likely to buy from you. 

Here is a handy table to remember the difference between the two:

Inbound Marketing  Outbound Marketing
Focuses on high-quality content Focuses on sales campaigns 
Generates brand awareness for building long-term relationships More focused on converting new users
May take less time May take more time
Saves money spent on marketing costs  Requires money for sales campaigns 

As you can see in our table, outbound marketing is still relevant. Think of outbound as getting your audience’s attention, and of inbound as what helps make them long-term customers. Using the two together is the best way to drive ideal marketing results.

The Stages of Inbound Marketing

Understanding the stages of inbound marketing can help you improve your website copy and attract the right customers faster. The four stages are: attract, convert, delight, and engage.

Attract

The first stage of inbound marketing is Attract. This stage is all about finding and attracting your target audience. An example would be creating a how-to guide as a blog. You would implement an effective SEO strategy by using relevant keywords in that blog, and then strategically share it on social media to attract people to your brand.

Ultimately, ask yourself: How do you help people find your website? Do you add a lot of relevant keywords in your blog posts? Do you use targeted hashtags? 

Answering these questions and adapting accordingly can help you rank higher in Google search and be more visible in your desired audience’s social media feed. 

Convert

When we talk about marketing, we often think about converting users. After all, the end goal of marketing is to find new users and “convert” them

How can you use inbound marketing to convert users? 

  • sign-up forms
  • effective calls to action (CTAs)
  • incentivizing signing up for your newsletter

For example, look at this section of Nike’s homepage. It reminds visitors of a challenge they’re hosting and gives them the options to start a run or a workout using buttons at the bottom.

How Can You Use Inbound Marketing to Convert Users - Nike homepage CTA

This CTA may prompt a casual viewer to sign up and become a part of Nike’s community. 

Close

In some cases, converting a user isn’t as straightforward as offering a sign-up form and hoping they join your community. 

One of the many ways you can enter the closing stage is by using automation. For example, automated emails that remind users of their abandoned carts can prompt a busy customer to return to your site and complete their purchase.

It works, too. Forty-five percent of abandoned cart emails are opened, and 50 percent of the links within are clicked. Such findings show how the “close” stage of the inbound marketing strategy can be equally if not more important.

Delight

The last stage of the inbound marketing strategy is the delight phase, wherein you reward customers for buying from you. 

It could include actions like sending a thank you message, personalized follow-up emails, offering discounts, and more.

Here’s an example of a thank you page from Codica:

A thank you page from Codica.

Source: https://www.convertflow.com/call-to-action/codica-thank-you-page

Not only does this add a personal touch and some appreciation to Codica’s funnel, but it also includes an opportunity for further engagement. Pointing visitors to additional articles and case studies gives Codica’s audience the opportunity to deepen their relationship with the brand.

If you choose to include surveys and feedback forms at this stage, you can also receive helpful comments and gain insight into potential problems to fix early on. 

Inbound Marketing Strategies to Drive Business Growth

Now that you know what is inbound marketing and how it works, let’s dive into the best strategies for inbound marketing for startups.

1. Define Your Goals and Target Audience.

The first and most critical part of creating compelling content is understanding what your target customers want to learn. You need in-depth knowledge of your market to react quickly.

From there, get specific about what you’re trying to achieve. Inbound goals should tie to business outcomes—not just “more traffic.” For example, are you trying to improve lead quality, generate more demo requests, or drive repeat purchases?

Once you’re clear on the goal, define exactly who you’re trying to reach and what they care about. What problems are they trying to solve? What questions do they ask before they buy? When you align your content to those answers, you attract the right people—and make it easier to turn that attention into revenue.

2. Survey Your Current Customers and Leads

The easiest way to get to know your target market is through a survey.

This doesn’t have to be complicated. If you already have an email list, you can send them a simple form through SurveyMonkey.

To make this work, you only need to ask one question: “What is your biggest struggle?”

Your goal is to understand the problems they’re facing so you can create compelling content that targets their deepest interests.

3. Map Content To The Buyer’s Journey

When it comes to content, one blog post won’t close the deal. You need to consider a buyer’s entire journey, from discovery to purchase, and reach them at multiple touchpoints until they’re ready. Here’s what that looks like in practice: 

  • Top-of-funnel (TOFU): attract attention with blogs, checklists, short videos, and beginner guides.
  • Middle-of-funnel (MOFU): build trust with webinars, templates, comparison posts, and email nurturing.
  • Bottom-of-funnel (BOFU): help people decide with case studies, demos, pricing pages, and customer proof.

And now AI is compressing the funnel. Search engines and AI answers can skip the “browse” stage and send someone straight to a shortlist. So your content can’t just educate—it has to prove. Make every stage easy to act on: clear next steps, strong proof, and pages that answer buying questions fast.

4. Choose the Right Channels for Your Audience

Choose channels the same way you choose content: based on how your audience actually behaves:

  • B2B buyers often want depth. SEO content, LinkedIn, webinars, and email nurturing work well because decisions take time and involve multiple people.
  • E-commerce shoppers tend to bounce between discovery and purchase. Lean into SEO, paid retargeting, creator/UGC, and lifecycle email/SMS to capture and re-capture demand.
  • Service businesses win locally with search, reviews, Google Business Profile, and case studies that prove outcomes fast.
  • Niche audiences often live in communities—Slack groups, Reddit, Discord, industry newsletters—where trust is built through participation.

The goal isn’t “be everywhere.” It’s about picking 2–3 channels you can execute consistently, then connecting them with clear next steps so attention turns into leads and revenue.

5. Create and Share Compelling Content

The quality of the content you create is the most important feature of your inbound marketing strategy.

If you create generic, self-serving articles and videos, you’ll never see success.

No matter how hard you promote this content or how you designed it to rank well in search engines, you’re going to struggle to find new clients and customers.

The best-in-class content marketers work tirelessly to adapt their content to the target audiences they want to attract — and where that audience is in the customer journey.

use inbound marketing strategies to create viral content

Understanding the customer journey and their needs is critical to making great content, but it’s not the only strategy you’ll need to draw in new customers and leads.

Optimizing your content headline is the most important strategy to do that. It’s what will drive the most clicks and draw in new traffic.

You should spend lots of time crafting a headline that appeals to your most targeted customers.

One of the best ways to do this is to include a bit of negativity, but you shouldn’t always have negative headlines.

But if you have a list of mistakes or talk about the worst strategies that could hurt your customer, this can be an effective way to drive traffic.

According to the Martal Group, companies with blogs generate 13x more leads per month than those who don’t.

If you’re going to produce this content, you need to make sure it works to its best ability.

For your content to appeal to your ideal readers, make sure there’s more to it than just large blocks of text. Humans love visual content. 

Including lots of images, charts, and graphs is a technique I use to make my content more appealing, and I’m not alone.

A graphic showing what marketers are putting into their content.

Source: https://www.orbitmedia.com/blog/blogging-statistics/

A graphic showing marketers that produce highly visual content.

Source: https://www.orbitmedia.com/blog/blogging-statistics/

The more visual your content, the more likely it is to improve your inbound marketing efforts.

Length is another focus area where you can improve your inbound marketing. Instead of writing short posts, you should be doing extensive research and producing in-depth content.

A graphic showing blog length's impact on results.

Source: https://www.orbitmedia.com/blog/blogging-statistics/

You should be writing articles that are a few thousand words long and supported by lots of data and analysis.

This is not only better for your SEO rankings, but it’s also more helpful for your customers.

The better your content, the more likely your readers are to share it with friends, recommend your site to others, and implement what you say.

Just because you base your content around data and analysis doesn’t mean it needs to be dry and academic.

You should work to produce the opposite type of content. You want to create articles that tell a story.

Using storytelling in your content (from sales pages to social media posts) is a way to create an emotional connection with your audience.

Storytelling has another powerful function. It creates brand recall. 

Creating a personal, emotional narrative around your brand can boost brand recall up to 70%.

Why? 

Because connecting with your audience on an emotional level literally rewires their brain. Compelling stories create new neural pathways linked to trust and personal connection, making you stand out far and above competitors in your target audience’s mind. 

But, how do you implement this tactic in your startup? Look for opportunities to weave in stories when talking about your product or business.

Sure, your benefits and features are great, but the emotional connection you create with storytelling will close the sale and help grow your startup through inbound marketing.

6. Make a Habit Out of Guest Posting Consistently

When you look at the data, you’ll find that guest blogging is the best inbound marketing strategy.

This is because it provides you with backlinks, authority in the space, and relationships with key influencers.

But most people go about it the wrong way. If you aren’t using smart strategies to spread your startup’s message through guest posting, you might as well not do it.

If you want to reap the benefits of guest posting, you need to write consistently.

This is how the most successful startup owners have made guest blogging work well for them. Instead of a few posts, they wrote prolifically and gained ground quickly.

If you do a Google search for guest posts by Danny Iny, you’ll find dozens of pieces of content across the web.

guest post by danny iny Google Search showing the power of inbound marketing

This massive, consistent guest-posting strategy allowed him to grow his business Mirasee into the powerhouse it is today.

On his homepage, he displays an in-depth list of all the sites where he has been featured.

Dedicate some of your time to creating compelling content for other blogs to reach as many customers as possible.

Dedicate some of your time to creating compelling content for other blogs to reach as many customers as possible.

Another problem I see with entrepreneurs who want to use guest posting as an inbound marketing strategy is that they don’t look for sites that will give them much ROI.

The truth is that every guest post requires work, and that’s work that needs to give you a distinct benefit in visitors or leads.

If you post on a blog that has a dead audience, you won’t get any benefit, and you’ll have wasted your time. Look at the comments people are leaving on sites where it makes sense for you to guest post. 

Not only will this give you content ideas, but it also tells you the readers are engaged, and a blog post here might result in readers clicking through to my startup’s website and purchasing from me.

6. Maximize Your Results from SEO with Keyword Optimization

You need to understand SEO to achieve any success with your startup in today’s search-driven marketplace.

The most important things to focus on are basic on-page SEO and backlinks for your site and your content.

How do you do that? Keyword optimization.

You want to find specific long-tail keywords which you’d like to use for targeting your content.

Why?

Long-tail keywords have a three to five percent higher click-through rate than generic searches. 

The more specific someone is in their search, the more likely they know what they want and are close to converting into a customer.

7. Promote Your Content to Build Backlinks

Backlinks still matter for SEO—but not in the “collect as many as possible” way.

At the simplest level, backlinks are links from other sites to yours. Search engines treat them like votes of confidence, especially when those links come from relevant, trustworthy websites. A handful of high-quality links can beat hundreds of low-quality ones.

The best way to earn backlinks today is to create something worth citing, then promote it the right way. Think: original data, strong opinions backed by examples, free tools, templates, step-by-step guides, and “definitive” resources people reference in their own content.

Then focus your promotion on modern link-earning plays:

  • Digital PR (pitch your data, angle, or story to journalists and editors)
  • Outreach to relevant creators (not random “influencers”)
  • Unlinked mention reclamation (turn brand mentions into links)
  • Partner and community placements (where your audience already hangs out)

The number of backlinks you need depends on the competition, but quality, relevance, and intent alignment are what move the needle.

Not sure where to start? Use my free backlink checker to see who’s linking to your competitors, and what’s realistically earning links in your niche.

8. Acquire Inbound Marketing Leads with Free Content

When it’s time to convert your visitors into leads, you need bulletproof strategies to get people to give you their email addresses.

The best method I’ve seen is to offer free content in exchange for this contact information.

If your startup is in the B2B sector, or if you appeal to customers who want or need in-depth analysis before purchasing, you can make an effective lead magnet from a report.

This is a great way to get leads because the comprehensiveness of your work seems like a great deal for an email address.

HubSpot’s list of marketing statistics includes a pitch for their “State of Inbound Marketing” report. This is a detailed guide with massive amounts of high-quality data.

hubspot state of inbound marketing report

But they aren’t giving this away for free. To receive the report, you need to provide a detailed amount of information that HubSpot will use to follow up with you on their products.

An access now form on HubSpot.

This is an effective way to drive your visitors into your sales funnel and reach them even more effectively.

9. Host a Free Webinar

One of my favorite inbound marketing techniques for startups is free webinars that encourage customers to learn in real-time.

This is great because it lets them see your face and understand your personality. Besides, lots of people will download a guide and never read it.

But if someone signs up for a webinar, you can see if they watch the whole thing.

I have used this kind of training on my homepage in the past. I didn’t call it a webinar, though. I just used the term “training.”

host a free webinar or training to collect inbound marketing leads

This is a great way to increase your leads as visitors must enter their first name and email address to access the training.

host a free webinar or training to get inbound marketing leads

Since this is such a valuable teaching piece, people who come to my website are happy to provide their email address to learn SEO better.

10. Launch an Email Course

There’s another form of content you can create that will drive new customers.

Even better, it won’t require the extensive research that a report demands or the complicated backend software necessary for a webinar.

That strategy is to create an email course. This is a simple way to provide extra value without spending tons of time creating something with design elements or video.

A great example is a free masterclass Mariah Coz offers. Because it’s a course, it makes the content feel more valuable.

create a free masterclass for your inbound marketing strategy

If you’re currently giving away an e-book for your startup and you’ve found that it isn’t converting well, consider breaking down the content into sections.

Then use each section as a separate email. You may find that an email course or a masterclass converts even better than an ebook.

11. Start an Influencer Marketing Campaign

According to a survey by Influencer Marketing Hub, 75 percent of brands have a dedicated budget for influencer marketing, and 90 percent of respondents believe it’s an effective form of advertising.

If you do this the right way, it can be a free or paid method to get people excited about your brand.

If you’re going to launch an influencer marketing campaign, you need to understand what will make it work best.

First and most importantly, you need to make sure you’re appealing to the right influencers.

This is easy to get wrong, as the people you think you’re appealing to may not be persuasive to your target audience.

The earlier research you did on your audience should be a great starting place to understand who they pay attention to, but you might need to do even more work than that.

How do you find the right influencers for your startup? You can:

  • Google phrases like “top [niche] influencers.
  • Browse hashtags on Instagram related to your niche.
  • Use Influencer platforms to connect with creators.
  • Search key phrases on Ubersuggest to find blogs that appeal to your target audience.
use Ubersuggest for inbound marketing

12. Make Your Website Convert Like Crazy by Making it Mobile Friendly

Ultimately, the goal of much of your inbound marketing strategy is to drive people to your startup’s website.

If you’re not converting people once they arrive, however, what’s the point?

Conversion is the key to successful inbound marketing since it’s the transition from visitor to prospect.

inbound marketing helps boost your conversions infographic

You need to make sure your website is ready to convert your traffic into leads and customers.

It’s the only way to make your startup grow with the traffic you’ve worked so hard to acquire.

The first and most important way to ensure you’re getting the conversions you deserve by focusing on your website’s conversion rate optimization (CRO).

If your startup’s site doesn’t load quickly or has a confusing layout, you’re going to struggle to convert the traffic you’ve worked so hard to drive there. You need to evaluate your site’s user interface (UI) and user experience (UI) through the lens of your target audience. What can you do to make your site simpler and drive visitors into your funnel? 

The vast majority of websites aren’t maximizing their CRO, and they aren’t putting in the work they need to make these changes.

Instead of actually converting their customers, they’re losing out on valuable traffic.
Don’t let that happen to you. Your site is more than just the place your leads land. It can be one of your most powerful strategic assets if you focus on CRO and use it well.

Inbound Marketing Tools

Inbound marketing strategies can be pretty effective, but they can be challenging to figure out initially. To help you make the transition from outbound to inbound marketing smoother, I have compiled a few inbound marketing tools to help you strengthen your marketing plan

These tools can be helpful, but at the end of the day, they’re just tools. It’s you as a marketer who can use them effectively for the best results. Having a deeper understanding of how inbound marketing works can help you strengthen your marketing plan for better reach. 

Jotform

Jotform is a free form builder with attractive templates and a ton of desirable features. It’s easy to set up, forms can be designed and edited in minutes, and the results can embed in most content management systems in a click. 

Tools like Jotform can help you design beautiful forms for newsletter sign-ups, e-book downloads, service subscriptions, and other inbound marketing practices. 

Mailchimp

While tools like Jotform can help you secure sign-ups, you need efficient email marketing and distribution to operate inbound strategies like a lead-generating newsletter. That’s where Mailchimp comes in. 

Mailchimp offers free and paid email distribution features. You can customize how your email looks, when it’s sent, what it includes, and more. Mailchimp also lets you create personalized email campaigns unique to each set of subscribers. 

Customizable features like these can help you create effective email campaigns to generate, capture, and nurture leads. 

Buffer

Social media management is a crucial aspect of inbound marketing. Tools like Buffer can help you improve the effectiveness of your social media marketing plan. 

Buffer lets you schedule social media posts to publish content when your target demographic is most active. As a result, no one has to stay awake at odd hours to post content at strategic times. 

This tool also automates most of the social media management, so you save time and money. So if you’re a startup with a tight budget, this can help give you a leg up. 

Inbound Marketing Metrics To Track

If you want inbound marketing to drive growth, you need to measure the stuff that actually impacts revenue—not vanity metrics like raw traffic or impressions.

Here are the numbers that matter most:

  • Qualified leads: Track MQLs/SQLs (or whatever you call “sales-ready”) so you know you’re attracting the right people, not just more people.
  • Conversion rates: Measure conversion by step—visitor → lead, lead → opportunity, opportunity → customer. This shows where you’re leaking results.
  • Cost per lead (CPL): Even “organic” inbound has a cost (tools, content, labor). CPL keeps you honest and helps compare inbound to paid channels.
  • Assisted revenue: Inbound rarely gets the “last click.” Track how content and email influence deals—especially in B2B or high-consideration purchases.

The big rule: watch trends, not one-off spikes. Review these metrics monthly, spot what’s improving (or slipping), and adjust your content, offers, and distribution. Inbound works best when you treat it like a system you constantly tune.

Inbound Marketing Strategy Frequently Asked Questions

What is inbound marketing?

Inbound marketing is the process of attracting customers by helping them first. You publish useful content, optimize it for search, and use conversion points (forms, CTAs, email nurture) to turn visitors into leads and customers. The goal is simple: earn attention with value instead of buying it with interruptions.

What are the types of inbound marketing?

The core types are: content marketing (blogs, guides, videos), SEO (ranking for intent-based searches), social distribution (sharing and community), email nurturing (education and follow-up), and conversion optimization (landing pages, CTAs, offers). The best inbound programs combine these so each channel reinforces the others.

How do you create an inbound marketing strategy?

Start with a clear business goal (pipeline, revenue, retention), then define your target audience and their buying questions. Build content for TOFU/MOFU/BOFU, add conversion paths (lead magnets, demos, trials), and set up nurture sequences. Pick 2–3 channels you can execute consistently, track results monthly, and double down on what drives qualified leads.

How do you develop an inbound strategy?

You need to know the purpose of your content, your target audience, and how your content fits in with the buyer’s journey.

How to measure inbound marketing?

Measure what ties to revenue: qualified leads, conversion rates by funnel step, cost per lead (including content/tooling costs), and assisted revenue (how content influences deals). Ignore one-week spikes. Look at trends over 30–90 days, identify drop-offs, and iterate on content, offers, and distribution.

Is SEO inbound marketing?

Yes, SEO is one of the biggest inbound channels. It brings in people who are already searching for answers, solutions, or comparisons. But SEO alone isn’t the full strategy. Inbound includes what happens after the click, too: content that builds trust, pages that convert, and follow-up that nurtures leads into customers.

Inbound Marketing Strategies Summary

Inbound marketing is the most effective way to increase visitors, leads, and buyers.

To attract customers, you need to understand their needs, aspirations, and struggles. Using that data, create great content that draws them in like a magnet.

You’ll need to include SEO best practices so that customers can find you through search engines.

Once you have the traffic, convert those visitors with free content and influencer marketing that drives leads.

With a compelling email campaign and a high-converting website, you can grow your business like never before.

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Content scoring tools work, but only for the first gate in Google’s pipeline

Content scoring tools work, but only for the first gate in Google’s pipeline

Most SEO professionals give Google too much credit. We assume Google understands content the way we do — that it reads our pages, grasps nuance, evaluates expertise, and rewards quality in some deeply intelligent way. The DOJ antitrust trial told a different story.

Under oath, Google VP of Search Pandu Nayak described a first-stage retrieval system built on inverted indexes and postings lists, traditional information retrieval methods that predate modern AI by decades. Court exhibits from the remedies phase reference “Okapi BM25,” the canonical lexical retrieval algorithm that Google’s system evolved from. The first gate your content has to pass through isn’t a neural network. It’s word matching.

Google does deploy more advanced AI further down the pipeline, including BERT-based models, dense vector embeddings, and entity understanding systems. But those operate only on the much smaller candidate set traditional retrieval produces. We’ll walk through where each technology enters the process.

This matters for content optimization tools like Surfer SEO, Clearscope, and MarketMuse. Their core methodology — a mix of TF-IDF analysis, topic modeling, and entity evaluation — maps directly to how that first retrieval stage scores documents. The tools are built on the right foundation. The problem is that most people use them incorrectly, and the studies backing them have real limitations.

Below, I’ll explain how first-stage retrieval works and why it still matters, what the research on content scoring tools actually shows — and doesn’t show — and most importantly, how to use these tools to produce content that earns its way into the candidate set without wasting time chasing a perfect score.

How first-stage retrieval works and why content tools map to it

Best Matching 25 (BM25) is the retrieval function most commonly associated with Google’s first-stage system. 

Nayak’s testimony described the mechanics it formalizes: an inverted index that walks postings lists and scores topicality across hundreds of billions of indexed pages, narrowing the field to tens of thousands of candidates in milliseconds. 

Here’s what matters for content creators:

  • Term frequency with saturation: The first mention of a relevant term captures roughly 45% of the maximum possible score for that term. Three mentions get you to about 71%. Going from three to thirty adds almost nothing. Repetition has steep diminishing returns.
  • Inverse document frequency: Rare, specific terms carry more scoring weight than common ones. “Pronation” is worth roughly 2.5 times more than “shoes” in a running shoe query because fewer pages contain it.
  • Document length normalization: Longer documents get penalized for the same raw term count. All of these scoring algorithms are essentially looking at some degree of density relative to word count, which is why every content tool measures it.
  • The zero-score cliff: If a term doesn’t appear in your document at all, your score for that term is exactly zero. Not low. Zero. You’re invisible for every query containing it.

That last point is the single most important reason content optimization tools have value. If you write a comprehensive rhinoplasty article but never mention “recovery time,” you score zero for that entire cluster of queries, regardless of how good the rest of your content is. 

Google has systems like synonym expansion and Neural Matching — RankEmbed — that can supplement lexical retrieval and surface additional documents. But counting on those systems to rescue a page with vocabulary gaps is a risky strategy when you can simply cover the term.

After first-stage retrieval, the pipeline gets progressively more expensive and more sophisticated. RankEmbed adds candidates keyword matching missed. Mustang applies roughly 100+ signals, including topicality, quality scores, and NavBoost — accumulated click data over 13 months, described by Nayak as “one of the strongest” ranking signals. 

DeepRank applies BERT-based language understanding to only the final 20 to 30 results because these models are too expensive to run at scale. The practical implication is clear: no amount of authority or engagement signals helps if your page never passes the first gate. Content optimization tools help you get through it. What happens after is a different problem.

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What the research on content tools actually shows

Three major studies have examined whether content tool scores correlate with rankings: Ahrefs (20 keywords, May 2025), Originality.ai (~100 keywords, October 2025), and Surfer SEO (10,000 queries, July 2025). All found weak positive correlations in the 0.10 to 0.32 range.

A 0.24 to 0.28 correlation is actually meaningful in this context. But these numbers need serious qualification. Every study was conducted by a vendor, and in every case, the vendor’s own tool performed best. 

No study controlled for confounding variables like backlinks, domain authority, or accumulated click data. The methodology is fundamentally circular: the tools generate recommendations by analyzing pages that already rank in the top 10 to 20, then the studies test whether pages in the top 10 to 20 score well on those same tools.

The real question — whether following tool recommendations helps a new, unranked page climb — has never been rigorously tested. Clearscope’s Bernard Huang put it directly: “A 0.26 correlation is not the brag they think it is.” 

He’s right. But a weak positive correlation is exactly what you’d expect if these tools solve the retrieval problem — getting into the candidate set — without solving the ranking problem — beating competitors once there. Understanding that distinction is what makes these tools useful rather than misleading.

Why not skip these tools altogether?

Expert writers are terrible at predicting how their audience actually searches. MIT Sloan’s Miro Kazakoff calls it the curse of knowledge. Once you know something, you forget what it was like before you knew it. 

Clearscope’s case study with Algolia illustrates the problem precisely. Algolia’s writers were technical experts producing genuinely excellent content that sat on Page 9. The problem wasn’t quality. The team was using internal jargon instead of the language their audience actually typed into Google. 

After adopting Clearscope, their SEO manager Vince Caruana said the tool helped the organization “start writing for our audience instead of ourselves” by breaking out of internal vocabulary. Blog posts moved from Page 9 to Page 1 within weeks. Not because the writing improved, but because the vocabulary finally matched search behavior.

Google’s own SEO Starter Guide acknowledges this dynamic, noting that users might search for “charcuterie” while others search for “cheese board.” Content optimization tools surface that gap by showing you the actual vocabulary of pages that have already demonstrated retrieval success. 

You can do everything a tool does manually by reading top results and noting common themes, but the tools automate hours of SERP analysis into minutes. At $79 to $399 per month, the investment is justified when teams publish frequently in competitive niches or assign work to freelancers lacking domain expertise. For a solo blogger publishing once or twice a month, manual analysis works fine.

What about AI-powered retrieval?

Dense vector embeddings are the same core technology behind LLMs and AI-powered search features. They compress a document into a fixed-length numerical representation and can match semantically similar content even without shared keywords. Google uses them via RankEmbed, but they supplement lexical retrieval rather than replace it.

The reason is computational: A 768-dimensional embedding can preserve only so much information, and research from Google DeepMind’s 2025 LIMIT paper showed that single-vector models max out at roughly 1.7 million documents before relevance distinctions break down — a small fraction of Google’s index. Multiple studies, including findings on the BEIR benchmark, show hybrid approaches combining BM25 with dense retrieval outperform either method alone.

The bottom line for practitioners is clear: The AI layer matters, but it sits lower in the pipeline, and the traditional retrieval stage your content tools map to still does the heavy lifting at scale.

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How to actually use content scoring tools

This is where most guidance on content tools falls short. The typical advice is “use Surfer/Clearscope, get a high score, rank better.” 

That misses the point entirely. Here’s a framework built on how these tools actually intersect with Google’s retrieval mechanics.

Prioritize zero-usage terms over everything else

The highest-leverage action these tools identify is a term with zero mentions in your content. That’s a term where your retrieval score is literally zero, and you’re invisible for every query containing it. Going from zero to one mention is the single most impactful edit you can make. Going from four mentions to eight is nearly worthless because of the saturation curve.

When reviewing tool recommendations, filter for terms you haven’t used at all. Clearscope’s “Unused” filter does this explicitly. 

Ask yourself: Does this missing term represent a subtopic my audience would expect me to cover? If yes, work it in naturally. If the tool suggests a term that doesn’t fit your angle — a beginner’s guide doesn’t need advanced technical terminology — skip it. 

A high score achieved by forcing irrelevant terms into your content is worse than a moderate score with genuinely useful writing. As Ahrefs noted in its 2025 study, “you can literally copy-paste the entire keyword list, draft nothing else, and get a high score.” That tells you everything about the limits of chasing the number.

Be selective about which competitor pages you analyze

Default settings on most tools pull from the top 10 to 20 ranking pages, which frequently includes Wikipedia, major media outlets, and enterprise sites with overwhelming domain authority. These pages often rank despite their content, not because of it. Their term patterns reflect authority advantage, not content quality, and they’ll skew your recommendations.

A better approach: Look for pages that rank for a high number of organic keywords on mid-authority domains. 

Ahrefs’ data shows the average page ranking No. 1 also ranks in the top 10 for nearly 1,000 other keywords. A page ranking for 500 keywords on a DR 35 site has demonstrated broad retrieval success through vocabulary and topical coverage, not just backlinks. Those pages contain term patterns proven effective across hundreds of separate retrieval events, not just one. 

In most tools, you can manually exclude specific URLs from competitor analysis. Remove the Wikipedia pages, the Amazon listings, and any high-authority site where you know authority is doing the work. What’s left gives you a much cleaner picture of what content actually needs to include.

Use tools during research, not during writing

The worst workflow is writing with the scoring editor open, watching your number tick up in real time. That pulls your attention toward keyword insertion instead of communicating expertise. Practitioners reporting the worst experiences with these tools tend to be the ones writing to a live score.

The better workflow: Run the tool first. Review the term list. Identify gaps in your outline, especially terms with zero usage that represent subtopics you should cover. Then close the tool and write for your reader. 

Run it again at the end as a sanity check. Did you miss any major subtopics? Add them. Is the score significantly lower than competitors? That’s information worth investigating. But your job is to build the best page on the internet for this topic, not to match a number.

Understand that content is one player in the game

NavBoost, RankEmbed, PageRank-derived quality scores, site authority, click data, and engagement signals all operate on the candidate set that first-stage retrieval produces. Content optimization gets you through the gate. It doesn’t win the race. 

If you optimize a page, push the score to 90, and don’t see ranking improvements, that doesn’t mean the tool failed. It likely means the other ranking factors — backlinks, domain authority, and click signals — are doing more work for your competitors than content alone can overcome.

This is especially important when scoping on-page optimization projects. Be honest about what content changes can and can’t accomplish. If a page is on a DR 15 domain competing against DR 70+ sites, perfect content optimization is necessary but probably not sufficient. 

When a client asks why they’re not ranking after you pushed their score to 95, the answer shouldn’t be “we need more content.” It should be a clear explanation of which part of the problem content solves — retrieval — which parts it doesn’t — authority, engagement, brand — and what the next strategic move actually is.

Focus on going beyond, not just matching

The philosophy behind these tools — structure your content after what top results cover — is sound. You need to demonstrate topical relevance to enter the candidate set. But the goal isn’t to produce another version of what already exists.

The pages that rank broadly, the ones that show up for hundreds or thousands of keywords, consistently do more than match the competitive baseline. They add original research, practitioner experience, specific examples, or angles the existing results don’t cover.

Surfer SEO’s December 2024 study supports this. It measured “facts coverage” across articles and found that top-performing content by keyword breadth had significantly higher coverage scores than bottom performers.

The content that ranks for the most queries doesn’t just include the right terms. It includes more information, more specifically. Use the tool to establish the floor of topical coverage. Then build the ceiling with value the tool can’t measure.

A note on entities

Google’s Knowledge Graph contains an estimated 54 billion entities. Entity understanding becomes most powerful in the later ranking stages where BERT and DeepRank process final candidates. 

Some content tools are starting to incorporate entity analysis, but even the best versions present entities as flat keyword lists, missing the relationships between entities that Google’s systems actually evaluate. 

Knowing that “Dr. Smith” and “rhinoplasty” appear on your page is different from understanding that Dr. Smith is a board-certified surgeon with published research at a specific institution. That relational depth is what Google processes, and no content scoring tool currently captures it. 

Treat entity coverage as an additional layer beyond what keyword-focused tools measure, not a replacement for the fundamentals.

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Retrieval before ranking

Content optimization tools work because they’ve reverse-engineered the vocabulary of the retrieval stage. That’s a less exciting claim than “they’ve cracked Google’s algorithm,” but it’s the honest one, and it’s supported by what the DOJ trial revealed about Google’s infrastructure.

Use these tools to identify missing terms and subtopics. Be skeptical of exact frequency targets. Exclude high-authority outliers from your competitor analysis. Prioritize zero-usage terms over further optimization of terms you’ve already covered. 

Understand that a perfect content score addresses one stage of a multi-stage pipeline and use the competitive baseline as your floor, not your ceiling. The content that ranks the broadest isn’t the content that best matches what already exists. It’s the content that covers what already exists and then goes further.

Read more at Read More

How to Create a Wikipedia Page for Your Company

Wikipedia is a fascinating experiment. It’s a community-built encyclopedia that’s always in motion. It runs on volunteer energy and openly shared infrastructure, and it’s closer to an open-source project in how it’s built than a traditional encyclopedia book. Anyone can write, edit, and debate what belongs on a page.

And that’s the twist. The “truth” on Wikipedia isn’t handed down by a single editor or community member. It’s negotiated in public, guided by community standards, citations, and a whole lot of conversation. Contributors don’t so much control a subject’s story as they continually test it. They’re constantly asking questions: What can we verify? What deserves weight? What’s missing?

When you read a Wikipedia article, you’re seeing a current snapshot of a living, evolving community decision.

This whole experiment has scale, too. As of February 6, 2026, the English Wikipedia had 7.13 million articles, and the project spanned more than 340 languages.

If you’re thinking about creating a Wikipedia page for your company, it helps to know what you’re signing up for. Wikipedia isn’t a marketing channel, and it isn’t designed for companies to shape their narrative. 

It’s designed to summarize what independent, reliable sources have already said about a company, so not every organization qualifies for a stand-alone article. Wikipedia cautions that only a small percentage of organizations meet the requirements for an article in the first place.

The easiest way to orient yourself with the platform is to keep Wikipedia’s “five pillars” top of mind. Wikipedia is, first and foremost, an encyclopedia. It aims for a neutral point of view, the content is free for anyone to use and edit, editors are expected to be civil, and there are no hard-and-fast rules. It’s just policies and guidelines applied with unbiased judgment.

If your company is genuinely notable by Wikipedia’s standards and you’re willing to play by its guidelines, there’s a real visibility upside in a solid, well-sourced page that holds up over time.

Key Takeaways

  • Wikipedia isn’t for marketing. If a Wikipedia page reads like company positioning, a feature brochure, or a pricing page, it’ll get rejected, reverted, or flagged. Even if other company pages “get away with it,” you need to focus on creating a deeply researched, informative draft to give strong notability in Wikipedia’s eyes. 
  • Notability = independent coverage. You need multiple strong secondary sources (real reporting with editorial standards). Press releases, paid placements, niche trade mentions, and contributor “interviews” don’t hold up.
  • Sources drive the outline (and the page). Build your outline from what your credible secondary sources already cover. Possible sections could include a lead, history, high-level operations, leadership, or controversies, if documented. Each company’s outline may look different depending on what information can be strongly sourced. If you can’t source a section cleanly, it doesn’t belong.
  • Use Wikipedia’s Articles for Creation (AfC) process to avoid conflict of interest (COI) roadblocks. If you’re connected to a company or paid to write a Wikipedia page for them, you must disclose it and lean on the AfC process instead of directly pushing a company page live.
  • Getting published isn’t the finish line. Volunteers continuously review pages. Expect ongoing edits, scrutiny, and occasional challenges, so monitor a live page and keep it updated with strong, independent citations.

What Are the Benefits of Creating a Wikipedia Page?

The most significant benefit of Wikipedia is its sheer size and reach. It is one of the most visited websites in the world, averaging more than 1.1 billion unique visitors per month.

In addition to the size of its audience, the platform offers other benefits to marketers and company owners:

  • Credibility via independent validation (earned, not claimed): A live Wikipedia page signals that reliable, third-party sources have covered your organization in a meaningful way. For journalists, partners, investors, and enterprise buyers, this can reduce skepticism during research.
  • Search and AI visibility (off-page, long-term): Wikipedia tends to surface prominently in search results and is commonly referenced by knowledge systems. A well-sourced page can support progress in how your company appears in search features, AI overviews (AIOs), and large language model (LLM) output, based on what independent sources say, not what a company wants to say.
  • A neutral orientation page for readers: Wikipedia’s format helps readers quickly understand a company’s basics, including history, products or services, leadership, milestones, and context. The tradeoff is accessible neutrality. Anything included needs support from reliable secondary sources, and promotional language rarely lasts.
  • Clarity and disambiguation: If your name overlaps with other companies, or your story includes mergers, rebrands, or multiple founders, Wikipedia can help people land on the right entity and timeline.
  • A durable reference hub: A good Wikipedia page often becomes a stable directory of the strongest independent sources about you, such as press, books, and other reputable coverage, so readers can verify details without relying on your website alone.
  • Consistency across the web (a quiet multiplier): Wikipedia and related knowledge sources are reused in many downstream places. When the facts are clean, cited, and consistent, it can improve how your company is represented across third-party profiles and information panels over time.

A Wikipedia page is rarely a conversion engine, and it isn’t a place to “own” your story. The value is credibility and discoverability that can compound, but benefits can vary based on the strength of independent coverage and ongoing community scrutiny.

Below, we’ll cover the 10 steps on how to create a Wikipedia page, as well as considerations to keep in mind.

1. Check to See If Your Company is a Good Fit for a Wikipedia Page

Before you think about how to create a Wikipedia page for your company, you need to answer one question:

Would Wikipedia editors consider your company “notable”?

On Wikipedia, “notability” has nothing to do with how compelling your company story is. It means there’s enough independent, reliable coverage about your company that an article can be written from what third parties have already published, without filling in gaps with interpretation, insider knowledge, or marketing claims.

This is also where a lot of brand teams get tripped up. Again, Wikipedia isn’t a marketing channel. It’s not a place to shape messaging or control a narrative. If the only story you can tell is the one you want to tell, the page will be declined during initial submission review or deleted later.

What Notability Actually Looks Like

A company is usually considered notable when it receives significant coverage in multiple reliable sources independent of the company. “Significant coverage” is the key phrase here. Editors are looking for articles that discuss your company in real depth, not quick mentions or short blurbs.

A helpful way to think about it is this: if you can’t outline a neutral article using independent secondary sources alone, you probably don’t have enough notability yet.

Editors typically want coverage that checks these boxes:

  • Independent: Truly third-party reporting. Not press releases, paid placements, sponsored posts, advertorials, partner blogs, or content your PR team arranged. If a piece exists because the company made it happen, editors tend to discount it.
  • Significant: More than a passing mention. A funding announcement, product launch blurb, or event listing can be real coverage and still not be enough. The strongest sources are the ones that explain context, impact, history, or controversy in detail.
  • Secondary: Sources that analyze, summarize, or report on the company from the outside. Primary sources like your website, blog, press page, or social channels can support basic facts in limited cases, but they do not establish notability.
  • Reliable: Publications with editorial oversight and a reputation for accuracy. Big-name outlets can help, but they are not the only option. Trade and industry publications can be excellent sources when they have real editorial standards and provide in-depth coverage, but you can rarely use them to establish notability.
  • Multiple and sustained: A single great source is rarely enough on its own. Editors want to see more than one strong source, ideally across time, so the page can hold up after more people review it.
  • Neutral tone: Even when a source is independent, it can still be weak if it reads like promotion. Glowing profiles, “thought leadership” posts, or contributor content that feels like marketing often carry less weight than staff-reported coverage.

One nuance that matters a lot in practice is that “lots of links” does not equal notability. Companies can appear all over the internet through routine announcements and PR-driven writeups and still fail Wikipedia’s notability test.

What matters is whether independent sources have treated the company as worthy of real, substantive coverage. This also means that magazines and trade publications can’t work as reliable coverage to establish notability. Many industry leaders also run trade organizations, creating a conflict of interest (COI, in Wikipedia’s terms) if their trade publication were to cover their own company or the companies of friends or contributors. 

If your company does not meet this bar yet, that’s not a judgment on it. It just means a Wikipedia article is likely premature, and the better move is to wait until there is enough independent coverage to support a neutral, well-sourced page.

A Note on Conflict of Interest (COI)

If you’re writing about your own company (or you’re paid to write for a company), Wikipedia considers that a conflict of interest (COI). That doesn’t automatically ban you from participating, but it does change how you should approach it.

When creating a new page, submit it to Articles for Creation (AfC) to ensure community editors review it properly. 

When editing an existing page, you want to create your edits in a Sandbox draft (the Sandbox is a personal workspace where you can safely draft and refine changes to an article before submitting them for public review). Then, you submit that Sandbox draft onto the live Wikipedia page’s Talk page, along with a comment that asks community members to review and collaborate on the edits you suggested. Once a community consensus is reached, you can push those edits or additions live. 

An example of a sandbox page on Wikipedia.

Source: https://courses.shroutdocs.org/tutorials/editing-your-wikipedia-sandbox/

It’s also a good idea to disclose your COI connection. Your disclosure should be one of the following:

  • A statement on your User page.
  • A statement on the Talk page accompanying any paid contributions.
  • A statement in the edit summary accompanying any paid contributions.

Avoid directly creating or heavily editing an article and stick to Wikipedia’s COI process to request edits for independent editors to review.

Again, this is about expectations. If your team is hoping to just write a draft and hit “publish,” like you do with a blog, you’re going to have a bad time. But if you do have strong, independent coverage from credible outlets, you’ve got a real shot and can move to the next step.

2. Create a Wikipedia Account

Creating an account is a practical next step if you plan to contribute to Wikipedia. While you don’t need an account to read Wikipedia (or even to edit some pages), registering gives you features that make collaboration and transparency easier.

With an account, you can:

  • Create a User page (a simple profile and a place to draft in a Sandbox).
  • Use your Talk page to communicate with other editors.
  • Build an edit history tied to your username (helpful for credibility and continuity).
  • Work through article creation more smoothly, including drafting and submitting via AfC.

If you add images to your User page, make sure they’re properly licensed. Wikipedia generally accepts only freely licensed uploads.

To register, use Wikipedia’s account creation form.

The Create Account Page on Wikipedia.

After that, you’re set up to start editing, drafting, and participating in the community.

3. Contribute to Existing Pages

Quick reminder from earlier: If you’re connected to the company, you’re dealing with a COI. That’s why Wikipedia prefers that company pages undergo independent review before publication.

As a newbie, a good way to get comfortable on Wikipedia is to start by editing existing articles that have nothing to do with your organization. When you spend time improving clarity, tightening wording, and backing up facts with solid sources, you learn how Wikipedia works, and you build a history of helpful contributions.

As you do that, your account may become autoconfirmed. That usually happens automatically after your account has been around for more than four days and you’ve made at least 10 edits to Wikipedia pages that need them. Autoconfirmed status primarily grants a few basic permissions, such as creating pages and editing some semi-protected articles.

An Autoconfirmed Wikipedia account.

Here’s the key point, though: “Autoconfirmed” does not change your COI situation. Even if you can technically publish a page directly, a company-related article should still be written as a draft and submitted through AfC. This is the step that gets you the independent review Wikipedia expects, and it’s the safest, most appropriate route for a company page.

4. Conduct Research and Gather Sources

Before you write a single line of your Wikipedia draft, do the homework. Wikipedia doesn’t prioritize non-source-backed storytelling. The platform only cares about verifiability, meaning every meaningful claim must be backed by a reliable secondary source that an editor can check. Your company story could play well on Wikipedia, as long as there’s enough reliable evidence to back it up. 

This is where most company pages fall apart. Not because the company isn’t real, but because the sources are thin, biased, or too “inside baseball.”

Why sources matter so much on Wikipedia

Wikipedia runs on two big rules:

  • No original research: You can’t “introduce” new facts, even if they’re true, without proper citation. Which leads to the next point…
  • Cite everything that matters: If it’s notable, controversial, or specific (revenue, awards, history, key dates, acquisitions), you need a secondary source to back it up.

Primary vs. secondary vs. tertiary sources (and how Wikipedia treats them)

Wikipedia breaks sources down into three categories: primary, secondary, and tertiary. Here is a look at each and how they play into the strength of your Wiki page:

  • Primary sources (you): Your website, press releases, investor decks, published reports, filings (e.g., Securities Exchange Commission (SEC), etc.).
    • Upside: Can work for basic, factual details (launch dates, historical milestones, etc.).
    • Downside: Biased by default. Editors won’t accept these for “notability” or big claims like “industry leader.”
  • Secondary sources (best for Wikipedia): Independent journalism, books, academic analysis, reputable profiles.
    • Upside: Shows the world noticed you. This is the backbone of the strongest pages.
    • Downside: Harder to earn, and fluff pieces don’t carry much weight.
  • Tertiary sources: Encyclopedias, databases, reputable directories.
    • Upside: Useful for quick confirmation and context.
    • Downside: Often too shallow to prove notability on their own.

Overall, secondary sources are the most important to your success. By their nature, these sources are pivotal in helping you summarize what experts think about a company or topic in Wikipedia’s voice. Relying heavily on these gives you a really strong case for notability in Wikipedia’s eyes. 

What Makes a Good Wikipedia Source?

Good Wikipedia sources cover topics while maintaining editorial standards. Think major publications, local newspapers of record, respected business outlets, and independent industry analysis. If you’re short on that kind of coverage, that’s usually a PR problem, not a Wikipedia problem. Strengthening your digital PR (DPR) efforts can help you earn credible mentions that hold up under editor scrutiny.

But DPR for a Wikipedia use case must be handled carefully. What tends to work is focusing on independent coverage first. This looks like pitching credible story angles to journalists and outlets that genuinely cover your industry, and accepting that they may say no, or cover the story in a way you can’t control.

When an outlet does publish real, editorial reporting, that’s the kind of secondary source Wikipedia editors are more likely to accept.

Reliable Sources at a Glance

After seeing what Wiki editors consider reliable sources, you might be wondering where you even find sources that hit all their criteria. It helps to look at real-world use cases of which sources are best for your company. Here are some of the types of sites you can choose from.

For company pages, the sources that matter most are the ones that provide significant, independent coverage; the kind that demonstrates notability and gives editors something substantial to cite.

  • Major national/international newsrooms (strongest for notability + facts): Reuters, AP, BBC, Financial Times, The Wall Street Journal, Bloomberg, The New York Times, The Washington Post, NPR (news reporting over opinion).
  • Reputable business and investigative reporting: Deep dives and investigations from established outlets (e.g., ProPublica) can be highly valuable, especially for controversies, legal issues, and accountability reporting.
  • High-quality trade press with editorial oversight (context-dependent): Useful for industry coverage when it’s independent and more than a product announcement or reposted PR. You cannot use trade press as a primary indicator of notability, though.
  • Books from reputable publishers: Especially helpful for founders, company history, and industry impact when written by independent authors and published by established presses.
  • Government and major non-governmental organization (NGO) reports (within remit): Strong for regulatory actions, enforcement, public contracts, or formal assessments (but not a substitute for independent secondary coverage).
  • Medical/health claims (only when relevant): For biomedical statements, prioritize high-quality secondary sources like systematic reviews and authoritative guidelines (MEDRS standard), not individual studies or marketing claims.

Check out Wikipedia’s Perennial Sources list to see which sources have a good community track record because they all meet a high level of fact-checking and editorial standards. But remember, the sources featured in this list are still contextual; it’s not a whitelist. 

Non-reliable Sources

To paint a clearer picture, here are some of the sources you should avoid:

  • Self-published/user-generated content (UGC): Personal blogs, Substack/Medium posts, self-hosted sites, most social media. 
  • Press releases/advertorial: Company press rooms, PR wires; these are fine to state that an announcement occurred, not to establish third-party facts or notability. 
  • Sensational/tabloid sources: Outlets known for gossip/sensationalism; poor for verifying facts. 
  • Anonymous forums and crowdsourced threads: Message boards, comment sections, most Reddit/4chan/Discord posts. 

Wikipedia views these types of sources as weaker because they aren’t research-backed, trustworthy, or credible. The common thread is that they undergo minimal editorial oversight (if any) or, in Reddit’s case, most of the content is UGC and self-published. 

5. Research Your Competition

Like many things when it comes to Wikipedia, researching your competitors is fine if you do it the right way. As you start your research, view your competitors’ pages through the lens of what Wikipedia editors ultimately want. 

The challenge here is that Wikipedia isn’t perfectly consistent. Some company pages are old, lightly monitored, or haven’t been updated to match today’s standards.

When someone says, But other pages include feature lists and product tier breakdowns,” that doesn’t really matter. Editors don’t treat “other pages do it” as a justification. They judge your page on whether it reads like an encyclopedia entry and whether it’s backed by independent, reliable sources.

General Competitor Research Rules

Use competing Wiki pages to answer questions like:

  • What’s the typical structure for a company page in your category? Take note of the typical section titles. (We’ll dive into this next.) 
  • What kind of claims survive without getting reverted? (Neutral, sourced, non-promotional.)
  • What sources are doing the heavy lifting on pages that stay live?

A “Wiki-safe” Research Method

Pick 3–5 competitors with live pages, then audit them like an editor would:

  1. Scan the citations first. Are they mostly independent, secondary news coverage, press releases/company sites, or paid placements?
  2. Check the tone. If it reads like a promotional brochure (feature-by-feature, pricing tiers, “best-in-class”), that’s a red flag, even if it hasn’t been removed yet.
  3. Look at the page history and Talk page. Lots of reverts, banners, or sourcing disputes usually mean the page is shaky.
  4. Note what’s missing. If competitors avoid detailed feature lists, that’s usually a sign that those details don’t belong on Wikipedia.

6. Create an Outline

Once you’ve got your sources, your outline has a starting point. The hard part is deciding what belongs.

On Wikipedia, an outline is not “everything you want to say.” It’s you making careful decisions about what independent, reliable sources have actually covered, what they have not covered, and what deserves space without turning the page into a brochure. That takes judgment, and it often takes multiple passes.

The mindset you want is simple: Wikipedia pages are built around what reliable secondary sources already said about the subject. Your outline is how you organize those sourced facts into a structure that editors recognize and are willing to review.

Start with the standard Wikipedia “shape”

Most company pages follow a formulaic layout:

  • Infobox (quick facts): Founded, founders, headquarters, industry, key people, website, and similar basics. Only include items you can verify.
  • Lead (opening summary): 2–4 neutral sentences explaining what the company is, where it’s based, what it does at a high level, and why it’s notable. This is not a tagline.
  • History: Founding and major milestones, expansions, acquisitions, funding or IPO, only if independent sources cover them, and major pivots. Focus on events that third parties actually reported.
  • Operations/Business (optional, and only if sourced): What the company does at a high level and what markets it serves. Avoid feature-by-feature descriptions and pricing tiers.
  • Leadership/Ownership (optional): Only if reliable sources discuss executives, ownership changes, or governance in a meaningful way.
  • Reception/Controversies (only if they exist in sources): Reviews, notable criticism, legal issues, regulatory actions, all written neutrally and backed by sources.
  • See also / References / External links: References do the heavy lifting; external links are usually minimal (often just the official site).
An example company Wikipedia page.

Using Your Sources to Build the Outline

Start with your strongest independent secondary sources and work outward. As you read through them, you’re identifying what the coverage actually emphasizes.

As you review sources, pull out:

  • Events they cover (those become history sections)
  • Claims they support (those become lead and operations sections)
  • Any recurring themes across sources (those become section headings)

Each major section in your outline should be supported by multiple secondary sources, not a single mention. Also, keep an eye on the length as you draft. Wikipedia discourages overly long articles unless the amount of independent coverage truly warrants it. If a section or topic isn’t discussed in depth by reliable secondary sources, it usually doesn’t belong at length in the article.

If you focus on covering the topic from an encyclopedic angle and you leave out anything that feels like marketing, you will give your draft a much better chance of surviving review.

7. Write a Draft of Your Wikipedia Page

Take your time as you write a draft of your Wikipedia page from your outline. You want your content to be source-backed, thorough, thoughtful, and genuinely useful, giving readers the information they came for.

At this stage, it’s best to write your draft in a Wikipedia Sandbox. As mentioned earlier, this is a personal workspace where you can draft safely, revise freely, and share the link with others for informal feedback without accidentally publishing anything live.

While a Wikipedia page can support your broader visibility, the platform’s purpose is encyclopedic and impartial. Anything that reads as emotional, salesy, or promotional is likely to be flagged and can lead to rejection later in the process.

Aim for short, direct sentences that stick to verifiable facts. And those facts need strong secondary sources. For example, if you write, “Spot ran to the big oak tree yesterday,” that claim would need a source. Not just any source, but a credible, independent secondary source that Wikipedia considers reliable.

It’s also critical to remember you’re writing on behalf of Wikipedia. Aka, you’re writing in Wikipedia’s unbiased, impartial, and neutral voice.

Here are some examples to show what this looks like in practice:

Example 1: Product Description

  • Promotional: “XYZ Software is a revolutionary, industry-leading platform that empowers businesses to achieve unprecedented productivity gains. With its cutting-edge AI technology and intuitive interface, XYZ transforms the way teams collaborate, delivering exceptional results that exceed expectations.“​
  • Neutral: “XYZ Software is a project management platform that combines task tracking, team messaging, and file sharing. The software is used by businesses to coordinate work across departments.[1][2]“​

Example 2: Company History

  • Promotional: “Founded by visionary entrepreneur Jane Smith, the company quickly rose to prominence as a game-changer in the industry. Through relentless innovation and unwavering commitment to excellence, it has become the trusted choice for Fortune 500 companies worldwide.“​
  • Neutral: “The company was founded in 2015 by Jane Smith in Seattle.[3] It launched its enterprise tier in 2019 and rebranded from “TaskFlow” to its current name in 2021.[4][5]“​

Wikipedia also defines “promotional” language differently. It’s more than simply using words like “revolutionary” or “legendary.” Factually correct statements can still be considered “promotional” in a Wikipedia editor’s eyes if they meet certain structure and emphasis criteria:

  • Long, comprehensive feature inventories.​
  • Plan/tier breakdowns that resemble packaging (“Free vs. Premium vs. Enterprise”).​
  • Performance claims that read like sales positioning.​
  • Product-benefit phrasing stacked repeatedly (“includes tools for…,” “enables…,” “helps…”).​
  • Details that feel like purchase guidance (pricing, quotas, storage limits, admin entitlements).​

Let’s talk about specs and features for a second. If your company is well-known for a particular product or service, it can be tempting to include a specification or feature list on your Wikipedia page. Unfortunately, that can cause problems with Wikipedia for several reasons.

Here’s why:

  1. Wikipedia isn’t a manual or catalog: Wikipedia tries to avoid becoming vendor documentation. Specs and feature matrices belong on the company site, in the documentation center, in release notes, or on third-party comparison sites, not in an encyclopedia.​
  2. Specs change constantly: Feature sets, tiers, storage limits, and admin/security capabilities change frequently. Wikipedia content must remain stable and verifiable over time. Highly granular spec content becomes outdated quickly and attracts disputes.​
  3. It’s hard to verify neutrally: If the only source for a feature or tier is the vendor’s own site or press release, Wikipedia considers that primary sourcing; useful for limited factual verification, but not ideal for describing capabilities in detail or making value claims.​
  4. “Undue weight” and imbalance: Even accurate feature lists can give a product more prominence than independent sources do. Wikipedia tries to reflect external coverage: if reliable third parties don’t treat a feature as notable, Wikipedia typically won’t either.​

What a Company’s Wikipedia Draft Should Look Like

Much like sourcing, it’s hard to imagine what an acceptable draft should look like, given all of Wikipedia’s guidelines. Here’s a brief rundown of what a solid draft should look like when you’re done:

  • A clear, high-level description of what a company is (one paragraph, not a feature catalog).​
  • A history/timeline of major milestones (launches, renames, major releases) backed by independent sources.​
  • Widely covered integrations/partnerships only when reported by reliable third parties.​
  • A short, selective “features” summary only for capabilities that independent sources treat as notable and cover in-depth.​

8. Upload Your Page into the Article Wizard

Once your Sandbox draft is in good shape, move over to the Wikipedia Article Wizard. The Wizard is the guided tool that helps you move what you wrote from your Sandbox into Wikipedia’s Draft space, which is where new articles are typically prepared before they go live.

For company-related pages, the key takeaway is that the Wizard is the structured path to getting your draft into the right place so it can be submitted for independent review.

The Wikipedia Article Wizard confirming a page was uploaded.

9. Submit Your Article for Review

Now that your draft is in Draft space, you’re ready for the step that triggers formal evaluation by the community. Submit your draft through Articles for Creation by clicking “Submit for review.” This is when your draft enters the AfC queue, and a volunteer reviewer takes a look.

The timeline can range from a few weeks to a few months, depending on backlog and whether the reviewer requests changes. It’s also common for drafts to be declined at first, with feedback you’ll need to address before approval.

At NPD, we’ve found that sticking with AfC is the best practice for companies looking to go live. Even though autoconfirmed accounts may have the technical ability to publish directly, that path often creates more friction for company-related topics. AfC sets expectations for independent review from the start and helps reduce avoidable issues related to COI and other Wikipedia guidelines.

10. Continue Making Improvements

Once your page is accepted, the work is not really over.

Wikipedia is editable by anyone, so changes can happen at any time. Some edits will be helpful, some will be mistaken, and some may reflect a negative point of view. The best approach is to keep an eye on the page so you can understand what is changing and respond appropriately, usually by suggesting improvements on the Talk page or updating the article with strong, independent sourcing.

As the page gets more visibility and gains traction on Google and LLMs, focus on accuracy and neutrality rather than “updating marketing messaging.” Wikipedia is not the place for routine product updates, but it is the right place to reflect significant, well-covered developments when reliable third-party sources have written about them.

You should also plan for the possibility that your draft will be declined. That is common, especially for company-related topics. If it happens, do not get discouraged. Read the reviewer’s comments carefully, make the requested changes, and resubmit when you have addressed the specific issues that kept the draft from being accepted.

FAQs

Should I build a Wikipedia page for my company?

A Wikipedia page can be a meaningful credibility asset, but it isn’t a fit for every company. The deciding factor is whether there’s enough independent, reliable secondary coverage to support a neutral article. If you can’t outline the page using third-party sources alone, it’s usually too early.

If your company does qualify, the value tends to be indirect: stronger brand legitimacy, clearer “who you are” context in search results, and more consistent entity information across the web. It’s less about immediate conversions and more about long-term visibility and trust signals that can compound.

Yes. Creating, publishing, and maintaining a company page is challenging because Wikipedia is community-reviewed and built around strict expectations: neutral tone, verifiable claims, and high-quality sourcing. You also have to plan for ongoing edits and scrutiny after the page goes live.

The opportunity is achievable if you have strong independent coverage and treat the process as encyclopedic documentation rather than company messaging.

How do I know if my Wikipedia page will be published?

There’s no guaranteed way to know. Even well-prepared drafts can be declined, revised, and resubmitted, especially for company topics.

Your best indicators are practical: you have multiple independent sources with significant coverage, your draft reads neutrally (not like marketing), and you submit through the Articles for Creation (AfC) process so reviewers can evaluate it in draft space.

How long will my Wikipedia article be under review before publication?

Review time varies widely. Some drafts are reviewed quickly, but it’s also common for company-related submissions to take weeks (or longer) depending on backlog and how many revisions are needed. A decline doesn’t mean “never”; it usually means “not yet” or “needs stronger sourcing and a more neutral rewrite.”

Conclusion

If you’re looking to increase traffic, improve your search everywhere visibility, or build credibility, Wikipedia can be part of the equation. But it’s not a marketing channel, and it isn’t built for companies to shape their narratives. It’s a community-edited encyclopedia that summarizes what independent, reliable sources have already said about you.

Where Wikipedia can help is in discovery and trust signals. A stable, well-sourced page often shows up prominently for company and topic queries, and it can reinforce consistent “entity facts” that search engines and other knowledge systems use to understand companies. 

That’s also why Wikipedia often pairs well with entity SEO. When key details about your organization are documented consistently across reputable sources, your company is easier to interpret and surface accurately across platforms, including some LLM-style experiences. Results may vary based on implementation, the strength of independent coverage, and ongoing community review.

As you evaluate whether your company is a good fit for a Wikipedia page, keep in mind that the process is complicated, and it won’t be fully in your control. What matters most is having enough independent, reliable secondary coverage to justify a stand-alone article and being willing to follow Wikipedia’s COI expectations.

Read more at Read More

How to Build Audience Personas for Modern Search + Template

Search has changed, and so should your audience personas.

Your audience searches across Google, ChatGPT, Reddit, YouTube, and many other channels.

Knowing who they are isn’t enough anymore. You need to know how they search.

Search-focused audience personas fill gaps that traditional personas miss.

Think insights like:

  • Where this person actually goes for answers
  • What triggers them to look for solutions right now
  • Which proof points win their trust

And you don’t need months of research or expensive tools to build them.

An audience persona is a profile of who you’re creating for — what they need, how they search, and what makes them trust (or tune out). Done well, it aligns your team around a shared understanding of who you’re serving.


In this guide, I’ll walk you through nine strategic questions that dig deep into your persona’s search behavior. I’ve also included AI prompts to speed up your analysis.

They’ll help you spot patterns and synthesize findings without the manual work.

By the end, you’ll have a complete audience persona to guide your content strategy.

Free template: Download our audience persona template to document your insights. It includes a persona example for a fictional SaaS brand to guide you through the process.


1. Where Is Your Audience Asking Questions?

Answer this question to find out:

  • Where you need to build authority and presence
  • Which platforms to target for every persona
  • Which formats work well for each persona


Knowing where your persona hangs out tells you which channels influence their decisions.

So, you can show up in places they already trust.

It also reveals how they think and what will resonate with them.

For example, someone posting on Reddit wants honest advice based on lived experiences. But someone searching on TikTok wants visual content like tutorials or unboxing videos.

Where Your Audience Searches Reveals How They Think

How to Answer This Question

Start with an audience intelligence tool that lets you identify your persona’s preferred platforms and communities.

I’ll be using SparkToro.

Note: Throughout this guide, I’ll walk you through this persona-building process using the example of Podlinko, a fictional podcasting software. You’ll see every step of the research in action, so you can replicate it for your own business.


For this example, we’re building out one of Podlinko’s core personas: Marcus, a marketing professional on a one-person or small team team, so he’s scrappy and in-the-weeds.

Pro tip: Start with one primary persona and build it completely before adding others. Focus on your most valuable customer segment (the one driving the highest revenue for your business).


In SparkToro, enter a relevant keyword that describes your persona’s professional identity or core interests.

This could be their job title, industry, or a topic they care deeply about.

I went with “how to start a podcast.” Marcus would likely search for this early in his journey.

SparkToro – How to start a podcast

The report gives a pretty solid overview of Marcus’s online behavior.

For example, Google, ChatGPT, YouTube, and Facebook are his primary research channels.

SparkToro – Audience Research

But it could be worth testing a few other platforms too.

Compared to the average user, he’s 24.66% more likely to use X and 12.92% more likely to use TikTok.

SparkToro – Social networks report

The report also tells me the specific YouTube channels where he spends time.

He’s watching automation, editing, and business tutorials.

SparkToro – YouTube Channels & Podcasts

He’s also active in multiple industry-related Reddit communities.

Maybe he’s posting, commenting, or even just lurking to read advice.

SparkToro – SubReddits

Since Marcus uses ChatGPT, I also did a quick search on this platform to see which sources the platform frequently cites.

I searched for some prompts he might ask, like “Which podcast hosting platforms should I use for marketing?”

If you see large language models (LLMs) repeatedly mention the same sources, they likely carry authority for the topic.

And by extension, they influence your persona’s research as well.

ChatGPT – Sources – Podcast hosting platforms

Compare these sources to the ones you identified earlier. If they match, you have validation.

If they’re different, assess which ones to add to your persona document.

Here’s how I filled out the persona template with Marcus’s search behavior:

Persona template – Search behavior

2. What Exact Questions Are They Asking?

Answer this question to find out:

  • What language to mirror in your content
  • How to structure content for AI visibility
  • What content gaps exist in your market


Your buyer persona’s language rarely matches marketing jargon.

Companies might talk about “podcast production tools” and “integrated workflows.”

But personas use more personal and specific language:

  • What’s the cheapest way to record remote podcasts?
  • How long does it take to edit a 30-minute podcast?

Knowing your audience’s actual questions reveals the gap between how you describe your solution and how they experience the problem.

And shows you exactly how to bridge it.

How to Answer This Question

Start by going to the platforms and communities you identified in Question 1.

Search 3-5 topics related to your persona.

Review the context around headlines, posts, and comments:

  • How they phrase questions (exact words matter)
  • What emotions do they express
  • What outcomes they’re trying to achieve

Pro tip: As you research, save persona comments, discussions, and reviews in full — not just snippets. You’ll analyze the same sources in Questions 3-5. But through different lenses (challenges, triggers, language patterns). Having everything saved means you won’t need to revisit platforms multiple times.


For example, I searched “how to start a podcast for a business” on Google.

Then, I checked People Also Ask for related questions Marcus might have:

PAA – How to start a podcast for a business

On YouTube, I searched “how to edit a podcast” and reviewed video comments.

Users asked follow-up questions about mic issues and screen sharing.

This gave me insight into language and questions beyond the video’s main topic.

YouTube – How to edit a podcast – Comments

In Facebook Groups, I found users asking questions related to their goals, constraints, and challenges.

It also provided the unfiltered language Marcus uses when he’s stuck.

Facebook – Podcasters on Facebook

Now, use a keyword research tool to visualize how your persona’s questions connect throughout their journey.

I used AlsoAsked for this task. But AnswerThePublic and Semrush’s Topic Research tool would also work.

For Marcus, I searched “Best AI podcasting editing software,” which revealed this path:

Which AI tool is best for audio editing? → Can I use AI to edit audio? → Which software do professionals use for audio editing? → How much does AI audio editor cost?

AlsoAsked – Best Podcast Software

It’s helpful to visualize how Marcus’s questions change as he progresses through his search.

Next, learn the questions your persona asks in AI search.

You’ll need a specialized tool like Semrush’s AI Visibility Toolkit for this task.

It tells you the exact prompts people use when searching topics related to your brand.

(And if your brand appears in the answers.)

If you don’t have a subscription, sign up for a free trial of Semrush One, which includes the AI Visibility Toolkit and Semrush Pro.

Since Podlinko is fictional, I used a real podcasting platform (Zencastr.com) for this example.

Semrush – Visibility Overview – Zencastr

This brand appears often in AI answers for user questions like:

  • What equipment do I need to create a professional podcast setup?
  • Can you recommend popular tools for managing and promoting online radio or podcasts?

Semrush – Visibility Overview – Zencastr – Performing Topics

You’ll also see citation gaps — questions where your brand isn’t mentioned. These reveal content opportunities.

For this brand, one gap includes:

“Which AI tools are best for recording, editing, and distributing an AI-focused podcast?”

Semrush – Topic Opportunities – Questions

After reviewing all the questions I gathered, I narrowed them down to the top 5 for the template:

Top 5 template questions

3. What Challenges Influence Their Search Behavior?

Answer this question to find out:

  • What constraints influence their decision-making process
  • How to anticipate objections before they arise
  • What kind of solutions does your persona need


Challenges are the ongoing issues driving your persona’s search behavior. These overarching problems shape their decisions to find a solution.

Understanding these challenges can help you:

  • Position your solution in the context of these pain points
  • Anticipate and address objections before they come up
  • Structure your campaigns to speak directly to their limitations

How to Answer This Question

Review the questions you collected in Question 2 to identify underlying pain points.

For example, this Facebook Group post contains some telling language for Marcus’s persona:

Facebook – Telling language for Marcus's persona

Specific phrases highlight ongoing challenges:

  • “Tech support is no help”
  • Can’t find an editing software that consistently works”

Now, visit industry-specific review platforms.

Check G2, Capterra, Trustpilot, Amazon, Yelp, or another site, depending on your niche.

Look for reviews where people describe recurring frustrations.

Positive reviews may mention what drove a user to seek a new solution. For example, this one references poor audio and video quality:

G2 – Riverside – Review

Negative reviews reveal what users constantly struggle with.

Unresolved pain points often push people to find workarounds or alternatives.

This user noted issues with a podcasting tool, including loss of backups, unreliable tech, and more.

G2 – Riverside – Negative review

Pay close attention to the language people use. Word choice can signal underlying feelings and constraints.

When someone asks for the “easiest” and “most cost-effective” solution, they’re signaling:

  • Limited resources
  • Low confidence
  • Risk aversion

After reviewing conversations and communities, you’ll likely have dozens of data points.

Copy the reviews, questions, and phrases into an AI tool to identify your persona’s top challenges.

Use this prompt:

Based on these reviews and discussions, identify the five biggest challenges for this persona.

For each challenge, show:

(1) exact phrases they use to describe it

(2) what constraints make it harder (budget, time, skills)

(3) how it influences where and when they search.

Format as a table.


This analysis helped me identify Marcus’s recurring challenges:

Persona template – Challenges

4. What Triggers Them to Search Right Now?

Answer this question to find out:

  • What emotional and situational context should you address in your content
  • How to structure content for different urgency levels
  • Which pain points to lead with


Search triggers explain why your audience is ready to take action.

But they’re not the same as challenges.

Challenges are ongoing constraints your persona faces. This could be a limited budget, small team, or skill gap.

Triggers are the specific events or goals that push them to act right now. Like a looming deadline or a competitor launching a podcast.

Understanding triggers helps you reach your persona when they’re most receptive.

Decoding Persona Search Triggers

How to Answer This Question

If you have access to internal data, start there.

Your sales and customer support teams can spot patterns that push prospects from browsing to buying.

For example, your sales conversations might reveal that one of Marcus’s triggers is urgency. His manager might ask him to improve the sound quality by the next episode, prompting his search.

If you don’t have internal intel, use tools like AnswerThePublic, AlsoAsked, or Semrush’s Keyword Magic Tool.

Keyword Magic Tool – Podcast editing

This will help you identify the language people use when they’re ready to act.

For Marcus, my AlsoAsked research led to questions like:

  • “Can I record a podcast with just my phone?” This may suggest a desire to start immediately, without professional equipment.
  • “How to make a podcast with someone far away” could suggest the trigger of a sudden need to work with a remote guest/host

AlsoAsked – Questions

You can also refer back to your research on community spaces.

(Or conduct additional audience research, if needed.)

These spaces are where people describe the exact moments they decide to take action. Aka plateaus, milestones, and failed attempts.

When I searched “podcast marketing” on Reddit, I found a post from someone experiencing clear triggers:

Reddit – Podcast marketing

This user has been unable to get a consistent flow of organic listeners despite high-quality content.

Trigger: A growth plateau that pushed him to ask for help.

He’s also trying to hit his first 1,000 listeners.

Trigger: A goal that pushed him to look for solutions.

If you collected a lot of content, upload it to an AI tool to quickly identify triggers.

Use this prompt:

Analyze these community posts and discussions. Identify the specific trigger moments that pushed people to actively search for solutions.

For each trigger, show:

  1. The exact moment or event described (quote the language they use)
  2. The type of trigger (situational, temporal, emotional, or goal-driven)
  3. What action did they take as a result

Format as a table.


After analyzing the content I gathered, I identified the key triggers pushing Marcus to search:

Persona template – Triggers

5. What Language Resonates (and What Turns Them Off)?

Answer this question to find out:

  • Which messaging angles resonate
  • What tones build trust with your audience
  • Which phrases trigger objections or skepticism


The words you use can affect whether your persona trusts you or tunes out.

The right language makes people feel understood. The wrong language creates friction and drives them away.

When you know what resonates, you can create messaging that builds trust and motivates your personas to act.

How to Answer This Question

Refer back to your research from Questions 3 and 4.

This time, focus specifically on language patterns in reviews and community discussions.

Look at:

  • Exact phrases people use to describe success, relief, or satisfaction
  • Words highlighting frustration, disappointment, and concerns

For example, on Capterra, users praised podcasting platforms that “do a lot” and let them “distribute with ease.”

Capterra – Review on podcasting platform

This language signals Marcus’s preference for all-in-one platforms.

He would likely connect with messaging that emphasizes functionality without complexity.

Next, review the content you previously gathered from community spaces.

In r/podcasting, users like Marcus write with direct, benefit-focused language:

Reddit – r/podcasting – Benefit focused language

Notice what he values: simplicity and concrete outcomes (“automatic transcripts”).

He’s not mentioning jargon like “AI-powered transcription engine” or “enterprise-grade recording infrastructure.”

Plain language that emphasizes quick results over technical capabilities works best with this persona.

Once you have enough data, use this LLM prompt to identify language patterns:

Analyze these customer reviews and community discussions I’ve shared. Identify:

  1. Most common words and phrases people use to describe positive experiences
  2. Most common words and phrases that signal frustration or concerns
  3. Emotional undertones in how they describe problems and solutions

Create a table organizing these insights.


This analysis revealed the specific language that Marcus reacts to positively (and negatively).

Persona template – Language

6. What Content Types Do They Engage With Most?

Answer this question to find out:

  • Content types to prioritize in your content strategy
  • How to structure content for maximum engagement
  • What length and style work best for each format


Knowing the content types your audience prefers has multiple benefits.

It lets you create content that captures your persona’s attention and keeps them engaged.

Think about it: You could write the most comprehensive guide on podcast equipment.

But if your ideal customer prefers video reviews, they’ll scroll right past it.

How to Answer This Question

You identified your persona’s most-used platforms in Question 1. Now analyze which content formats perform best on each.

Conduct a few Google Searches to identify popular content types.

You’ll learn what users (and search engines) prefer for specific queries. Look at videos, written guides, infographics, carousels, podcasts, and more.

For example, when I search “how to set up podcast equipment,” the top results are a mix: long-form articles, video tutorials, and community discussions.

Google SERP – How to set up podcast equipment

But organic search rankings don’t tell the full story.

Analyze content directly on your persona’s preferred platforms, too.

I searched “How to distribute a podcast” on YouTube and assessed the top 20 videos and Shorts for:

  • Video length
  • Views
  • Comments
  • Engagement patterns

Look at the creators your persona follows on each platform. (From the SparkToro report in Question 1).

SparkToro – Report

Pay attention to:

  • Content types drive the most engagement (videos vs. carousels vs. threads)
  • How these creators structure content (length, style, tone)
  • Which topics resonate most with their audience

Once you’ve collected this data, look for patterns.

Or drop your data into an LLM and ask it to find the patterns for you:

Analyze this engagement data I’ve collected for my audience persona.

Identify:

  1. Which video lengths perform best (views, comments, engagement rate) and why
  2. Which content styles generate the most engagement (tutorials, vlogs, behind-the-scenes, etc.)
  3. Any patterns in thumbnails, titles, or formats that consistently perform well

Summarize my persona’s content preferences by video type and rank them as low, medium, or high


For Marcus, I learned that 5- to 15-minute video tutorials generated the highest engagement.

Shorts consistently underperformed for how-to queries, showing his preference for in-depth tutorials.

I documented my findings and ranked each content type by engagement level: high, medium, or low.

Persona template – Content Preferences

7. What Proof Points and Signals Matter?

Answer this question to find out:

  • What proof points influence buyers
  • How to structure case studies and testimonials
  • Where to place proof points to win people’s trust


Proof points can influence whether someone acts on your content or bounces.

They’re also a ranking factor.

Search engines and LLMs reward content that demonstrates Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T).

What is E-E-A-T

But different personas might value different proof points.

Understanding what matters to each persona is crucial to building trust and visibility.

How to Answer This Question

Identify the most common trust markers on your persona’s preferred sites.

Look for:

  • Author credentials: Bylines with relevant expertise
  • Methods: Transparency about the method for creating this content
  • Citations: Links to studies, expert quotes, industry reports, original research
  • Recency signals: Publication and last updated dates
  • Visual proof: Screenshots, before/after comparisons, annotated walkthroughs
  • Social validation: Comment sections, user discussions, engagement metrics

Use Semrush’s Keyword Overview tool to find this information.

Note: A free Semrush account gives you 10 searches in this tool per day. Or you can use this link to access a free Semrush One trial.


Enter your keyword (I used “how to start a podcast”).

Scroll to the SERP Analysis report to view the ranking domains.

Keyword Analytics – How to start a podcast – SERP Analysis – URL

Aim to review 20 to 50 pages for the best results. (Create a spreadsheet to organize the information.)

Identify which proof points they use and how prominently they’re displayed.

Here’s how I did this for one of the articles I assessed:

  • Quantified track record: “Since 2009, Buzzsprout has helped over 400,000 podcasters”
  • First-person experience: “I’ve drawn on lessons from my own podcasts and thousands of conversations with creators”
  • Third-party sources: Expert advice cited from Apple Podcasts on naming conventions
  • Visual demonstrations: Embedded tutorials showing recommendations in action

Buzzsprout – How to start a podcast

Then, use an LLM to quickly spot patterns:

I’ve analyzed top-ranking pages for my persona and uploaded my findings.

Identify:

  1. Which proof points appear most frequently (e.g., “8 out of 10 pages include X”)
  2. How these proof points are displayed (above the fold, in sidebar, throughout content)
  3. Which combinations of proof points appear together most often

Format as a summary with the top 5 most common patterns.


Ultimately, you’ll want to infuse your content with these same trust markers to attract and convert your persona.

After identifying Marcus’s top proof points, I ranked them from medium to high in the template:

Persona template – Proof points

8. Where (and How) Should You Distribute Content to Reach This Persona?

Answer this question to find out:

  • Which platforms deserve your investment
  • What content formats work best on each platform
  • How to maximize organic reach through distribution


Where you distribute content determines whether it reaches your audience.

If you only publish content on your website but buyers find solutions on LinkedIn, you’re overlooking key touchpoints.

Even worse, you’re invisible on major platforms that LLMs scan for answers, recommendations, and citations.

How to Answer This Question

By now, you know your audience persona’s top platforms.

These are your initial distribution targets.

But you’ll ideally be able to validate them against real behavioral data.

If possible, survey recent customers to find concrete patterns about their search behavior.

Send a short survey to customers who converted in the last 90 days:

  • Where did you first hear about us?
  • Where do you go for advice about [primary pain points]?
  • What platforms do you use when researching [your product category]?
  • How do you prefer to learn about new solutions in your workflow?

Once responses come in, look for patterns in how each segment discovers, researches, and evaluates solutions.

Here’s a prompt you can use in an AI tool for faster analysis:

I surveyed recent customers about their search and discovery behavior.

Analyze this data and identify:

  1. The top 3-5 platforms where customers discovered us or researched solutions
  2. Common pain points or information needs they mentioned
  3. Preferred content formats for learning about solutions
  4. Any patterns in how different customer segments discover and evaluate us

Highlight the platforms and channels that appear most frequently, and flag any gaps between where customers search and where we currently have a presence.


Next, cross-reference your research against existing data in Google Analytics.

Open Google Analytics and navigate to Reports > Lifecycle > Acquisition > Traffic acquisition.

GA – Traffic acquisition

Sort by engagement rate or average session duration to see which channels drive genuinely engaged visitors.

Look for high time on site (2+ minutes) and multiple pages per session (3+).

Then, map each platform to the content format that performs best there.

Combine insights from Question 1 (preferred platforms) and Question 6 (preferred formats) to build your distribution strategy.

Here’s what this looks like for Marcus:

Persona template – Distribution strategy

9. What Keeps This Persona Coming Back?

Answer this question to find out:

  • What product features or experiences to double down on
  • How to position your solution beyond initial use cases
  • What content to create for existing customers


Winning your audience’s attention once is easy. Earning it repeatedly is the real challenge.

Understanding what keeps your persona engaged is the key to getting them to return.

How to Answer This Question

Review all the audience persona insights you’ve gathered so far to identify recurring needs.

Look at triggers, pain points, content preferences, and community discussions.

Pinpoints problems that can’t be solved with a single article or resource.

This could include:

  • Tasks they do every week (editing, distribution, promotion)
  • Decisions they face with each piece of content (format, platform, messaging)
  • Skills they’re continuously learning (new tools, changing algorithms)
  • Friction points that slow them down every time

Then, outline the content types that repeatedly solve these problems.

Think tools, templates, checklists, and guides they’ll use repeatedly.

If you don’t want to do this manually, drop this prompt into an AI tool to synthesize your findings:

Based on my audience persona research, here’s what I’ve learned:

Questions they ask: [Paste top questions from Q2]

Challenges they face: [Paste challenges from Q3]

Triggers that push them to act: [Paste triggers from Q4]

Their preferred content types: [Paste formats from Q6]

Identify recurring problems they face repeatedly (not one-time issues).

For each recurring problem:

  1. Describe the problem in their own words
  2. Explain why it’s recurring (weekly task, ongoing decision, changing landscape, etc.)
  3. Suggest 2-3 content types that would provide repeatable value each time they face this problem

Format as a table with columns: Problem | Why It’s Recurring | Content Solutions


For Marcus, this could look something like this:

Problem areas Content assets
Marcus spends too long cleaning audio
  • Editing workflow template (step-by-step, repeatable each week)
  • Breakdown video: “How to Edit a 30-minute Episode in Under 12 Minutes”
Marcus wants consistent reach across platforms
  • Podcast distribution checklist (Apple, Spotify, YouTube, LinkedIn, newsletter)
  • Repurposing templates (social snippets, video clips, carousel outlines)

Every time Marcus faces these challenges, he can turn to them for a reliable solution.

These are the content types that have repeatable value for him:

Persona template – What brings Marcus back

Build Audience Personas That Win AI Visibility

Forget surface-level demographics.

These nine audience persona questions give you actionable, in-depth search intelligence.

You now know a lot about your persona.

You’ve uncovered where they search, what language resonates, and which proof points earn trust.

This is everything you need to show up in the right places with the right message.

If you haven’t already, download our audience persona template to organize your research.

Use it to guide your content creation, search strategy, and distribution efforts.

Your next move: Expand your visibility further with our guide to ranking in AI search. Our Seen & Trusted Framework will help you increase mentions, citations, and recommendations for your brand.

The post How to Build Audience Personas for Modern Search + Template appeared first on Backlinko.

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How to Leverage Google Natural Language to Boost Your ASO Efforts 

Over the past year, Google has significantly accelerated its investment in artificial intelligence and machine learning across its products and platforms. While most marketers are familiar with ChatGPT, Google has been advancing its own AI capabilities in parallel, including the relaunch of Bard as Gemini and the steady rollout of AI-assisted features across Google Play.

For app marketers and ASO specialists, these developments are not abstract. They represent a fundamental shift in how apps are understood, categorized, and surfaced to users. Google Play is no longer relying primarily on keyword matching. Instead, it is moving toward a deeper, semantic understanding of apps, their functionality, and the problems they solve.

This evolution raises an important question. If Google increasingly generates, interprets, and evaluates app metadata itself, how do ASO teams maintain control, differentiation, and long-term competitive advantage?

One underutilized answer lies in a tool that has existed for years but is rarely discussed in an ASO context: the Google Natural Language.

Key Takeaways

  • Google Play is moving away from keyword density and toward semantic understanding driven by machine learning and natural language processing.
  • The Google Natural Language provides valuable insight into how Google interprets app metadata, including entities, sentiment, and category relevance.
  • Optimizing for category confidence and entity relevance can improve keyword coverage and resilience during algorithm updates.
  • ASO teams that align metadata with user intent and natural language patterns are better positioned for long-term discovery performance.
  • Using tools like the Google Natural Language helps future-proof ASO strategies as automation and AI-driven ranking signals continue to expand.

Why Traditional ASO Signals Are Losing Impact

Before exploring how the Google Natural Language can support ASO, it is important to understand the broader shifts in Google Play’s ranking algorithms.

Over the past two years, Google Play has shifted away from frequent, visible algorithm swings towards a more continuous learning model. While ASO teams still see volatility, it is now driven less by discrete updates and more by ongoing recalibration as models ingest new behavioural, linguistic, and performance data. Reindexing events still occur, but they are increasingly tied to semantic reassessment rather than simple metadata changes.

At the same time, the effectiveness of traditional optimization levers such as keyword density, exact-match repetition, and rigid keyword placement has continued to erode. These tactics no longer align with how Google Play evaluates relevance.

Like Google Search, Google Play is now firmly optimized for meaning, not mechanics. Its systems are designed to understand intent, function, and audience context rather than rely on surface-level keyword signals. The algorithm is increasingly capable of identifying what an app does, who it serves, and the problems it solves, even when those ideas are expressed using varied, natural language.

This is where natural language processing becomes central to modern ASO tools and practices.

Explanation of Natural Language processing.

What is the Goal of the Google Natural Language

Google Natural Language is designed to help machines understand human language in a way that more closely mirrors human interpretation. It powers a wide range of Google products and capabilities, including sentiment analysis, entity recognition, content classification, and contextual understanding.

In practical terms, it analyzes a body of text and identifies:

  • The overall sentiment and tone.
  • Key entities and their relative importance.
  • The categories and subcategories that the content most strongly aligns with.

For ASO teams, this offers a rare opportunity. Instead of guessing how Google might interpret app metadata, it provides a proxy for understanding how Google’s machine learning systems read and categorise text.

Used correctly, it can help ASO specialists align metadata more closely with Google’s evolving ranking logic.

How Google Natural Language Applies to ASO

When applied to app metadata, Google Natural Language can reveal how Google is likely to associate an app with certain concepts, categories, and keyword themes. This insight is particularly valuable as keyword density becomes less influential and semantic relevance takes priority.

Below are the key components that matter most for ASO.

Sentiment Analysis

Sentiment analysis evaluates the emotional tone of a piece of text and categorises it as positive, negative, or neutral. While sentiment is not a primary ranking factor for app discovery, it does provide useful contextual information.

For example, overly promotional, aggressive, or unclear language can introduce noise into metadata. Reviewing sentiment outputs can help teams ensure that descriptions maintain a clear, neutral, and informative tone that supports both user trust and algorithmic interpretation.

Entity Recognition and Salience

Entity recognition identifies specific entities within a text and classifies them into predefined types such as company, product, feature, or concept. Each entity is assigned a salience score, which reflects how central that entity is to the overall content.

In an ASO context, entities might include:

  • Core app features
  • Functional use cases
  • Industry-specific terms
  • Recognisable product or service concepts

Salience scores range from 0 to 1.0. Higher scores indicate that an entity plays a more important role in defining the content.

From an optimization perspective, this is critical. If key features or use cases are not appearing as highly salient, it suggests Google may not be strongly associating the app with those concepts.

Strategically incorporating relevant entities into metadata in a natural, user-focused way can improve clarity and strengthen topical relevance. Placement also matters. Important entities that appear early in descriptions or are reinforced toward the end of the text tend to carry more weight.

Metadata entities.

Categories and Confidence Scores

Category classification is arguably the most impactful element of Google Natural Language for ASO.

When text is analyzed, it assigns it to one or more categories and subcategories, each with an associated confidence score. These scores indicate how strongly the content aligns with a given category.

For Google Play, this has major implications. Higher category confidence increases the likelihood that an app will be associated with a broader range of relevant search queries within that category. Rather than ranking for a narrow set of exact keywords, apps can gain visibility across an expanded semantic keyword space.

In practice, we have seen that improving category confidence can significantly enhance keyword coverage and ranking stability, particularly during periods of algorithm change.

To increase category confidence:

  • Use clear, natural language that reflects real user intent
  • Focus on describing functionality and value, not just features
  • Avoid keyword stuffing or forced phrasing
  • Reinforce category-relevant concepts consistently throughout metadata
Hinge's Dating App.

Applying GNL Insights to Metadata Strategy

The real value of Google Natural Language lies not in isolated analysis, but in iterative optimization. By repeatedly testing metadata drafts through the Google Natural Language, ASO teams can refine language until category confidence, entity salience, and overall clarity improve.

This approach aligns well with broader 2026 ASO best practices, which emphasize:

  • User intent over keyword lists
  • Semantic relevance over repetition
  • Long-term stability over short-term gains

Case Study Insights

We have applied GNL-driven optimisation techniques across multiple app categories. While results vary by vertical, the overall pattern has been consistent.

During periods of significant Google Play algorithm updates, apps optimized around category confidence and entity relevance showed greater resilience. In several cases, visibility improved despite widespread volatility elsewhere in the store.

In one example, keyword coverage expanded substantially following metadata updates that increased confidence across both a core category and secondary related categories. This translated into a more than fivefold increase in organic Explore installs over time.

A Yodel Mobile case study about keyword coverage.

These results reinforce an important principle. When ASO strategies align with how Google understands language, they are better positioned to benefit from algorithm evolution rather than being disrupted by it.

Connecting GNL to 2026 ASO Strategy

Looking ahead, the role of natural language processing in app discovery will only grow. As Google continues to automate metadata creation and interpretation, manual optimization will shift from mechanical execution to strategic guidance.

ASO teams that understand and leverage tools like Google Natural Language will be better equipped to:

  • Guide AI-generated content rather than react to it
  • Maintain differentiation in an increasingly automated ecosystem
  • Build metadata that supports both paid and organic discovery

This approach also complements broader trends such as AI-powered search, cross-platform discovery, and privacy-first measurement frameworks.

Conclusion

The rise of natural language processing does not signal the end of ASO. Instead, it marks a shift in how optimization should be approached.

By moving beyond keyword density and embracing semantic relevance, ASO teams can align more closely with Google’s evolving algorithms. Google Natural Language offers a practical way to understand how app metadata is interpreted and how it can be improved to support discovery, conversion, and long-term stability.

As automation continues to expand across Google Play, the teams that succeed will be those who understand the systems behind it and adapt their strategies accordingly. Natural language optimization is no longer optional. It is becoming a core pillar of modern ASO.

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Meta adds Manus AI tools into Ads Manager

Inside Meta’s AI-driven advertising system: How Andromeda and GEM work together

Meta Platforms is embedding newly acquired AI agent tech directly into Ads Manager, giving advertisers built-in automation tools for research and reporting as the company looks to show faster returns on its AI investments.

What’s happening. Some advertisers are seeing in-stream prompts to activate Manus AI inside Ads Manager.

  • Manus is now available to all advertisers via the Tools menu.
  • Select users are also getting pop-up alerts encouraging in-workflow adoption.
  • The feature rollout signals deeper integration ahead.

What is Manus. Manus AI is designed to power AI agents that can perform tasks like report building and audience research, effectively acting as an assistant within the ad workflow.

Why we care. Manus AI brings AI-powered automation directly into Meta Platforms Ads Manager, making tasks like report-building, audience research, and campaign analysis faster and more efficient.

Meta is currently prioritizing tying AI investment to measurable ad performance, giving advertisers new ways to optimize campaigns and potentially gain a competitive edge by testing workflow efficiencies early.

Between the lines. Meta is under pressure to demonstrate practical value from its aggressive AI spending. Advertising remains its clearest path to monetization, and embedding Manus into everyday ad tools offers a direct way to tie AI investment to performance gains.

Zoom out. The move aligns with CEO Mark Zuckerberg’s push to weave AI across Meta’s product stack. By positioning Manus as a performance tool for advertisers, Meta is betting that workflow efficiencies will translate into stronger ad results — and a clearer AI revenue story.

The bottom line. For advertisers, Manus adds another layer of built-in automation worth testing. Early adopters may uncover time savings and optimization gains as Meta continues expanding AI inside its ad ecosystem.

Read more at Read More

Why AI optimization is just long-tail SEO done right

The return of long-tail SEO in the AI era

If you look at job postings on Indeed and LinkedIn, you’ll see a wave of acronyms added to the alphabet soup as companies try to hire people to boost visibility on large language models (LLMs).

Some people are calling it generative engine optimization (GEO). Others call it answer engine optimization (AEO). Still others call it artificial intelligence optimization (AIO). I prefer large model answer optimization (LMAO).

I find these new acronyms a bit ridiculous because while many like to think AI optimization is new, it isn’t. It’s just long-tail SEO — done the way it was always meant to be done.

Why LLMs still rely on search

Most LLMs (e.g., GPT-4o, Claude 4.5, Gemini 1.5, Grok-2) are transformers trained to do one thing: predict the next token given all previous tokens.

AI companies train them on massive datasets from public web crawls, such as:

  • Common Crawl.
  • Digitized books.
  • Wikipedia dumps.
  • Academic papers.
  • Code repositories.
  • News archives.
  • Forums.

The data is heavily filtered to remove spam, toxic content, and low-quality pages. Full pretraining is extremely expensive, so companies run major foundation training cycles only every few years and rely on lighter fine-tuning for more frequent updates.

So what happens when an LLM encounters a question it can’t answer with confidence, despite the massive amount of training data?

AI companies use real-time web search and retrieval-augmented generation (RAG) to keep responses fresh and accurate, bridging the limits of static training data. In other words, the LLM runs a web search.

To see this in real time, many LLMs let you click an icon or “Show details” to view the process. For example, when I use Grok to find highly rated domestically made space heaters, it converts my question into a standard search query.

Dig deeper: AI search is booming, but SEO is still not dead

The long-tail SEO playbook is back

Many of us long-time SEO practitioners have praised the value of long-tail SEO for years. But one main reason it never took off for many brands: Google.

As long as Google’s interface was a single text box, users were conditioned to search with one- and two-word queries. Most SEO revenue came from these head terms, so priorities focused on competing for the No. 1 spot for each industry’s top phrase.

Many brands treated long-tail SEO as a distraction. Some cut content production and community management because they couldn’t see the ROI. Most saw more value in protecting a handful of head terms than in creating content to capture the long tail of search.

Fast forward to 2026. People typing LLM prompts do so conversationally, adding far more detail and nuance than they would in a traditional search engine. LLMs take these prompts and turn them into search queries. They won’t stop at a few words. They’ll construct a query that reflects whatever detail their human was looking for in the prompt.

Suddenly, the fat head of the search curve is being replaced with a fat tail. While humans continue to go to search engines for head terms, LLMs are sending these long-tail search queries to search engines for answers.

While AI companies are coy about disclosing exactly who they partner with, most public information points to the following search engines as the ones their LLMs use most often:

  • ChatGPT – Bing Search.
  • Claude – Brave Search.
  • Gemini – Google Search.
  • Grok – X Search and its own internal web search tool.
  • Perplexity – Uses its own hybrid index.

Right now, humans conduct billions of searches each month on traditional search engines. As more people turn to LLMs for answers, we’ll see exponential growth in LLMs sending search queries on their behalf.

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Dig deeper: Why ‘it’s just SEO’ misses the mark in the era of AI SEO

How to do long-tail SEO with help from AI

The principles of long-tail SEO haven’t changed much. It’s best summed up by Baseball Hall of Famer Wee Willie Keeler: “Keep your eye on the ball and hit ’em where they ain’t.”

Success has always depended on understanding your audience’s deepest needs, knowing what truly differentiates your brand, and creating content at the intersection of the two.

As straightforward as this strategy has been, few have executed it well, for understandable reasons.

Reading your customers’ minds is hard. Keyword research is tedious. Content creation is hard. It’s easy to get lost in the weeds.

Happily, there’s someone to help: your favorite LLM.

Here are a few best practices I’ve used to create strong long-tail content over the years, with a twist. What once took days, weeks, or even months, you can now do in minutes with AI.

1. Ask your LLM what people search when looking for your product or service

The first rule of long-tail SEO has always been to get into your audience’s heads and understand their needs. This once required commissioning surveys and hiring research firms to figure out.

But for most brands and industries, an LLM can handle at least the basics. Here’s a sample prompt you can use.

Act as an SEO strategist and customer research analyst. You're helping with long-tail keyword discovery by modeling real customer questions.

I want to discover long-tail search questions real people might ask about my business, products, and industry. I’m not looking for mere keyword lists. Generate realistic search questions that reflect how people research, compare options, solve problems, and make decisions.

Company name: [COMPANY NAME]
Industry: [INDUSTRY]
Primary product/service: [PRIMARY PRODUCT OR SERVICE]
Target customer: [TARGET AUDIENCE]
Geography (if relevant): [LOCATION OR MARKET]

Generate a list of 75 – 100 realistic, natural-language search queries grouped into the following categories:

AWARENESS
• Beginner questions about the category
• Problem-based questions (pain points, frustrations, confusion)

CONSIDERATION
• Comparison questions (alternatives, competitors, approaches)
• “Best for” and use-case questions
• Cost and pricing questions

DECISION
• Implementation or getting-started questions
• Trust, credibility, and risk questions

POST-PURCHASE
• Troubleshooting questions
• Optimization and advanced/expert questions

EDGE CASES
• Niche scenarios
• Uncommon but realistic situations
• Advanced or expert questions

Guidelines:
• Write queries the way real people search in Google or ask AI assistants.
• Prioritize specificity over generic keywords.
• Include question formats, “how to” queries, and scenario-based searches.
• Avoid marketing language.
• Include emotional, situational, and practical context where relevant.
• Don't repeat the same query structure with minor variations.
• Each query should suggest a clear content angle.

Output as a clean bullet list grouped by category.

You can tweak this prompt for your brand and industry. The key is to force the LLM (and yourself) to think like a customer and avoid the trap of generating keyword lists that are just head-term variations dressed up as long-tail queries.

With a prompt like this, you move away from churning out “keyword ideas” and toward understanding real customer needs you can build useful content around.

Dig deeper: If SEO is rocket science, AI SEO is astrophysics

2. Use your LLM to analyze your search data

Most large brands and sites don’t realize they’ve been sitting on a treasure trove of user intelligence: on-site search data.

When customers type a query into your site’s search box, they’re looking for something they expect your brand to provide.

If you see the same searches repeatedly, it usually means one of two things:

  • You have the information, but users can’t find it.
  • You don’t have it at all.

In both cases, it’s a strong signal you need to improve your site’s UX, add meaningful content, or both.

There’s another advantage to mining on-site search data: it reveals the exact words your audience uses, not the terms your team assumes they use.

Historically, the challenge has been the time required to analyze it. I remember projects where I locked myself in a room for days, reviewing hundreds of thousands of queries line by line to find patterns — sorting, filtering, and clustering them by intent.

If you’ve done the same, you know the pattern. The first few dozen keywords represent unique concepts, but eventually you start seeing synonyms and variations.

All of this is buried treasure waiting to be explored. Your LLM can help. Here’s a sample prompt you can use:

You're an SEO strategist analyzing internal site search data.

My goal is to identify content opportunities from what users are searching for on my website – including both major themes and specific long-tail needs within those themes.

I have attached a list of site search queries exported from GA4. Please:

STEP 1 – Cluster by intent
Group the queries into logical intent-based themes.

STEP 2 – Identify long-tail signals inside each theme
Within each theme:
• Identify recurring modifiers (price, location, comparisons, troubleshooting, etc.)
• Identify specific entities mentioned (products, tools, features, audiences, problems)
• Call out rare but high-intent searches
• Highlight wording that suggests confusion or unmet expectations

STEP 3 – Generate content ideas
For each theme:
• Suggest 3 – 5 content ideas
• Include at least one long-tail content idea derived directly from the queries
• Include one “high-intent” content idea
• Include one “problem-solving” content idea

STEP 4 – Identify UX or navigation issues
Point out searches that suggest:
• Users cannot find existing content
• Misleading navigation labels
• Missing landing pages

Output format:
Theme:
Supporting queries:
Long-tail insights:
Content opportunities:
UX observations:

Again, customize this prompt based on what you know about your audience and how they search.

The detail matters. Many SEO practitioners stop at a prompt like “give me a list of topics for my clients,” but this pushes the LLM beyond simple clustering to understand the intent behind the searches.

I used on-site search data because it’s one of the richest, most transparent, and most actionable sources. But similar prompts can uncover hidden value in other keyword lists, such as “striking distance” terms from Google Search Console or competitive keywords from Semrush.

Even better, if your organization keeps detailed customer interaction records (e.g., sales call notes, support tickets, chat transcripts), those can be more valuable. Unlike keyword datasets, they capture problems in full sentences, in the customer’s own words, often revealing objections, confusion, and edge cases that never appear in traditional keyword research.

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3. Create great content

The next step is to create great content.

Your goal is to create content so strong and authoritative that it’s picked up by sources like Common Crawl and survives the intense filtering AI companies apply when building LLM training sets. Realistically, only pioneering brands and recognized authorities can expect to operate in this rarefied space.

For the rest of us, the opportunity is creating high-quality long-tail content that ranks at the top across search engines — not just Google, but Bing, Brave, and even X.

This is one area where I wouldn’t rely on LLMs, at least not to generate content from scratch.

Why?

LLMs are sophisticated pattern matchers. They surface and remix information from across the internet, even obscure material. But they don’t produce genuinely original thought.

At best, LLMs synthesize. At worst, they hallucinate.

Many worry AI will take their jobs. And it will — for anyone who thinks “great content” means paraphrasing existing authority sources and competing with Wikipedia-level sites for broad head terms. Most brands will never be the primary authority on those terms. That’s OK.

The real opportunity is becoming the authority on specific, detailed, often overlooked questions your audience actually has. The long tail is still wide open for brands willing to create thoughtful, experience-driven content that doesn’t already exist everywhere else.

We need to face facts. The fat head is shrinking. The land rush is now for the “fat tail.” Here’s what brands need to do to succeed:

Dominate searches for your brand

Search your brand name in a keyword tool like Semrush and review the long-tail variations people type into Google. You’ll likely find more than misspellings. You’ll see detailed queries about pricing, alternatives, complaints, comparisons, and troubleshooting.

If you don’t create content that addresses these topics directly — the good and the bad — someone else will. It might be a Reddit thread from someone who barely knows your product, a competitor attacking your site, a negative Google Business Profile review, or a complaint on Trustpilot.

When people search your brand, your site should be the best place for honest, complete answers — even and especially when they aren’t flattering. If you don’t own the conversation, others will define it for you.

The time for “frequently asked questions” is over. You need to answer every question about your brand—frequent, infrequent, and everything in between.

Go long

Head terms in your industry have likely been dominated by top brands for years. That doesn’t mean the opportunity is gone.

Beneath those competitive terms is a vast layer of unbranded, long-tail searches that have likely been ignored. Your data will reveal them.

Review on-site search, Google Search Console queries, customer support questions, and forums like Reddit. These are real people asking real questions in their own words.

The challenge isn’t finding questions to write about. It’s delivering the best answers — not one-line responses to check a box, but clear explanations, practical examples, and content grounded in real experience that reflects what sets your brand apart.

Dig deeper: Timeless SEO rules AI can’t override: 11 unshakeable fundamentals

Expertise is now a commodity: Lean into experience, authority, and trust

Publishing expert content still matters, but its role has changed. Today, anyone can generate “expert-sounding” articles with an LLM.

Whether that content ranks in Google is increasingly beside the point, as many users go straight to AI tools for answers.

As the “expertise” in E-E-A-T becomes table stakes, differentiation comes from what AI and competitors can’t easily replicate: experience, authority, and trust.

That means publishing:

  • Original insights and genuine thought leadership from people inside your company.
  • Real customer stories with measurable outcomes.
  • Transparent reviews and testimonials.
  • Evidence that your brand delivers what it promises.

This isn’t just about blog content. These signals should appear across your site — from your About page to product pages to customer support content. Every page should reinforce why a real person should trust your brand.

Stop paywalling your best content

I’m seeing more brands put their strongest content behind logins or paywalls. I understand why. Many need to protect intellectual property and preserve monetization. But as a long-term strategy, this often backfires.

If your content is truly valuable, the ideas will spread anyway. A subscriber may paraphrase it. An AI system may summarize it. A crawler may access it through technical workarounds. In the end, your insights circulate without attribution or brand lift.

When your best content is publicly accessible, it can be cited, linked to, indexed, and discussed. That visibility builds authority and trust over time.

In a search- and AI-driven ecosystem, discoverability often outweighs modest direct content monetization.

This doesn’t mean content businesses can’t charge for anything. It means being strategic about what you charge for. A strong model is to make core knowledge and thought leadership open while monetizing things such as:

  • Tools.
  • Community access.
  • Premium analysis or data.
  • Courses or certifications.
  • Implementation support.
  • Early access or deeper insights.

In other words, let your ideas spread freely and monetize the experience, expertise, and outcomes around them.

Stop viewing content as a necessary evil

I still see brands hiding content behind CSS “read more” links or stuffing blocks of “SEO copy” at the bottom of pages, hoping users won’t notice but search engines will.

Spoiler alert: they see it. They just don’t care.

Content isn’t something you add to check an SEO box or please a robot. Every word on your site must serve your customers. When content genuinely helps users understand, compare, and decide, it becomes an asset that builds trust and drives conversions.

If you’d be embarrassed for users to read your content, you’re thinking about it the wrong way. There’s no such thing as content that’s “bad for users but good for search engines.” There never was.

Embrace user-generated content

No article on long-tail SEO is complete without discussing user-generated content. I covered forums and Q&A sites in a previous article (see: The reign of forums: How AI made conversation king), and they remain one of the most efficient ways to generate authentic, unique content.

The concept is simple. You have an audience that’s already passionate and knowledgeable. They likely have more hands-on experience with your brand and industry than many writers you hire. They may already be talking about your brand offline, in customer communities, or on forums like Reddit.

Your goal is to bring some of those conversations onto your site.

User-generated content naturally produces the long-tail language marketing teams rarely create on their own. Customers

  • Describe problems differently.
  • Ask unexpected questions.
  • Compare products in ways you didn’t anticipate.
  • Surface edge cases, troubleshooting scenarios, and real-world use cases that rarely appear in polished marketing copy.

This is exactly the kind of content long-tail SEO thrives on.

It’s also the kind of content AI systems and search engines increasingly recognize as credible because it reflects real experience rather than brand messaging many dismiss as inauthentic.

Brands that do this well don’t just capture long-tail traffic. They build trust, reduce support costs, and dominate long-tail searches and prompts.

In the age of AI-generated content, real human experience is one of the strongest differentiators.

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The new SEO playbook looks a lot like the old one

For years, SEO has been shaped by the limits of the search box. Short queries and head terms dominated strategy, and long-tail content was often treated as optional.

LLMs are changing that dynamic. AI is expanding search, not eliminating it.

AI systems encourage people to express what they actually want to know. Those detailed prompts still need answers, and those answers come from the web.

That means the SEO opportunity is shifting from competing over a small set of keywords to becoming the best source of answers to thousands of specific questions.

Brands that succeed will:

  • Deeply understand their audience.
  • Publish genuinely useful content.
  • Build trust through real engagement and experience.

That’s always been the recipe for SEO success. But our industry has a habit of inventing complex tactics to avoid doing the simple work well.

Most of us remember doorway pages, exact match domains, PageRank sculpting, LSI obsession, waves of auto-generated pages, and more. Each promised an edge. Few replaced the value of helping users.

We’re likely to see the same cycle repeat in the AI era.

The reality is simpler. AI systems aren’t the audience. They’re intermediaries helping humans find trustworthy answers.

If you focus on helping people understand, decide, and solve problems, you’re already optimizing for AI — whatever you call it.

Dig deeper: Is SEO a brand channel or a performance channel? Now it’s both

Read more at Read More

Google Search Console AI-powered configuration rolling out

Over two months ago, Google began testing its AI-powered configuration tool. It allows you to ask AI questions about the Google Search Console performance reports and it would bring back answers for you. Well, Google is now rolling out this tool for all.

Google said on LinkedIn, “The Search Console’s new AI-powered configuration is now available to everyone!”

AI-powered configuration. AI-powered configuration “lets you describe the analysis you want to see in natural language. Your inputs are then transformed into the appropriate filters and settings, instantly configuring the report for you,” Google said.

Rolling out now. If you login to your Search Console account and click on the performance report, you may see a note at the top that says “New! Customize your Performance report using Al.”

When you click on it, you get into the AI tool:

More details. As we reported earlier, Google said “The AI-powered configuration feature is designed to streamline your analysis by handling three key elements for you.”

  • Selecting metrics: Choose which of the four available metrics – Clicks, Impressions, Average CTR, and Average Position – to display based on your question.
  • Applying filters: Narrow down data by query, page, country, device, search appearance, or date range.
  • Configuring comparisons: Set up complex comparisons (like custom date ranges) without manual setup.

Why we care. This is only supported in the Performance report for Search results. It isn’t available for Discover or News reports, yet. Plus, it is AI, so the answers may not be perfect. But it can be fun to play with and get you thinking about things you may not have thought about yet.

So give it a try.

Read more at Read More