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How to Run a Competitor Traffic Analysis (9 Steps)

August 5, 2025/0 Comments/in Web Design News/by

You know that feeling when you see a brand new competitor swooping in and snatching leads away from you?

It can make you start questioning your whole approach.

But instead of panicking, it’s far more useful to break down what they’re doing.

That way, you can cherry-pick their best ideas. And spot the gaps they’ve missed.

This post will show you exactly how to do that.

As you read it, imagine you’re a new pet supplies brand going head-to-head with the retailer Hollywood Feed.

To get the upper hand, you’ll need to understand how they’re driving traffic and converting customers, answering questions like:

Which channels bring the most visits and sales?
How much of their traffic is organic vs. paid?
Which pages, platforms, and campaigns are working best?

In this guide, you’ll learn how to run a competitor analysis to find the answers to these questions and more — regardless of your brand, industry, and experience.

Free resource: You can follow along with our Competitive Analysis Worksheet. Just open it up in another tab, and use this article as a guide to fill it out for your top 3-5 competitors.

Competitive Traffic Analysis Worksheet – Backlinko

Before you start, this guide assumes you’ve already covered the basics.

You know your ideal customer. You’ve nailed your positioning. You’re clear on the category or niche you’re competing in.

If not, start here: The Complete Guide to Market Research

It’ll make everything in this guide way more useful.

Let’s start by identifying your real competition.

Step 1: Spot the Competitors Grabbing Your Traffic

You need to build a live list of 5–10 competitors.

Begin Googling broad, high-intent terms like:

“best dog food”
“pet store near me” (or “pet store in [city]”)
“cat toys online”

Not sure where to start? Try this AI prompt to gather some terms you can then type into Google:

“What high-intent keywords do people use when searching for [your product/service] online?”

Make a note of:

Who ranks organically
Who’s running paid ads
Who’s in the local pack (map section that shows nearby businesses) or shopping results

Next, check out popular Reddit threads and pet owner forums. This is where you’ll often find smaller, more niche brand mentions. But they might still be your competitors depending on your location and/or stage of growth.

(As a bonus it’ll also often reveal the sentiment around your rivals from real customers.)

Now go to Google and look for “best of” listicles from publishers and bloggers.

The Spruce Pets – Best Places to Buy Dog Food

Find these by searching for modifiers like “best” and “cheapest” followed by:

[product] in [industry]
[product] in [city]
[product] for [specific need]
[product] under $[amount]
[product] in [year]
[industry] brands

Google SERP – Best dog food for sensitive stomach

Tip: Also check which competitors rank for these terms directly. These are generally high volume, competitive, and valuable. If your rivals rank for them, you likely want to as well.

Want a more straightforward way to find your rivals?

You can use an SEO platform like Semrush to instantly find your main competitors.

Just pop your domain into the Organic Research tool. Head to the “Competitors” tab and you’ll see the Competitive Positioning Map.

This shows your top rivals on a chart of the number of keywords they rank for vs. their organic search traffic.

Organic Research – Petfoodexpress – Competitors Map

You’ll also see more information below that about each competitor. Like common keywords, paid keywords, and more.

Note: A free Semrush account gives you 10 searches in the Organic Research tool per day. Or you can use this link to access a 14-day trial on a Semrush Pro subscription.

Finally, AI tools like ChatGPT can help uncover competitors that traffic tools might miss. Here are a few prompts you can try:

Use Case	Example Prompt	What It Reveals
General Discovery	What are the best places to buy [your product] in [your market]? E.g. What are the best places to buy pet supplies online in the U.S.?	Returns top names, but might sometimes surface lesser-known brands too
Niche-Specific	Top-rated [your business] for [your niche] in [your market] E.g., Top-rated pet stores for natural dog food in the U.S.	Highlights specialty brands focused on natural or premium products
Emerging and Hidden Players	Fastest-growing [your vertical] business in [your market] E.g., Fastest-growing pet retailers in the US	Surfaces rising brands that may not rank in traffic tools yet

Note that AI tools may personalize answers based on your chat history. Run prompts in a fresh window, and always verify unfamiliar results.

Pro tip: It’s easy to watch the big names and miss smaller players like Hollywood Feed who are gaining ground.

Don’t just check Google.

Search Reddit, niche listicles, and online communities to spot emerging competitors.

Reminder: Add these competitors to your copy of our competitor analysis worksheet.

Step 2: Find Your Edge by Comparing Products and Positioning

Once you’ve got your competitor list, go through them one by one, and start by looking at the basics:

What products do your competitors sell?
How do those products compare to yours?

Then, look at how they talk about themselves.

What value propositions are they leaning on: quality, price, convenience, or something else?

Head to their website to find this out.

Have a click around, paying particular attention to the product and category pages. Use what you find to fill out the “Product and Positioning” sections of our template:

You can use AI to gather a lot of this info even faster (although I still recommend actually visiting their website too).

Here’s an example of a prompt you could use:

I’m analyzing competitors to understand how to position my brand more effectively.

Here’s what I’d like help with:

My brand: [insert brief description — product, audience, values]

Competitors: [insert 3–5 competitor names]

For each competitor, please:

List their main products

Compare their offerings to mine in terms of variety, pricing, target customer, and positioning

Identify their core value propositions (price, convenience, quality, speed, etc.)

Describe their messaging tone and website language

Then suggest 2–3 ways I can differentiate — based on gaps or overlaps in their positioning. Format your answer using tables and bullet points

Here’s an example using Hollywood Feed and Chewy:

Section	Brand	Details
Product Comparison	Chewy	Wide selection: pet food (all types), toys, meds, grooming. Convenience-focused.
	Hollywood Feed	Natural/premium food, boutique accessories, regional in-store experience.
Value Propositions	Chewy	Convenience, speed, selection, 24/7 service.
	Hollywood Feed	High quality, local expertise, boutique service.
Messaging & Tone	Chewy	Warm, mass-market tone. “Trusted by millions.” Friendly and supportive.
	Hollywood Feed	Expert-led, local authority. “Nutrition-trained associates.” Boutique feel.
Differentiation Opportunities	1. Sustainable + subscription niche	Neither competitor clearly owns this space — potential to stand out.
	2. Ingredient transparency	Competitors mention quality, but don’t emphasize traceability or sourcing.
	3. Radical simplicity	Chewy offers everything; Hollywood Feed is regional. There’s room for a frictionless, curated experience.

Note: We’ve included a section at the end of the downloadable worksheet to go a step further and analyze your rivals’ customer experience and checkout flows.

Competitive Traffic Analysis Worksheet – Backlinko – Customer Experience Audit

There are too many checks to cover in detail here. But they’re still super important as they can help you understand where your rivals are winning at the end of the buyer journey.

Step 3: Analyze Their Traffic Channels

Looking at your competitor’s website traffic can tell you where they’re investing. And how fast they’re growing.

Here’s how.

Start with the Top-Level Traffic Numbers

Start by checking competitor website traffic in general. You can do this with a tool like Semrush’s Domain Overview (although there are other options out there — including our own free website traffic checker).

Domain Overview – Hollywood Feed – Search

Here’s what to check:

Total Traffic

Look for their estimated monthly visits.

A higher number doesn’t always mean more sales.

But it does show the scale of their online presence.

Domain Overview – Hollywood Feed – Overview

For example, Hollywood Feed has around 193K organic visits per month. That’s a significant number to contend with if I’m a new player, and I shouldn’t expect to reach that number overnight.

Paid vs. Organic

Comparing paid traffic to organic traffic reveals how your rivals are acquiring customers.

A brand with mostly organic traffic is typically investing in SEO and content.

A brand leaning on paid search or social is buying quick traffic. But they may be vulnerable to rising costs.

Hollywood Feed brings in only 8.4K from paid search. It looks like they’re betting on SEO over ads.

If your pet store has the budget to invest in paid search, you could reach customers they’re missing.

Further reading: Learn more about using paid ads effectively in our guide on advertising your business.

Traffic Share

Use traffic share metrics to compare competitor website traffic and understand where you fit in the picture.

For example, Hollywood Feed holds a 9% traffic share compared to its main competitors.

They’re a meaningful player in the market, but not the dominant one.

Branded vs. Non-Branded

Are people searching for their brand name or just looking for what they sell?

Hollywood Feed gets 68.1% of its traffic from branded keywords.

That shows strong name recognition but also reveals an opportunity.

Aim to rank for the non-branded, high-intent searches they’re missing.

Analyze Their Traffic Split

Moving away from just traffic, you can learn a lot about your competitor’s SEO and content marketing strategy from the outside.

You can do this with Semrush’s Organic Research tool.

Organic Research – Hollywoodfeed – Overview

Scroll down to see their top pages.

Are they blog posts, category pages, product pages, or store locators?

This helps you spot where they’re strongest, and where there might be opportunities.

Organic Research – Hollywoodfeed – Top Pages

For example, 61% of Hollywood Feed’s traffic goes to their home page.

This suggests strong brand recognition but potentially limited organic discovery.

Their location pages also drive some traffic, suggesting investment in local SEO.

Blog content contributes less than 3% of visits.

So there’s a chance to compete on content.

Next, look at their Keywords by Intent:

Informational keywords represent people looking for advice
Navigational keywords come from people searching for a specific site
Commercial keywords are searched by those comparing products
Transactional keywords are used by shoppers ready to buy

Note: Traffic numbers can look impressive, but context matters. A competitor with 200K visits might not be a real threat if most traffic is just browsing educational content. Focus on traffic quality and intent, not just volume.

Here’s the breakdown for Hollywood Feed:

Organic Research – Hollywoodfeed – Keywords by Intent

Their keywords primarily cover informational, commercial, and transactional intent. And it’s a pretty even split.

This means they reach searchers at every stage of the buying journey.

No obvious gaps here.

But as they’re evenly spread, you could consider going deeper on one keyword set to compete.

For instance, better product comparisons could help you compete for commercial keywords.

Further reading: For more tips on finding these opportunities, check out our full guide to uncovering competitor keywords.

Step 4: Look at Their Paid Media Performance

Next, check how your competitors are using paid media to drive traffic and sales.

Start with Google Ads.

Search for their brand name to find branded search ads.

Also, look for relevant non-branded keywords. Like “natural dog food” or “best dog treats.”

Google SERP – Best dog food delivery – Google Ads

Look for Google Search ads and Google Shopping ads (product images with prices).

Pro tip: Use Google’s Ads Transparency Center to browse a brand’s live and past ads.

Next, visit the Meta Ad Library and type in their brand name.

This will show you any active ads they’re running on Facebook or Instagram.

Meta Ad Library – Hollywood Feed – Results

You can do the same on TikTok’s Ad Library.

As you review their ads, pay attention to:

What products they’re promoting (specific brands, seasonal items, top-sellers)
What offers they’re using (discounts, bundles, subscriptions, free shipping)
Which platforms they’re investing in (Google, Facebook, Instagram, TikTok)

This gives you a snapshot of their paid strategy on social media.

Hollywood Feed’s Meta ads are a mix of product promotions and local messages.

You could stand out by using stronger calls to action.

You might also try content-driven ads or user-generated videos to boost engagement.

Further reading: You can also use this free Competitor Search Ads tool to spy on your competitors’ ads.

Step 5: Deep Dive Into Their Content and Messaging

Take a closer look at how your competitors are talking to their audience.

Start with their homepage copy.

Is it clear who they’re targeting and what makes them different?

Hollywood Feed does a good job of highlighting benefits upfront.

Same-day delivery. Curated product picks. “Why we’re a different breed” messaging.

It’s all there — baked right into the homepage.

Steal that move.

Make sure your top benefits are front and center.

What makes you different? Why should someone buy from you instead of the competition?

If that’s not obvious in the first few scrolls, fix it.

Also analyze their:

Product descriptions: Are they just listing features, or are they showing how their products solve problems? Do they use benefit-driven language?
Blog/educational content: Is their content deep, or is it thin and only covering the basics? Could you create more engaging, valuable blog posts for your audience to outrank and outcompete them?
Tone, style, and trust signals: Do they prominently feature social proof? Do they show off guarantees or certifications/awards?

Finally, look into their content structure.

Topic clusters are groups of related articles linked to a central pillar page. This can help build authority around key topics.

The Hollywood Feed University blog covers topics like pet care and nutrition.

But they haven’t built out strong topical clusters to organize this content.

When you click on a category, you get a list of articles, not a central pillar page.

That’s a missed SEO opportunity — and a chance for you to win.

Create clear pillar pages that link out to related content.

It helps Google understand your site and builds topical authority.

Compare the insights you gather with your own content to identify areas you can improve — and gaps you can fill.

Step 6: Explore Their Social Media Presence

Next, see which social media platforms your competitor uses.

Tip: B2C brands often use Facebook, Instagram, and TikTok. B2B brands usually focus on LinkedIn, X/Twitter, and YouTube.

Scroll through their recent posts and take note of the content formats they use.

Are they sharing educational posts, demos, customer stories, or thought leadership?

Look at follower engagement too.

Are people commenting, sharing, or ignoring the content?

Strong engagement signals an active community and loyal audience.

Finally, assess their brand personality and values.

Are they playful, bold, helpful, or professional?

For our pet food example, we find that Hollywood Feed is on Instagram. And they have a large following (around 35K followers).

Their social content leans into friendly, community-focused messaging, with discounts for followers.

You could stand out by adding more educational content.

You might also try more engaging formats, like videos or user-generated posts.

Step 7: Check Their LLM Visibility

Research from Semrush suggests that LLM traffic will overtake Google search by 2027.

That means getting visibility in AI answers is about to matter as much as (or more than) traditional rankings.

Google and LLM Unique Visitor Growth Projection (Moderate Case)

Here’s how to analyze your competitors’ LLM visibility to make sure you’re not falling behind:

First, open a fresh incognito window or use a VPN to avoid personalized results.

Then, in Google Search, look for an AI Overview by searching for broad, high-intent keywords. (Or take a look at the results in AI Mode.)

Think “best dog food delivery” or “top pet stores near me.”

Try the same searches in tools like Perplexity.ai and ChatGPT.

Look for mentions of your competitor’s brand name and links to their site in AI responses.

Also note the sentiment:

Are they being mentioned as a top brand?
What specific features are the AI tools calling out?
Are the AI responses pulling from reviews, or are they also citing round-up posts and forum discussions?

LLM visibility and optimization is a massive topic in its own right. This post would get too long if we tried to cover all the ways you can analyze your competitors’ performance in these tools.

So for a more detailed guide, check out our dedicated article on LLM visibility.

Step 8: Review Their Local SEO (If Applicable)

If your competitor has a physical presence, search for their brand name + city (e.g., “Hollywood Feed Austin TX”) in Google Search and Google Maps.

Look for their Google Business Profile.

Is it optimized with photos, opening hours, and reviews?

Do they rank for proximity-based keywords like “pet store near [city]” or “dog food delivery [city]”?

Hollywood Feed appears to be investing in local landing pages.

They have active Google Business Profiles for each store:

Hollywood Feed – Google Business Profiles

If you wanted to compete on a local search level, you’d better make sure you’ve done the same.

Further reading: Read our Google Business Profile guide to find out how to compete at the local level.

Step 9: Turn Competitive Insights Into Action

Now it’s time to bring all your research together so you can act on it.

If you’ve been following along with our competitor analysis worksheet, you’ll have a lot of info already.

I recommend filling it out for your top 3-5 competitors. Then, download our competitor analysis summary template.

Competitor Analysis Summary Template by Backlinko

Here’s where you’ll turn data into actionable strategies that you’ll use to beat your rivals.

It helps you dig deeper into what each competitor is doing well, where they’re falling short, and how you can differentiate.

Competitor Analysis Summary Template by Backlinko – Strenghts

Pro tip: Competitor insights are valuable. But they should never replace your own market research.

Use their playbook as a reference, not a roadmap.

And don’t try to beat them at everything. Find one or two clear openings and double down.

Don’t Just Copy Your Competitors — Outsmart Them

Competitor analysis isn’t about copying. It’s about learning.

Use this process to sharpen your edge, not mirror theirs.

Begin by picking one competitor and analyzing their online presence using the steps in this guide.

To help you get started, download the free Competitive Traffic Analysis Tracker.

The post How to Run a Competitor Traffic Analysis (9 Steps) appeared first on Backlinko.

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Google Ads lets you test images, videos in Demand Gen campaigns

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Dealing with Google Ads frustrations: Poor support, suspensions and rising costs

Google is testing a new feature that allows advertisers to run A/B tests on images and videos within Demand Gen campaigns, marking a major step toward creative performance transparency.

How it works:

Create an A/B test with two experiment arms.
Google duplicates the campaign for comparison.
Add or remove images and/or videos in either arm.
Set traffic split (commonly 50/50) and total budget.
Define your experiment dates.
Optional: Review campaign opt-ins like video enhancements.

Note: Changes made to the control arm sync to the treatment arm – but not the other way around. Avoid editing the treatment campaign after setup.

Why we care. Until now, you’ve had limited tools to test how visuals perform in Demand Gen campaigns. This new A/B testing functionality gives you a structured way to compare creatives head-to-head and make data-backed decisions. You can now test different visuals across duplicated campaign arms and clearly measure which creatives drive better engagement and conversions.

Between the lines: This gives advertisers a clearer lens into which visual elements perform best – at a time when creative is increasingly driving performance in Google’s AI-heavy ecosystem.

Bottom line: With A/B testing for images and videos now available in Demand Gen campaigns, creative testing just got real. Leveraging it early will unlock stronger insights and more optimized results.

First seen. The update was first highlighted by Thomas Eccel, head of Google Ads at JvM IMPACT, on LinkedIn.

Read more at Read More

AI search fight: Cloudflare and Perplexity clash over crawling

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Cloudflare accused AI answer engine Perplexity of “stealth crawling,” saying it uses deceptive techniques to bypass website blocks and access content it’s been explicitly told not to touch.

In response, Perplexity said Cloudflare has a fundamental misunderstanding of how AI assistants work and accused the company of either publicity-seeking or technical incompetence.

The big picture. Cloudflare said Perplexity uses declared bots when it can, but switches to “stealth crawling” when blocked. That includes mimicking normal browser behavior, rotating IPs, and ignoring robots.txt rules (tactics that can be associated with scrapers and bad actors).

Cloudflare tested this by setting up honeytrap sites and found Perplexity answering questions using content it shouldn’t have been able to access.
Perplexity insisted its requests are made on behalf of users, not as preemptive crawling. The company says these are real-time fetches, akin to what a browser or email client does, and claims Cloudflare mistook its behavior for something it wasn’t.

Why we care. If AI assistants can sidestep robots.txt by posing as browsers, brands, creators, and publishers lose control over how and when their content is used. That breaks the old deal between search engines and websites.

What’s next. Cloudflare said it’s already blocking the behavior in question and expects Perplexity’s tactics to change in response. It’s calling for standardization of bot behavior through IETF (the Internet Engineering Task Force) and other policy efforts.

Perplexity, meanwhile, is doubling down on its identity as an agentic AI platform and says it shouldn’t be governed by rules designed for traditional web crawlers.

The blog posts. You can view the full back and forth here:

Cloudflare: Perplexity is using stealth, undeclared crawlers to evade website no-crawl directives
Perplexity: Agents or Bots? Making Sense of AI on the Open Web

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From search to answer engines: How to optimize for the next era of discovery

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

The shift from traditional search engines to AI-powered answer engines signals more than a technical upgrade.

It marks a fundamental change in how people discover, evaluate, and act on information.

Search is no longer a discrete game of isolated queries and static rankings.

It’s becoming an infinite game – one shaped by context, memory, and ongoing interaction.

For many users, large language models (LLMs) now offer a more effective starting point than classic search engines, especially when the task calls for clarity, research, or a more conversational experience.

How search evolved: From static queries to continuous conversations

Traditional search: A one-off query model

Traditional search engines (like classic Google Search) operate on a deterministic ranking model.

Content is parsed, analyzed, and displayed in SERPs largely as provided.

Ranking depends on known factors:

Content quality.
Site architecture.
Links.
User signals.

A user types a query, receives a list of results (“10 blue links”), clicks, and typically ends the interaction.

Each query is treated independently, with no memory between sessions.

This model supports advertising revenue by creating monetization opportunities for every new query.

AI-powered search: Built for continuity and context

AI-powered answer engines use a probabilistic ranking model.

They synthesize and display information by incorporating:

Reasoning steps.
Memory of prior interactions.
Dynamic data.

The same query can yield different results at different times.

These systems are built for ongoing, multiturn conversations, anticipating follow-up questions and refining answers in real time.

They operate continuously, even while you sleep, and focus on delivering direct, synthesized answers rather than just pointing to links.

How output and experience differ between search and answer engines

The differences between traditional search and AI-powered answer engines aren’t just technical. They show up in what users see and how they interact.

From output format to underlying signals, the user experience has fundamentally changed.

From link lists to zero-click answers

Traditional search engines: Return a ranked list of links generated by complex algorithms.
Answer engines: Deliver full answers, summaries, direct responses, or even product recommendations by blending large-scale training data with real-time web results. They reduce the need for users to click through multiple sites, leading to more zero-click experiences.

From keywords to context

Traditional search: Relies on keyword matching, backlinks, and on-page optimization.
AI search/generative engines: Rely on semantic clarity, contextual understanding, and relationships between entities enhanced by attention mechanisms and references in credible sources. Even content that doesn’t rank highly in traditional search may appear prominently in AI summaries if it is well-structured, topical, and cited across trusted platforms.

Key characteristics of answer engines

Conversational search

LLMs like ChatGPT, Google Gemini, and Perplexity enable conversational interactions, often serving as a more intuitive starting point for users seeking clarity, context, or nuanced understanding.

Queries tend to be longer and phrased as full questions or instructions.

Personalization and memory

Unlike traditional search, AI-powered search incorporates user context, such as:

Past queries.
Preferences.
Location.
Even data from connected ecosystems (e.g., Gmail within Google’s AI Mode).

This context allows the engine to deliver tailored, dynamic, and unique answers.

Dig deeper: How to boost your marketing revenue with personalization, connectivity and data

Query fan-out

Instead of processing a single query, answer engines deconstruct a user’s question into dozens or even hundreds of related, implicit, comparative, and personalized sub-queries.

These synthetic queries explore a broader content pool.

From one query, systems like AI Mode or AI Overviews:

Generate a constellation of search intents.
Retrieve responsive documents.
Build a custom corpus of relevant content.

Reasoning chains

AI models move beyond keyword matching, performing multi-step logical reasoning. They:

Interpret intent.
Formulate intermediate steps.
Synthesize coherent answers from multiple sources.

Multimodality

Answer engines can process information in various formats, including text, images, videos, audio, and structured data. They can:

Transcribe videos.
Extract claims from podcasts.
Interpret diagrams.
Integrate these inputs into synthesized outputs.

Dig deeper: Visual content and SEO: How to use images and videos in 2025

Chunk-level retrieval

Instead of retrieving or ranking entire pages, AI engines work at the passage level.

They extract and rank smaller, highly relevant chunks of content to build precise, context-rich answers.

Advanced processing features

User embeddings and personalization

Systems like Google’s AI Mode use vector-based profiles that represent each user’s history, preferences, and behavior.
This influences how queries are interpreted and how content is selected, synthesized and surfaced as a result – different users may receive different answers to the same query.

Deep reasoning

LLMs evaluate relationships between concepts, apply context, and weigh alternatives to generate responses.
Content is judged on how well it supports inference and problem-solving, not just keyword presence.

Pairwise ranking prompting

Candidate passages are compared directly against each other by the model to determine which is most relevant, precise, and complete.
This approach departs from traditional scoring models by favoring the best small sections rather than entire documents

A step-by-step guide to answer-engine-optimized content

Content best practices remain the same – it should be people-centric, helpful, entity-rich with healthy topical coverage based on audience intent.

However, the content creation process needs to incorporate answer-engine optimization best practices in the details.

Here’s our recommended seven-step process for content creation.

1. Content audit

When auditing existing content:

Check current visibility signals, including impressions, rich results, and whether the page is cited in AI platforms like Google AI Overviews, ChatGPT, or Perplexity.
Identify signs of content decay to establish a baseline for measuring improvement.
Spot and document issues such as:
- Topical gaps or missing subtopics.
- Unanswered user questions.
- Thin or shallow content sections.
- Outdated facts, broken references, or weak formatting.
- Grammatical errors, duplicate content, or poor page structure.

2. Content strategy

It is not all about creating new content.

Your content strategy should incorporate aligning existing content to the needs of answer engines.

Retain: High-converting content with high visibility and high traffic.
Enhance: Pages with high impressions but low click-through rate, pages with low visibility, impressions, and rich results.
Create: Content around topical gaps found in the audit.

3. Content refresh

Update existing content to close topical gaps to make information easily retrievable

4. Content chunking

This involves breaking long blocks into:

Scannable sections (H2/H3).
Bullet lists.
Tables,
A short TL;DR/FAQs.

Keep each chunk self-contained so LLMs can quote it without losing context, and cover just one idea per chunk.

Dig deeper: Chunk, cite, clarify, build: A content framework for AI search

5. Content enrichment

Fill in topical gaps by:

Expanding on related topics.
Adding fresh data.
Drawing on first-hand examples.
Referencing expert quotes.

Cover topics AI can’t easily synthesize on its own.

Cite and link to primary sources within the text (where relevant and meaningful) to boost credibility.

6. Layer on machine-readable signals

Insert or update schema markup (FAQPage, HowTo, Product, Article, etc.).

Use clear alt text and file names to describe images.

7. Publish → monitor → iterate

After publishing, track organic visibility, AI citation frequency, and user engagement and conversion.

Schedule content check-ins every 6–12 months (or after major core/AI updates) to keep facts, links, and schema current.

Make your content LLM-ready: A practical checklist

Below is a checklist you could incorporate in your process to ensure your content aligns with what LLMs and answer engines are looking for.

Map topics to query fan-out

Build topic clusters with pillar and cluster pages.
Cover related questions, intents, and sub-queries.
Ensure each section answers a specific question.

Optimize for assage-level retrieval

Use clear H2/H3 headings phrased as questions.
Break content into short paragraphs and bullet points.
Include tables, lists, and visuals with context.

Build depth and breadth

Cover topics comprehensively (definitions, FAQs, comparisons, use cases).
Anticipate follow-up questions and adjacent intents.

Personalize for diverse audiences

Write for multiple personas (beginner to expert).
Localize with region-specific details and schema.
Include multimodal elements (images w/ alt text, video transcripts, data tables).

Strengthen semantic and entity signals

Add schema markup (FAQPage, HowTo, Product).
Build external mentions and links from reputable sources.
Use clear relationships between concepts.

Show E-E-A-T and originality

Include author bios, credentials, and expertise.
Add proprietary data, case studies, and unique insights.

Ensure technical accessibility

Clean HTML, fast load times, AI-friendly crawling (robots.txt).
Maintain sitemap hygiene and internal linking.

Align with AI KPIs

Track citations, brand mentions, and AIV (attributed influence value).
Monitor engagement signals (scroll depth, time on page).
Refresh content regularly for accuracy and relevance.

Get the newsletter search marketers rely on.

See terms.

How SEO is evolving into GEO

As the mechanics of search evolve, so must our strategies.

GEO (generative engine optimization) builds on SEO’s foundations but adapts them for an environment where visibility depends on citations, context, and reasoning – not just rankings.

Many “new” AI search optimization tactics, such as focusing on conversational long-tail searches, multimodal content, digital PR, and clear content optimization, are essentially updated versions of long-standing SEO practices.

New metrics and goals

Traditional SEO metrics like rankings and traffic are becoming less relevant.

The focus shifts to being cited or mentioned in AI-generated answers, which becomes a key visibility event and a brand lift moment, rather than just driving traffic.

New KPIs at the top of the funnel include:

Search visibility.
Rich results.
Impressions.
LLM visibility.

With declining traffic, engagement, and conversion metrics become critical at the bottom of the funnel.

Relevance engineering

This emerging discipline involves:

Strategically engineering content at the passage level for semantic similarity.
Anticipating synthetic queries.
Optimizing for “embedding alignment” and “informational utility” to ensure the AI’s reasoning systems select your content.

Your website acts as a data hub.

This also means centralizing all types of data for consistency and vectorizing data for easy consumption, and distributing it across all channels is a critical step.

Importance of structured data

Implementing schema markup and structured data is crucial for GEO.

It helps AI engines understand content context, entities, and relationships, making it more likely for content to be accurately extracted and cited in AI responses (53% more likely).

Dig deeper: How to deploy advanced schema at scale

Brand authority and trust

AI models prioritize information from credible, authoritative, and trustworthy sources.

Building a strong brand presence across diverse platforms and earning reputable mentions (digital PR) is vital for AI search visibility, as LLMs may draw from forums, social media, and Q&A sites.

Connecting the dots: UX and omnichannel in the age of AI search

The typical user journey is no longer linear. The options for discovery have diversified with AI acting as a disruptor.

Most platforms are answering questions, are multimodal, delivering agentic and personalized experiences.

Your audience expects similar experiences on the sites they visit. As the user journey evolves, our approach to marketing needs to change, too.

In a linear journey, having channel-based strategies worked.

Consistency of messaging, content, visuals and experiences at every touchpoint are today key to success.

That means you need an audience strategy before mapping channels to the strategy.

Dig deeper: Integrating SEO into omnichannel marketing for seamless engagement

To make it happen effectively, you need to orchestrate the entire content experience – and that starts with your platform as the foundation.

Your website today needs to act as the data hub feeding multimodal information across channels.

How to make your content discoverable by LLMs

To show up in LLM-driven search experiences, your content needs more than depth. It needs structure, speed, and clarity.

Here’s how to make your site visible and machine-readable.

Foundational SEO

The fundamentals of SEO still apply.

LLMs have to crawl and index your content, so technical SEO elements like crawlability and indexability matter.

LLMs do not have the crawl budgets or computing power that Google and Bing have.

That makes speed and page experience critical to maximize crawling and indexing by LLMs

Digital assets

With search going multimodal, your digital assets – images and videos – matter more than they ever did.

Optimize your digital assets for visual search and make sure your page structure and elements include FAQs, comparisons, definitions, and use cases.

Structural integrity

Your site and content need to be both human and machine-readable.

Having high-quality, unique content that addresses the audience’s needs is no longer enough.

You need to mark it up with an advanced nested schema to make it machine-readable.

Deep topical coverage

Ensure your content aligns with the best practices of Google’s E-E-A-T.

People-first content that:

Is unique.
Demonstrates expertise.
Is authoritative.
Covers the topics that your audience cares about.

Make your content easy to find – and easy to use

While the building blocks of SEO are still relevant, aligning with LLM search calls for refining the finer points of your marketing strategy to put your audience before the channels.

Start with the basics and ensure your platform is set up to let you centralize, optimize and distribute content.

Adopt IndexNow to push your content to LLMs instead of waiting for them – with their limited computing and crawling capabilities – to crawl and find your content.

Thank you, Tushar Prabhu, for helping me pull this together.

Read more at Read More

Google Business Profiles Posts creation tool refreshed

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Google has updated the Google Posts creation tool within Google Business Profiles. The update makes it easier to use, by placing all the posts in a centralized location with an easier way to manage those posts.

This update should be live for all of you by now, as it quietly launched last Friday.

What changed. Google made several changes to the Google Posts screen, the changes were summarized by Lisa Landsman from the Google team. She wrote on LinkedIn the list of changes, which includes:

Centralized Posts Hub: The “Add Update” button has been replaced with a new management screen where you can easily see and manage all your posts in one place.
Simpler Creation Process: The post creation experience is now streamlined into a single dialog, allowing you to quickly create updates, events, or offers from one screen.
Enhanced Management View: You can now view key details for each post, such as creation date, status, and post type, making it easier to track and make changes.
Minor Visual Improvements: Google introduced small visual changes throughout the experience to make it more intuitive and enjoyable to use.

What it looks like. Here is a GIF of the new refreshed interface for Google Posts:

What are Google Posts. Google Posts allows businesses to post updates on your Business Profile to share announcements, offers, updates, and event details directly with your customers on Search and Maps. These posts show up within Google Maps and Google Search for searches on your business and within your Google local panel.

You can learn more about Google Posts in this help document.

Why we care. If you are a business with a local footprint or do marketing for a local business, Google Posts can help you get more attention and conversions for that business. By pushing updates, promotions, offers, events and so forth in your local listing on Google, it can attract new and repeat business for the organization.

This new interface may make things easier for you and your business to manage.

Read more at Read More

AI traffic is up 527%. SEO is being rewritten.

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

For the past year, we’ve talked about how AI might change search.

That moment is over.

This is no longer a “what if” conversation. We are seeing a measurable shift in web traffic movement.

At Previsible, we analyzed LLM-driven traffic across 19 GA4 properties and found something undeniable: AI platforms like ChatGPT, Perplexity, Claude, Gemini, and Copilot are already influencing how users find and engage with websites.

Not in theory. In actual traffic.

In just five months, total AI-referred sessions jumped from 17,076 to 107,100.
- That’s a 527% increase between January and May 2025.
Some SaaS sites are now seeing over 1% of all sessions coming from LLMs.
Traffic from ChatGPT, Claude, and others is doubling and tripling across verticals like Legal, Health, and Finance.

If you work in SEO, content, or growth strategy, this moment will feel familiar. Like when mobile-first flipped ranking factors overnight. Or when social transformed from brand garnish into a legitimate acquisition engine.

Every time the rules changed, early adopters won. This time is no different, except it’s moving faster.

So the question isn’t if AI is changing your traffic mix. It’s how much it already has, without you realizing it.

TL;DR: What you need to know about AI search

AI discovery is up 527%: Comparing the first 5 months of 2025 with the same time frame in 2024 we see how total sessions from LLMs (like ChatGPT, Perplexity, and, Gemini) surged from 17,076 to 107,100 across 19 GA4 properties.
LLMs are already part of the user journey: Some sites, especially in SaaS, are seeing over 1% of all traffic initiated by AI results. Primarily to the bottom of funnel users and targeted prospects.
High-consultive industries are leading: Legal, Finance, SMB, Insurance, and Health make up 55% of all LLM-driven sessions, showing that users turn to AI for complex, contextual questions.
ChatGPT leads, but the field is widening: ChatGPT still dominates, but Perplexity, Copilot, and Gemini are gaining real traction.
SEO is splitting and speeding up: It’s no longer just about ranking in Google. You now need to earn visibility in AI assistants, summaries, and conversational UIs, and they prefer content that’s structured, clear, and genuinely helpful.

AI discovery is up 527% – and it isn’t waiting for you to rank

AI is reshaping web traffic at warp speed.

When we compared January-May 2025 to the same period in 2024, we saw total AI-sourced sessions across 19 GA4 properties jump from 17,076 to 107,100.

That’s a 527% year-over-year increase.

In one standout example, ChatGPT went from just 600 visits/month in early 2024 to over 22,000/month by May 2025.

And when you zoom in by industry, the growth in share is just as dramatic:

Legal: 0.37% → 0.86% of sessions from LLMs
Health: 0.17% → 0.56%
Finance and SaaS are showing similar trajectories, in some cases, exceeding 1% of total traffic

LLMs are becoming a legitimate discovery channel, and they’re doing it fast.

Why it matters:

Most SEO strategies are still stuck in the old timeline:

Optimize → Wait → Crawl → Rank → Convert

That playbook was built for Google’s crawling and indexing cycle – a system that rewards patience, backlinks, and slow iteration.

But LLMs don’t care about that process.

They don’t crawl the same way. They don’t rank in the same order. They don’t wait for your canonical tag to propagate.

They surface content immediately if it’s useful.

The only thing that matters is whether your content helps answer the user’s question in a way the model trusts.

No indexing delay. No competition for blue links. No sandbox.

Just: Is this helpful right now?

That rewires everything.

Content doesn’t need to appear at the top of Google’s SERPs to be found. It needs to be clear, structured, and cited by the model – whether in a blog, a help doc, a case study, or a knowledge base.

And it means the old mindset — publish, wait, and hope Google figures it out — is now dangerously outdated.

We’ve entered the “instant surfacing era” of SEO, where content can be discovered before it even ranks.

If your SEO strategy doesn’t account for that, you’re already behind.

Where LLM traffic is actually going: The real breakdown

Not predictions. Not vibes. Actual traffic.

In the 2025 Previsible AI Data Study, we analyzed LLM-driven sessions across 19 GA4 properties to understand where platforms like ChatGPT, Claude, Gemini, Copilot, and Perplexity are already influencing real user behavior.

Here’s what we found:

Legal topped the chart, with 0.28% of total traffic from LLMs
Finance followed at 0.24%, showing strong traction in regulated markets
Health came in at 0.15%, with a mix of ChatGPT, Gemini, and Perplexity sources
SaaS showed breakout performance but only in some domains, with a selected few getting 1%+ of total sessions from LLMs

But the most important finding?

Legal, Finance, Health, SMB, and Insurance account for 55% of all LLM-sourced sessions across the dataset.

Why these five?

Because people aren’t using LLMs like search engines.

They’re asking contextual, trust-heavy, consultative questions. The kind they’d normally ask a real expert:

“What should I ask a lawyer before signing this contract?”
“Is this medication safe with XYZ conditions, XYZ personal information, and XYZ symptoms?”
“How do I structure payroll as a small business owner that owns a flower shop with 5 employees, 2 part-time and 3 full-time?”

These are high-context moments, and that’s where LLMs are starting to win.

So if your brand plays in a space where trust, clarity, or expertise matters, and your content isn’t optimized for AI, you’re likely missing the exact kinds of requests these models are built to answer.

Model-level insight: Who’s actually driving the traffic?

It’s not just about how much AI traffic you’re getting, but also about who’s sending it.

Across nearly every vertical, ChatGPT is the dominant contributor, consistently driving 40–60%+ of all LLM traffic.

But this isn’t a single-player story. Other models are gaining share, especially in specific sectors:

Perplexity is surprisingly strong, contributing over 0.073% of Finance traffic, 0.041% in SMB, and 0.041% in Legal.
Copilot makes up a meaningful chunk of Legal (0.076%) and Finance (0.036%) sessions. Second only to ChatGPT in both.
Gemini is emerging in Insurance (0.0075%) and SMB (0.035%).
Claude is still marginal (<0.001% in most industries), but present across the board.

Bottom line: While ChatGPT leads, LLM discovery is becoming a multi-model landscape, and performance is beginning to vary by vertical and use case.

This has two implications:

You can’t just optimize for one model. Visibility across platforms will matter more over time.
Different models favor different formats, sources, and structures. Understanding how each one pulls and presents content is your next strategic edge.

How to adapt to the LLM traffic surge starting now

If you’re still treating LLMs like a 2026 conversation, you’re already behind.

The shift is no longer theoretical; it’s happening in your analytics right now. And the teams that move early will stay visible and build a lasting competitive edge.

Here’s how to respond:

1. Start tracking LLM-driven sessions, even if it’s imperfect

You can’t manage what you don’t measure.

Set UTM parameters for AI platforms. Monitor for unexplained spikes in direct traffic. Annotate content that gets surfaced in ChatGPT or Perplexity.

Look for surges in branded search that coincide with AI exposure. Start tracking mentions, not just clicks.

Attribution won’t be perfect – but waiting for standardized reporting is how you miss the wave.

2. Structure your content for AI interfaces, not just human readers

LLMs favor content that’s clean, clear, and scannable. Think bullet points, tight intros, FAQ sections, and strong summaries.

If featured snippets were SEO 2.0, this is 3.0. Answers need to perform inside a model’s response, not just on a results page.

3. Shift your mindset: from ranking to being selected

It’s not about being in position #1 – it’s about being the answer a model chooses to surface.

That means relevance, clarity, and trust signals matter more than ever.

Audit the content already being cited or linked by AI platforms and build a strategy for becoming the go-to source in your space.

If you don’t, your competitor will.

4. Make your content AI-ready across the entire funnel

This isn’t just about blogs.

Product pages, help docs, onboarding flows – every touchpoint is now eligible to be surfaced in an AI conversation.

You need cross-functional alignment between SEO, content, UX, and product teams to ensure your entire site is conversation-ready.

SEO isn’t dying – it’s evolving

SEO is splitting into two tracks: traditional search and LLM-driven discovery.

The second one is growing faster than anyone expected and it’s already rewriting how users find answers and how brands earn visibility.

Move now. Learn fast. Or get left behind.

Read more at Read More

Why your content strategy needs to move beyond SEO to drive demand

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

For many years, SEO has been the lifeblood of content marketing.

Keyword research, quality content, blog optimization, and organic traffic became the gospel of lead generation.

But times have changed.

Take the Great Decoupling of organic impressions from clicks as a result of Google’s AI Overviews.

Or the shift in user behavior away from Google search and toward LLM-powered engines, like ChatGPT.

With these changes, and many others, how we think about content needs to change as well.

If your content strategy still relies on keyword lists and Google ranking to move the needle, you risk falling behind.

Future-forward competitors are learning to adapt to the new landscape of assistive engine optimization, personalization, and immersive content.

This article tackles how to move beyond traditional SEO and build a content engine that powers brand demand across search engines and formats.

What is demand generation content?

Demand generation is an area of marketing focused on generating awareness of and interest in your brand.

Demand generation content, then, is content that speaks to the needs of your target audience, gets you noticed, and makes people aware of your products or services.

It isn’t just MQL capture, though. It’s the full system of:

Educating buyers.
Comparing your brand to competitors.
Accelerating prospective buyers through a decision cycle.

The best demand gen content:

Provokes curiosity.
Answers buyers’ burning questions.
Challenges users’ assumptions.
Turns competitors on their heads.
Offers value (before the “ask”).
Addresses purchase-oriented queries, not just informational searches.

The problem with the traditional “SEO-first” approach to content is that this content typically (not always) involves targeting what people are already searching for.

Which makes sense, because most brands want to capture volume. But this content does little in terms of anticipating users’ questions before they’re asked.

Content in today’s competitive (and comparative) environment needs to create desire, long before your audience even knows what they’re looking for.

The limitations of traditional SEO in demand gen

Now, SEO still matters.

Most of the traditional approaches to optimization still apply, and I don’t suspect Google will disappear anytime soon.

But SEO should not be the sole driver of discovery or your demand gen strategy.

AI and zero-click searches are changing the SERPs

In 2024, 25.6% of desktop and 17.3% of mobile Google searches ended without a click, according to Semrush data.

And those numbers are only expected to grow, especially with the growing prevalence of AI Overviews, featured answers, etc.

This shows that ranking near the top of the SERPs isn’t always enough to drive immediate traffic to your site from those searches.

Trying to rank at the top is still a worthwhile endeavor, as it increases your chances of being seen.

But there are many more pieces of SERP “real estate” for users to see before they ever decide to click on your site.

When users can get answers without having to click through, you lose the ability to move prospective “visits” through the funnel.

Keyword competition is fierce

Also, the highest value keywords you want to rank for are probably the most competitive.

Hundreds, if not thousands, of brands are publishing content optimized for the same keywords. And there are only 10 spots to rank.

Even if your content is technically better, it still might not stand out. You’re competing against the authority and relevance of other domains – often, big players.

Chasing keywords, then, doesn’t quite work as well as it used to. So, your approach to content needs to be revisited.

Buyers don’t just rely on Google anymore

Google is still the leading search engine in town, but the prevalence of LLM-driven engines like ChatGPT and Perplexity is shaking things up.

Users are now able to ask uber-specific questions, receive personalized answers, and seek further clarification on those answers within the answer engines.

They don’t necessarily need Google or you to tell them what they need to know or want to hear.

Also, there are other channels driving the conversations – Instagram, podcasts, Reddit, YouTube, and forums, just to name a few.

A growing portion of B2B buyers spend more time on self-directed research across these types of channels, Gartner reports.

This means that you need to engage potential buyers where they actually are, not just where search engines decide to place you.

From SEO-centric to buyer-centric: How to create content that drives demand

If you want to generate real, tangible demand for your brand, you need to shift your content strategy away from keywords and toward buyer behavior.

That means creating content in anticipation of buyers’ needs, questions, comparisons, and buying triggers.

Here’s how to do that.

1. Identify common friction points

Don’t ask “What are people searching for?”

Instead, ask “What are people debating internally before they buy?”

Any SEO tool can surface keywords like “best restaurant POS” or “best POS for cafes,” but they won’t drive the strategy in terms of addressing buyer friction points, comparisons, etc.

And the importance of addressing friction points becomes obvious when you do any LLM search for your keyword…

Here, we see ChatGPT’s output for “best POS for restaurants,” where it organizes recommendations by:

Business type (e.g., “Enterprise”).
Device (e.g., “Mobile/Tablet Use”).
Budget (e.g., “Budget-Friendly”).

It then prompts you as to whether you’d like to see a “comparison chart” of these options side-by-side.

Targeting and ranking for “best restaurant POS” is:

Likely not feasible given the high competition.
Not sufficient in targeting all of these “comparison”-style queries.

So, instead of creating a “Best Restaurant POS” page or listicle, create content like:

Hidden Costs of “Cheap” Restaurant POS Platforms: Toast vs Square vs [our Brand]
Best Restaurant POS for Tablet: Streamline Your FOH Tech Stack
Your Current Restaurant POS Isn’t Working – X [Competitor] Alternatives to Try
When to Use Toast POS for Your Restaurant (and When You Need Something Better)
Cloud vs. Legacy POS Systems: Which One Is Right for Your Restaurant?

These topics come from actual buying friction.

They don’t simply target high-search-volume keywords but contain valuable information that aids the buyer’s decision and can easily be interpreted by LLMs.

Also, this content tends to work better for cross-channel repurposing, such as in email, paid social, and sales enablement, not just organic search.

Aren’t sure what friction points to address?

Talk to your sales team and customer success managers.

The phrases buyers use in calls and email threads are content goldmines.

It’s also worth checking out ChatGPT and the like to find “gaps” that might be missing in your content (e.g., product features and benefits, brand comparisons, pricing tables, etc.)

2. Prioritize first-party data over third-party sources

Traditional SEO often depends on tools like Semrush or Ahrefs to surface content opportunities.

While this data is certainly valuable, it only really tells you what people are searching for, not what they are actually consuming/interacting with.

First-party data sources, such as Google Analytics 4 or your website’s native analytics, can provide valuable insight into:

How users are engaging with your site.
What they’re searching for on your site (site search).
What’s leading to conversions.

With this information, you’re better positioned to create content based on what your target audience is most interested in and what will drive them to take action, rather than chasing monthly search volume.

Here are a few good sources of user behavior data:

GA4 for conversions, traffic sources, or pages visited.
Your chosen CRM tool (e.g., HubSpot) for lead-to-conversion flow.
Social media, for high-engagement and/or high-CTR content.
Email analytics, such as CTR or reply rates.
Support Center, for customer questions and complaints.

First-party analytics can help guide your demand generation strategy in a few ways.

For one, it can help you address gaps in your existing content, especially if you see users falling off after a particular page.

It can also help you better leverage (CRO-wise) the content that’s performing well, to hopefully generate more conversions from your most popular content.

For example, if your GA4 data shows that you have a service page that gets a lot of clicks but few conversions, you might want to add content like:

“How to Know if [Service] is Right for You – Weigh Your Options.”

Or, if you see from your CRM that leads often drop off after downloading your gated content, consider following up with a targeted email campaign with a subject line like:

“Thinking about [Service]? Read This First…”

Don’t rely solely on search volume to drive your content strategy. Volume without relevance will not generate the results you want!

Get the newsletter search marketers rely on.

See terms.

3. Use content to support the sales process

Demand generation content is not just about lead capture. It’s a tool for generating user interest, addressing friction points, and continuing the sales conversation.

Who said your best content needs to live on your website? There are many different content formats that can be used to drive sales.

Instead of focusing all of your time on web pages and blogs, think of different content assets your sales team could use to support their conversations with prospective customers.

For example:

Objection-handling one-pagers (“Is [Brand] Worth the Cost?”).
Client testimonials praising your product/service against your competitors.
Competitive battlecards repurposed into comparison guides.
Industry-specific guides for different verticals.
Short tutorial videos explaining your products or integrations.

It is important to have content that addresses top-of-funnel interests and bottom-of-funnel buying considerations, and your website should include places for this.

But often, the difference makers occur in the conversations prospective customers have during trials or with your sales team.

Demand generation content should build buyer confidence. Buyer confidence shortens the sales cycle.

Better content leading to higher impact means a better ROI for your business – and this can happen during Sales, not just through content on your website.

4. Form/communicate a clear point of view

Users are spoiled for choice when it comes to “helpful” content.

Any Google search is likely to produce a surplus of listicles, guides, videos, etc.

While “value” may be the goal, this content is often created with SEO in mind – high word count, keyword dense, etc.

But what many brands fail to do is offer a distinct point of view.

People don’t want to read another article they can find anywhere else (and what Google AI Overviews can summarize for them).

They want something actionable, unique, thoughtful, etc. – something that will make their lives better!

So, how do you do that in content?

First, you start with a hook. Ideally, one that taps into a tension your audience already feels. It could be:

A misconception (“Beauty bloggers say you need this, but you don’t…”)
A pain point (“Your skincare routine isn’t doing you any favors…”)
A bold opinion (“Your current restaurant POS sucks…”)

Hooks don’t just grab attention. They immediately communicate the relevance of your content to user interests.

Then, you make your argument. Instead of regurgitating the same old information, connect the dots your way.

For example, instead of a boring guide on “How to Create and Send an Invoice,” show a real customer using your platform to create an invoice step by step.

Something like:

“If you’re a small business owner like me, then you know creating invoices manually is super time-consuming. Here’s what I do to automate my invoicing and get paid faster…”

For another example, a typical “10 Best Summer Dresses for Summer” listicle becomes “10 Girlies Top Picks – What We’re Wearing This Summer,” with reviews from real customers.

In short, try to:

Use real examples from your own customers.
Incorporate stories.
Inject your unique brand voice.
Back up unconventional wisdom with evidence.

Bring something interesting to the SERPs!

In demand gen, this isn’t about being contrarian for clicks.

It’s about helping the reader see their problem differently, and how they can find the solution outside traditional methods and in your product/service.

5. Showcase content on the right distribution channels

Now, you’ve created all this good content. That’s great. But you want it to get seen!

The traditional approach to content marketing was to wait for SEO to do its thing. That can take weeks or months.

Who wants to wait to see results?

Fortunately, there are many platforms available if you want to get your content in front of customers. You just need to identify the right ones.

For demand generation, these platforms tend to work the best:

LinkedIn: B2B buyers, executives, decision-makers, agency leads, founders.
YouTube: DIYers, visual learners, problem-aware buyers, comparison shoppers.
Meta: Business owners, impulse buyers, local service seekers.
Email: Existing leads, subscribers, trial users, pipeline prospects.
X: Thought leaders/influencers, early adopters, B2B.
TikTok: Impulse buyers, creators, DTC shoppers, SMB founders.
Reddit + Facebook Groups: High-intent researchers, skeptics, deep divers, niche hobbyists.

There are others.

It’s important to narrow your focus to the channels your prospective buyers tend to use most and that align with their shopping behaviors.

Your Google Analytics can be a great source of identifying where your referral or social traffic is coming from.

Your sales team may also have insight into where you get most of your business.

The misconception that you need to be everywhere is exactly that – a misconception.

It’s better to create highly targeted content that appeals to the audience on that particular platform, rather than a wide-cast blast of content to every outlet.

Also, you can usually optimize your content for search engines at the same time, for good measure. Long-term potential plus quick gains!

Demand gen example: How Lavender does it right

Lavender is an AI email assistant and sales intelligence platform designed to help reps move faster and close more deals.

But what really sets them apart isn’t just the product – it’s the content strategy behind it.

While they have a blog, it’s far from your basic “top guide” type content.

Just take, for example, some of their recent topics:

“11 Reasons NOT to Buy Lavender”
“Lavender’s Secret Sauce for Onboarding New SDRs”
“Cold Email Wizardry 101”

Also, their LinkedIn presence is consistently valuable, entertaining, and tactical.

They have a clear POV and humorous tone of voice and are shaking up online conversations.

Through this content, prospective customers can discover the brand, engage in conversations, and walk away with something new.

And in the sea of other AI tools, this differentiation is essential.

They share this content on the platforms that matter most to them – well before it hits the Google ranks.

Demand gen content that goes beyond the status quo

SEO content still has its place, but the traditional approach to optimizing content for search engines has been shaken up.

There are many more “no click” options for users to consider than ever before.

Ranking at the top isn’t a foolproof strategy.

A more adaptive approach to content creation is needed for brands to generate new demand and customer interest.

This requires content that addresses user friction, communicates a clear POV, and attracts users at relevant channels.

It also requires looking outside SEO tools for topic ideas and data. It’s not only about what’s searchable.

The more you can differentiate your brand, the better.

And the more you can be adaptive to the LLM-dominated landscape, the less dependent you will be on the SERPs to drive your brand’s traffic and sales.

Read more at Read More

AI ate my traffic by Campaign Monitor

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Have you noticed a dip in your organic traffic lately? You aren’t imagining it.

AI-powered search engines, such as Google’s AI Overviews, ChatGPT, and Perplexity, are transforming the way people discover and consume content. Instead of clicking your link, users are getting instant AI-generated answers – often built from your content – without ever visiting your site.

You’re still publishing and optimizing. But your results are shrinking.

Welcome to the AI discovery era, where your hard-earned traffic is the appetizer on someone else’s plate.

SEO isn’t dead – but it’s no longer yours

Organic rankings no longer guarantee visibility. AI search experiences are removing the middle step between “search” and “solution.” Your website often gets cut out in the process.

If your strategy is solely focused on SEO and attracting clicks, your success depends on platforms you don’t control.

The answer: reclaim what you own

In this new landscape, the smart move isn’t just chasing new traffic – it’s protecting and activating the audience you already have.

That means doubling down on email.

Why?

Email remains:

Direct (no algorithm middleman)
Personal (built for 1:1 relationships)
Segmentable (think personalize, automate, scale)

In fact, according to Marigold’s 2025 Consumer Trends Index Report, 77% of respondents stated they were likely to engage with an email focused on exclusive VIP offers, while 86% said they would be motivated to engage with sale or holiday promotions.

But here’s the kicker: to segment messaging and remain consistent in your outreach, you need a platform built for fast-moving businesses.

Introducing Campaign Monitor by Marigold – your revival engine

Campaign Monitor isn’t just for sending newsletters. It’s your command center for fostering, rebuilding, and monetizing opportunities.

Here’s how Campaign Monitor helps power your revival:

List management at scale

With traffic declining, your contact and email lists are more valuable than ever, and they are unique to your business. Through Campaign Monitor, you can use your owned lists to:

Segment by behavior, purchase history, or engagement.
Identify dormant contacts and re-engage them.
Clean your list to improve deliverability and performance.

Automation that nurtures (while you sleep)

Don’t send one email and hope. Use Campaign Monitor to:

Welcome new subscribers with personalized messages.
Deliver value-driven nurture sequences with easy-to-use pre-built journeys.
Trigger timely emails based on behavior, like abandoned carts or event registration. With intelligent automation, you can turn a cold list into a steady stream of engaged leads and real conversion opportunities – no late nights required.

Personalization that cuts through the noise

Generic emails are easy to ignore. Campaign Monitor allows you to:

Personalize subject lines, product recommendations, and timing.
Use dynamic content to deliver the right message to the right person.
A/B test and optimize continuously.

Real metrics. Real decisions.

AI platforms don’t share data. Campaign Monitor provides insights into audience engagement and campaign performance, allowing marketers to optimize their strategies:

See who’s opening, clicking, and converting.
Track revenue generated from each campaign.
Attribute performance down to the segment or workflow.
No guesswork. Just growth.

So… what now?

AI may have eaten your top-of-funnel traffic, but that doesn’t mean your pipeline is doomed.

Now is the time to:

Rebuild your list with intent-driven offers.
Modernize your email strategy with segmentation, automation, and personalization.
Use Campaign Monitor to make it all scale – without burning out.

Final word

AI isn’t your enemy. Passive marketing is.

The smartest brands are adapting by doubling down on what they can control: their list, their messaging, and their subscriber relationships.

With Campaign Monitor by Marigold, you’re not just surviving the AI age – you’re reviving your funnel for the long haul.

Read more at Read More

AI Max gets new reporting features

August 4, 2025/0 Comments/in Search Engine Land, Web Design News/by

Why campaign-specific goals matter in Google Ads

Google Ads’ AI Max reporting now allows advertisers to view search terms, headlines, and landing pages in a single report, offering a clearer window into how AI-powered campaigns operate.

Why we care. This update means less guesswork and more control. You can now see what users actually searched for, which landing page Google’s AI sent them to, and the headline shown alongside the ad. That’s a big upgrade from the days of Performance Max (PMax), where advertisers waited years for basic visibility into campaign behavior.

The details. Especially useful if you’re using Final URL expansion or Auto-Generated Assets

It also makes it easier to:

Spot when a product search lands on a generic category page.
Diagnose and fix page mismatch issues.
Deactivate Final URL expansion if needed.

“This means more transparency. From Month one. Unlike PMax where we had to wait 4 years,” said Thomas Eccel, head of Google Ads at JvM IMPACT.

Bottom line. Google is giving advertisers a clearer lens into AI Max behavior – allowing for smarter optimization, faster troubleshooting, and a better user experience. This update removes a major blind spot in AI Max reporting.

First seen. The update was mentioned by Eccel who credited senior SEA consultant Jerome Fleck for first spotting it.

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AI Max experiments arrive in Google Ads: Here’s how they work

August 4, 2025/0 Comments/in Search Engine Land, Web Design News/by

How Google works: Experiments, entities, and the AI layer beneath search

Google Ads rolled out a new AI Max experiment type for Search campaigns, aimed at streamlining how advertisers test AI-powered features – without duplicating campaigns.

Why we care. Traditional experiments require creating campaign copies, adding complexity and delaying results. This new format runs within the original campaign, splitting the budget 50/50 between control and test groups. The goal: faster, statistically valid insights.

How it works:

Found under a new Choose a variable to test section, advertisers can now select AI Max for Search campaigns.
The experiment auto-enables:
- Search Term Matching
- Asset Optimization
Advertisers can customize these settings at the campaign or ad group level.
By default, results are auto-applied. This can be turned off for more control.

Zoom out. The new setup is already visible in many accounts. For those looking for more details, Google Ads’ help page on AI Max Experiments breaks it down.

First seen. This update was first surfaced by marketing consultant Dario Zannoni.

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