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The Ultimate  Content Marketing Guide in 2026

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Key Takeaways

  • Content marketing is how you turn attention into trust, and trust into business outcomes. Every section of this guide covers a piece of that pipeline. 
  • The majority of top-performing B2B marketers credit audience understanding as their top success factor. Define who you’re reaching and what problem they’re solving before producing anything. 
  • One well-researched piece outperforms 10 thin ones. Cornerstone content keeps earning attention for years. 
  • A blog post that performs can fuel a video or social carousel. Repurposing extends reach without doubling the work. 
  • Use AI for research and outlining. Protect original perspective and first-hand experience as the work only you can do. 

Many people feel like AI means the end of content marketing as we know it.  

That couldn’t be further from the truth.  

The strategy is strong as ever, even if it’s not a new idea. What’s changed are the tools we use and the factors that set good content marketers apart.  

Unsurprisingly, the playbook that worked even three years ago no longer holds up.  

This content marketing guide is built to prepare you for that reality. I’ll walk you through what strategies and formats will shape the future of content marketing, plus where AI fits without dragging down your quality. 

What Makes Content Marketing Work

The content that drives real results does three things consistently: 

  • It addresses a problem someone is actually trying to solve. 
  • It reaches that person at a moment when they’re looking for help, and it doesn’t show up as a pitch. 
  • It nudges them one step closer to a decision, whether that’s signing up for a newsletter or making a buying decision. 

If a piece of content doesn’t check all three, it’s filler. Only 22 percent of B2B marketers say their content marketing is extremely or very successful. Of that group, 82 percent credit audience understanding as the top driver of their results, not publishing volume or chasing trends. 

All that to say: Keep your audience top of mind in all your content marketing efforts. 
 

Bar graph showing the factors that B2B marketers say contribute to their content marketing success 

Source: https://contentmarketinginstitute.com/content-marketing-strategy/content-marketing-statistics 

The audience focus also reframes the old paid vs. organic debate.  

You can’t just pick one. Paid advertising drives instant visibility, while content compounds in value over time.  

Smart teams use them together. Start by building assets organically and identifying the pieces that resonate. Then put paid dollars behind the ones that strike a chord with your audience.  

Content marketing for small businesses runs on this principle, since tighter budgets mean every dollar has to pull more weight. 

How to Do Content Marketing: Building Your Strategy

Most content fails because there’s no strategy behind it. Nearly half of B2B marketers with only moderately effective strategies point to unclear goals as the reason.  

These four steps give your campaigns the kind of direction that drives real business results. 

1. Define Your Audience and Goals

Every content strategy starts with two questions: Who are you trying to reach, and what do you want them to do?  

Vague goals like “build brand awareness” are a wish. “Add 500 email subscribers this quarter” or “double trial signups from organic search by the end of the year” are quantifiable goals you can shoot for. 

Start defining your target audience by the problem they’re trying to solve, not just by demographic data. For example, a 45-year-old chief marketing officer (CMO) at a SaaS company and a 45-year-old founder of a brick-and-mortar shop look identical in a spreadsheet, right? Chances are, though, they gravitate toward completely different content. 

2. Choose Your Formats and Channels

Pick formats that match your audience and goals.  

  • Blog posts still dominate for SEO and lead generation.  
  • Podcasts may be a good pick if your audience isn’t full of big readers 
  • Social keeps you top of mind between site visits. 

The trick is not trying to master everything all at once. Focus on one or two channels and expand only once they start performing. 

3. Build a Publishing Cadence

Consistency beats volume. A weekly post you follow through on publishing is worth a lot more than a daily schedule you ditch after a month.  

Use an editorial calendar to plan topics and publish dates a month or quarter at a time. You don’t need fancy software for this. Asana, Trello, Monday.com, or even a shared spreadsheet will do the job.  

The fanciest format doesn’t win here. Stick to whatever you can come back to time and time again. 

An editorial calendar plans content deliverables and helps establish a consistent cadence. 

 
Source: https://neilpatel.com/blog/create-editorial-calendar/ 

4. Plan for Distribution

Hitting “post” puts content on your site, but distribution is what gets it in front of people.  

Most great pieces of content need at least two distribution channels working to gain traction. 

Think about your distribution plan from the beginning of your content process. So, dig into where your target audience is spending the most time.  

If LinkedIn is where your audience lives, you could repackage each blog post as a carousel and a long-form post after publishing. If they’re on YouTube, you might cut a 60-second clip from the supporting video.  

Match the repackaging to the channel. 

Paid promotion fits into this plan, but only after content has proven it can resonate organically.  

Put budget behind the pieces that are already earning attention. That signal tells you they’ll perform when amplified. 

Content Marketing Tips That Actually Move the Needle 

The fundamentals above are enough to get you started, but these content marketing tips are what separate teams that hit their numbers from teams that publish and pray. Each one is a lesson learned from our work with hundreds of clients at NP Digital. 

Map Content to the Buyer Journey

Each content type has its own purpose. The classic three funnel stages (awareness, consideration, and decision) still apply, though AI is collapsing the traditional funnel and changing the buyer journey.  

A how-to blog post still works for readers trying to understand a problem, and its instructional, question-based format is great for AI visibility. A comparison guide or case study is perfect for someone mid-funnel in their journey, weighing solutions. A free trial offer or pricing page is perfect for someone who is near the bottom of the funnel, ready to buy. 

AIDA framework funnel showing four customer journey stages: Awareness, Interest, Desire, and Action. 

Source: https://neilpatel.com/blog/content-marketing-and-beyond/ 

One callout worth its own line: Question-based, instructional blog posts now double as your best shot at AI visibility. Their format matches how large language models pull and cite information, so a well-structured how-to can earn you both Google traffic and LLM citations. 

A common beginner mistake is publishing only top-of-funnel content and wondering why none of it converts. Audit what you have. If you’re heavy on awareness pieces and light on decision-stage content, that could be why leads are dropping off. 

Prioritize Depth Over Volume 

One comprehensive, well-researched piece will often outperform 10 thin ones.  

Orbit Media’s 2025 survey found that marketers publishing 2,000-plus-word articles were nearly twice as likely to report strong results, 39 percent vs. 21 percent across all respondents.  

That can translate to a huge business impact. A cornerstone guide written today can still drive traffic and generate leads three years from now, something a paid ad can never do.  

Think of content as an asset. It’s not just output that fills a calendar. Use it to build a library that keeps working long after you publish it. 

Repurpose What’s Already Working

A blog post that performs well is the seed for a dozen other pieces. The same post can become several other content assets, from video scripts to email series.  

Content repurposing saves 60 to 80 percent of the time it would take to create from scratch. That goes a long way for smaller teams. 

Just don’t repurpose mindlessly, though. Your top organic blog post, your highest-engagement webinar, or a LinkedIn post that overperformed are all strong candidates. Pull the core insight, then rebuild it in the format and channel where your audience consumes content. 

That might mean a 1,500-word how-to becomes a five-email nurture sequence or a 90-second explainer video. 

Here’s an example from my own site. I took a blog post on [topic] and turned it into a companion YouTube video covering the same ground for viewers who prefer to watch rather than read. Same insight, two formats, two different segments of the audience reached. 

Neil Patel blog post titled “YouTube Marketing Strategy: Grow Your Channel.

Source: https://neilpatel.com/blog/youtube-marketing-guide/ 

Alt txt: YouTube video titled “Why YouTube Is the Best Place to Find Customers Right Now.” 

A YouTube video.

Source: https://www.youtube.com/watch?v=DAKFpSgJY9o 

Use Paid Promotion to Amplify Organic Wins

This is where a lot of teams leave money on the table.  

If you have a blog post ranking on page two and pulling steady traffic or a video that’s getting unusually high watch time, that’s a glaring sign to amplify it with paid social or search dollars.  

The organic performance has already proven that the content resonates. Paid dollars just accelerate the reach. 

Running this kind of integrated paid-and-organic workflow takes coordination that a lot of internal teams just aren’t built for. Content marketing companies handle this kind of work daily. 

Track the Metrics That Matter 

Page views and social likes feel good, but they rarely tell you whether content is working. The metrics that matter depend on your goals from the start, but most content programs should be tracking some version of these: 

  • Organic traffic to commercial pages 
  • Time on page for in-depth pieces 
  • Conversions from content (email signups, demo requests, free trial activations) 
  • Return visits from the same user 
  • Pipeline or revenue attributed to specific pieces 

Tie every metric back to the goals you set in step one of your strategy. Google Analytics 4 (GA4) handles the traffic and behavior measurement. Your marketing platforms (HubSpot, Klaviyo, Mailchimp, or whatever stack you run) handle the conversion side.  

If you can’t draw a line from a piece of content to a business outcome, you can’t make the case to keep funding it. 

How AI Fits Into a Content Marketing Strategy 

About 94 percent of marketers plan to use AI in content creation in 2026. AI has changed how content gets made, but it hasn’t changed what makes content work. The question is how you use it. 

Three places where AI genuinely helps: 

  • Research and ideation. Use these tools to discover new, refreshing ways to cover popular industry topics and find gaps in what’s already ranking. AI can compress hours of background work into minutes. 
  • Drafting and outlining. Use AI to generate a structural skeleton or rough first draft you can then refine. About 61 percent of marketers use AI for outlining, which is exactly the kind of structural work it does well. 
  • Repurposing existing content. AI can quickly adapt a blog post into a LinkedIn carousel or a video script. The original thinking is already done. The platform just splices the original content into the format necessary to generate ROI on other platforms.  

Where AI comes up short is on original perspective and real expertise. These platforms draw on what already exists, so they’re structurally limited when it comes to fresh insight. That matters for SEO, too. 

Google has been clear that it doesn’t penalize AI-generated content as a category, but it does penalize  scaled, low-effort content that exists only to game rankings.  

The teams excelling with AI use are the ones taking the time to edit and humanize content output. They also enhance their assets by adding firsthand experience and treating AI output only as a starting point.  

Use AI and other content marketing tools to move faster on the parts that don’t need a human and protect the parts that do.  

FAQs

 

What is content marketing?

Content marketing is the practice of creating and distributing valuable content (blog posts, videos, podcasts, email, social) to attract and retain a defined audience, to drive profitable customer action. 

Why is content marketing important?

It’s a cost-effective way to drive sustained traffic, leads, and revenue. A single piece of strong content can generate returns for years, whereas paid ads stop the moment you stop paying.

What is a content marketer?

A content marketer plans, creates, distributes, and measures content tied to business goals. The role spans strategy and writing workflows, as well as strategy and performance analytics, depending on the team’s size. 

How does content marketing help SEO?

Search engines reward sites that publish helpful, in-depth content. Each well-optimized piece is another opportunity to rank for relevant keywords and build topical authority over time.

Why is content marketing important for B2B?

B2B buyers research independently before talking to sales. Content meets them in that research phase, builds trust, and shortens the sales cycle. The majority (87 percent) of B2B marketers say content marketing helped create brand awareness. 

Conclusion

Content marketing is a high-ROI strategy, but only when you build it on a defined audience and content that genuinely helps those people. The teams pulling ahead in 2026 are publishing with clearer goals and a tighter strategy. 

Playing the volume game won’t get you anywhere. 

Pick one strategy from this content marketing guide and act on it this week. Maybe that’s writing down three specific goals you didn’t have before. Maybe it’s auditing your content against the buyer journey.  

If you implement and have patience, your marketing will start to gain traction. From there, you’ll see the light at the end of this wild marketing tunnel.  

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Best Backlink Analysis Tools: Compare Free and Paid Options

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Key Takeaways

  • The right backlink analysis tool depends on the job: Ahrefs or Semrush for deep data, Pitchbox or BuzzStream for outreach, Linkody for monitoring, and Whitespark for local SEO.  
  • Referring domains carry more weight than total backlink count. One link from 100 different sites beats 100 links from a single source. Backlink tools help you target the most impactful ones. 
  • Every tool in this guide includes a competitor link gap report, which surfaces sites linking to your competitors but not to you.  
  • A quarterly link audit catches toxic links, broken backlinks pointing to your site, and outreach wins worth replicating.  
  • Monthly pricing spans $14.90 to over $500. Match the tool to the scale of your work, not to what an enterprise SEO team would buy. 

What comes to mind when you think about creating a “good” link profile? 

Search “What are backlinks,” and Google returns plenty of information, including the  steps  you can take today to improve your link profile and boost your rankings. 

In the past, I’ve provided a lot of advice on building quality links, where to find the best links, and tools that can help. 

Those tips can get you far, but there’s something else you need to do first: Examine your link profile. 

If your website is brand new, this won’t always be a big deal. That’s because you probably don’t have links pointing to your website yet. 

Conversely, if your website’s been around for a few months or longer, there’s a good chance you have some links pointing to it. Some may be good. Some may be bad. Others may not move the needle in either direction. 

It’s important to understand your link profile, as this will give you a clear idea of whether you’re on the right track. 

In a perfect world, you’d see nothing but high-quality, relevant links  pointing to your site. That’s rarely the case in the real world, though. 

Need help conducting a link audit and reviewing the results? If so, this post is for you. Below, you’ll find 14 backlink tools packed with features that shed light on your link profile.  

Backlink Analysis Tools: The Basic Comparison

Pages with backlinks get more organic traffic than pages without, according to Ahrefs research.  

A good backlink analysis tool tells you who links to you, who links to your competitors, and which links are helping your rankings. That way, you know where to target your outreach efforts next. 

The 14 tools I cover in this guide differ in several ways. Some are all-in-one SEO suites with strong backlink modules. Others focus narrowly on a single job, such as outreach or local citations. The right pick depends on your linking strategy and your budget. 

Here’s a side-by-side look at every tool covered below. Pricing reflects entry-level paid plans at the time of writing and may have shifted, so check the vendor’s site before committing. 

Tool  Best For  Standout Feature  Starting Price (Monthly) 
Ubersuggest  Small businesses and solopreneurs  Affordable lifetime plans  $29 
Semrush  Agencies and in-house marketing teams  Backlink gap analysis  $139 
Ahrefs  SEO professionals who need deep link data  Largest live backlink index  $129 
BuzzSumo  Content marketers and PR teams  Content + influencer discovery  $199 
AIOSEO  WordPress users running on-site SEO  Native WordPress integration  $49.50/year 
Linkody  Solo SEOs monitoring a few sites  Real-time disavow management  $14.90 
Cognitive SEO  Mid-sized teams cleaning toxic links  Unnatural link detection  $129.99 
Majestic SEO  Researchers focused purely on link metrics  Trust flow and citation Flow  $49.99 
SEOptimer  Agencies producing white-label audits  Customer-facing reports  $29 
Moz Link Explorer  Marketers who rely on domain authority (DA)  DA, page authority (PA), and spam score  $99 
Pitchbox  Outreach-heavy link-building teams  Automated outreach sequences  $300 
Whitespark  Local SEO specialists  Local citation discovery  $39 
Linkstant  Real-time backlink alerts (legacy)  Instant new-link notifications  $7 
BuzzStream  Outreach and digital PR teams  Built-in customer relationship management (CRM) for prospects  $24 

1. Ubersuggest 

A screenshot of the Ubersuggest homepage telling brands they can get mentioned in Google and Gemini. 

Ubersuggest is my own tool, and I’ve designed it to make serious backlink analysis accessible without an enterprise budget.  

You get a full backlink overview for any domain, including new and lost links, referring domains, anchor text breakdowns, and a domain authority (DA) score.  

The Backlink Opportunity feature is the one I use most. Plug in two or three competitor URLs, and Ubersuggest gives you every site linking to them but not to you. That’s a ready-made outreach list. 

  • Pricing: Plans start at $29 per month for individuals, $49 for small teams, and $99 for agencies. Unlike most competitors, Ubersuggest offers lifetime plans. 
  • Best for: Solopreneurs, small business owners, and in-house marketers who want a solid backlink workflow without paying enterprise rates. If you’re new to SEO, the interface is easier to navigate than that of Ahrefs or Semrush. 
  • Considerations: The link index isn’t as deep as Ahrefs or Majestic, but that won’t matter as much for most small to midsizedsites, that won’t matter. 

2. Semrush 

A screenshot of Semrush’s backlink checker homepage tells readers they can win backlinks that move rankings and offers a free trial.  

Semrush says it runs one of the largest backlink databases in the industry, with more than 43 trillion backlinks indexed. It earns its place on this list for that data depth alone. 

The free Backlink Checker is good for quick checks. You can see a site’s top backlinks, Authority Score, total backlinks, referring domains, dofollow percentage, anchor text, link attributes, and whether links are new or lost. That’s useful if you just want a snapshot of your site or a competitor. 

The paid tools are where Semrush gets more useful for serious backlink work.  

Backlink Analytics gives you fuller backlink and referring domain data, more reports, filters, and tracking. Backlink Gap lets you compare your link profile against up to four competitors in a single view.  

Semrush also includes Backlink Audit, which scores toxic links and flags candidates for the disavow file.  

Both pair well with Semrush’s keyword and traffic data, which is why many agencies consolidate on this platform. 

  • Pricing: Semrush’s SEO + AI Search plans start with the SEO plan at $139. The Pro+ plan is $299. The Business plan ($549) adds AI visibility tools and other functionality. Discounts for annual billing are available, and Semrush also offers a seven-day free trial. 
  • Best for: Marketing agencies and in-house teams that need backlink data alongside full SEO, PPC, and competitive intelligence. If backlinks are one of five or six things you analyze regularly, Semrush is hard to beat. 
  • Considerations: Semrush’s free backlink tools are fine for quick checks. You’ll need a paid plan for serious backlink work, though. 

3. Ahrefs 

Ahrefs Backlink Checker homepage offering a free trial version. 

Ahrefs is one of the strongest backlink tools for SEOs who need more than a quick link count. Its free Backlink Checker is useful for spot checks, but its Site Explorer tool is where serious backlink work happens.  

Ahrefs says its backlink index updates with fresh data every 15 minutes and includes 35 trillion external backlinks in historical records.  

Site Explorer shows referring domains, backlinks, domain rating, anchor text, followed vs. nofollowed links, backlink growth, and “best by links,” which helps you find the pages attracting the most links.  

Content Explorer helps surface link-worthy content ideas, while Link Intersect finds sites linking to competitors but not to you.  

Ahrefs does have free access, but there’s a catch. The free account gives verified site owners limited Site Explorer access for their own websites, including backlinks, referring domains, anchors, and “best by links.” Competitor research, larger reports, Content Explorer, and more advanced link-building workflows require a paid plan.  

  • Pricing: Lite is $129 per month, Standard is $249, Advanced is $449, and Enterprise starts at $1,499 per month. Discounts for annual billing are available. 
  • Best for: SEO consultants, agencies, and in-house specialists who live on backlink data daily. Ahrefs may be overkill for someone publishing one blog post a month but invaluable for anyone running active outreach or technical SEO audits. 
  • Considerations: Lite works for basic backlink monitoring, but Standard is the better fit for most serious users. 

4. BuzzSumo

A screenshot of the BuzzSumo homepage. 

BuzzSumo started as a content discovery tool, and that’s still its strongest trait. Its backlink data is built around content, not just domains, so you can see which articles in your niche earned the most links and where they came from. 

The Content Analyzer pulls the top-shared and top-linked content for any keyword. Pair it with the influencer search, and you have a workflow for finding the writers and publications most likely to link to a similar piece on your site. The link-building use case here is digital PR, not technical backlink audits. 

  • Pricing: Content Creation starts at $199 per month; PR & Comms at $299; Suite at $499; and Enterprise at $999. Annual billing knocks roughly 20 percent off. 
  • Best for: Content marketers and PR teams who build links through earned media rather than direct outreach. If you want to know what’s working in your space and who to pitch, this is the tool. 
  • Considerations: It’s not a replacement for Ahrefs or Semrush on raw backlink data. 

5. AIOSEO

A screenshot of AIOSEO’s homepage. 

AIOSEO (All in One SEO) is a WordPress plugin first and an SEO suite second. It’s not a dedicated backlink checker, but it can help WordPress users manage the links they control inside their own site. 

Its Link Assistant shows internal links, external links, affiliate links, orphaned posts, and top domains you link to. That makes it useful for improving internal linking and cleaning up outbound links, but it won’t replace a backlink database like Ahrefs or Semrush. 

Broken Link Checker is another useful add-on. It scans your content for broken links and images, then lets you address issues. The free version includes 250 internal and external link checks per month. 

  • Pricing: Annual plans range from $49.50 for Basic to $299.50 for Elite. 
  • Best for: WordPress site owners who want on-page SEO, sitemaps, and lightweight backlink data in one plugin. If you already pay for a dedicated backlink tool, AIOSEO is more of a complement than a replacement. 
  • Considerations: AIOSEO is not a true backlink analysis tool. Use it to manage links on your WordPress site. 

6. Linkody

A screenshot of Linkody’s homepage. 

Linkody is a tool built for backlink monitoring. Add your domain, and Linkody tracks discovered links and alerts you when links go live or drop. The platform even handles marking links for disavow with a built-in file generator. 

The dashboard provides backlink status, anchor text, follow/nofollow data, landing pages, Moz DA, spam score, majestic trust flow and citation flow, and other link-quality signals.  

The disavow workflow is what sets Linkody apart, though. You can flag toxic links inside the dashboard and export the file for Google Search Console in a couple of clicks. 

  • Pricing: Webmaster starts at $14.90 per month, Advanced at $24.90, Pro at $49.90, Agency at $99.90, and Agency XL at $153.90. Free trials and discounts for annual billing are available. 
  • Best for: Solo SEOs, freelancers, and small agencies who want backlink monitoring and disavow management without paying for a full SEO suite. The price-to-feature ratio is the main draw. 
  • Considerations: Linkody is great for monitoring and managing backlinks, but it’s not as deep as some of the other tools on this list for large-scale backlink research. 

7. CognitiveSEO

A screenshot of CognitiveSEO’s homepage. 

cognitiveSEO gets its reputation from the Unnatural Link Detection tool, which scores links in your profile for risk and flags candidates for disavow. If you’ve inherited a site with a messy link history or recovered from a penalty, this is the platform for you. 

Beyond toxic link cleanup, you get rank tracking, content optimization, and competitive backlink analysis.  

The main draw is the link-quality workflow. cognitiveSEO aggregates backlink data from trusted link databases, then crawls and analyzes links on demand, so it’s better framed as an audit and recovery tool than a pure backlink index play. 

  • Pricing: Starter is $129.99 per month, Premium is $199, and Elite is $499. Annual billing offers a discount. A free trial is available. 
  • Best for: Mid-sized teams and consultants who handle penalty recovery, link audits, or sites with risky historical link profiles. 
  • Considerations: cognitiveSEO is strongest for backlink cleanup and risk review. It’s less compelling if you only need everyday backlink discovery or broad SEO reporting 

8. Majestic SEO

A screenshot of Majestic SEO’s homepage suggesting they’re specialists in backlink analysis. 

Majestic predates most of the tools on this list and remains a go-to for pure link metrics. Its proprietary metrics, trust flow and citation flow, are highly regarded across the SEO industry and shown inside other tools, like Linkody. Trust flow estimates link quality, while citation flow reflects link quantity. 

Majrestic’s Site Explorer report shows referring domains, anchor text, and a topical trust flow that breaks down which niches link to you. The Link Context feature displays the surrounding paragraph for any backlink, helping you judge link quality at a glance. 

  • Pricing: Lite is $49.99 per month, Pro is $99.99 per month, and API access is $399.99 per month. Annual billing is available at a discount. 
  • Best for: SEO researchers, link prospectors, and analysts who care more about link metrics than the full SEO suite experience. Trust flow and citation flow are the reasons most people sign up. 
  • Considerations: Majestic is strong for backlink analysis, but it does not replace all-in-one SEO tools. 

9. SEOptimer 

A screenshot of SEOptimer’s homepage. 

SEOptimer is best known for white-label site audits, and its backlink research module fits into that broader reporting workflow. The dashboard pulls referring domains, anchor text, and link quality scores you can drop straight into client-facing reports. 

The embeddable audit tool is a nice touch for agencies. You can install a lead-generation form on your site that runs a free backlink and SEO audit for prospects, capturing the lead. 

  • Pricing: DIY SEO starts at $29 per month, White Label at $39, and White Label & Embedding at $59. Annual billing discounts are available, as is a free trial. 
  • Best for: Small agencies and consultants who need affordable, brandable reports for clients. If you’ve been using a tool called Monitor Backlinks, that product has now been merged into the SEOptimer platform. 
  • Considerations: SEOptimer is stronger for audits and lead generation than deep backlink research. 

10. Moz Link Explorer

A screenshot of the landing page for Moz Link Explorer. 

Moz Link Explorer is built around domain authority, the metric many SEOs still use as a quick read on site strength. The tool provides DA, page authority (PA), spam score, and a full backlink profile with link-quality filters. 

The Link Intersect report shows pages linking to your competitors but not to you, similar to Ahrefs and Semrush. Moz also tracks new and lost links over time, which helps spot outreach wins or drops in your link profile. 

  • Pricing: Standard starts at $99 per month, Medium at $179, and Large at $299. Annual billing is discounted, and a free trial is available. Free Moz access is useful for occasional DA checks and light backlink research, but it’s limited. 
  • Best for: Marketers and content teams who already work with DA and want a familiar backlink dashboard alongside keyword and rank tracking tools. 
  • Considerations: The link index is smaller than Ahrefs, but Moz’s data quality and reporting are reliable for everyday work. 

11. Pitchbox

A screenshot of Pitchbox’s homepage also showing a snapshot of their SEO campaign dashboard. 

Pitchbox is an outreach platform with backlink prospecting built in. You can create prospect lists, find contacts, run outreach sequences, manage follow-ups, track replies, and monitor links from one dashboard. 

Integrations with Moz, Ahrefs, Semrush, and Majestic let you filter prospects by link metrics before reaching out, shortening the time from finding a prospect to sending a personalized pitch. 

  • Pricing: Pro is $300 per month, Advanced is $600 monthly, and Scale is $1,200 monthly. Enterprise pricing is custom. Annual billing discounts are available, and a free trial is available. 
  • Best for: Agencies and in-house teams running serious outreach programs. If link building is a primary channel and you’re sending hundreds of pitches a month, Pitchbox pays for itself quickly.  
  • Considerations: For occasional outreach, Pitchbox is probably overkill. 

12. Whitespark

A screenshot of Whitespark’s homepage. 

Whitespark focuses on local SEO, and its backlink-adjacent work centers on citations—the mentions of your business name, address, and phone number across local directories and review sites. 

The Local Citation Finder identifies high-value citation opportunities for any business or competitor. Whitespark also offers done-for-you citation building and cleanup, as well as a local rank tracker. The toolset is deliberately narrow. It’s built for local businesses, not enterprise SEO. 

  • Pricing: Local Citation Finder has a free starter plan. Paid plans start at $39 per month for Small Business, $49 for Specialist, $59 for Agency, and $149 for Enterprise. Annual billing is available at a discount. 
  • Best for: Local businesses and agencies serving multi-location clients. If you serve a geographic market and rely on Google Business Profile rankings, Whitespark is the tool for you. 
  • Considerations: Whitespark is not a backlink research tool in the Ahrefs or Semrush sense. Use it for citations, listings, Google Business Profile visibility, and local rank tracking. 

13. Linkstant

A screenshot of Linkstant’s homepage explaining why it’s powerful to discover your new backlinks instantly.  

Linkstant carved out a niche around one promise: instant alerts when a new link points to your site. While most tools poll for new backlinks once a day or once a week, Linkstant ran on near-real-time detection, enabling users to thank the linker, share the content, or correct a broken link within minutes. 

  • Pricing: Linkstant’s small business package is $7 per month, and its enterprise pricing is $27 per month.  
  • Best for: Anyone building outreach workflows around instant backlink notifications.  
  • Considerations: Linkstant is not a replacement for a backlink analysis platform. 

14. BuzzStream 

A screenshot of BuzzStream’s homepage. 

BuzzStream is an outreach customer relationship management (CRM) platform with link research baked in. You research prospects, find their contact info, send personalized pitches, and track every conversation from a single dashboard. The backlink piece comes from integration with Moz and built-in link metrics that help you qualify prospects. 

The list-building features make it easy to import prospects from a Google Sheet or scrape them directly from search results. From there, the CRM handles the rest of the outreach cycle. 

  • Pricing: Starter is $49 per month, Growth is $174, Professional is $424, and Custom starts at $999. A free trial is available. 
  • Best for: Digital PR and link-building teams that prioritize relationship management over raw link data.  
  • Considerations: BuzzStream is best paired with a dedicated backlink tool if you need deep competitor link research or large-scale backlink audits. 

Finding the Right Backlink Tool for You (and Getting the Most Out of It)

The right backlink analysis tool depends on three things: what you do with backlink data most often, how many sites you manage, and what you can spend. A solopreneur running one blog doesn’t need the same setup as a large agency. 

Start with your goals and the task at hand.  

  • If you mostly research competitors and prospect for new links, Ahrefs or Semrush makes sense.  
  • If outreach is the bottleneck, Pitchbox or BuzzStream pays for itself.  
  • For budget-friendly monitoring and disavow management, choose Linkody or CognitiveSEO.  
  • Local businesses should look at Whitespark first. 

Once you’ve picked a tool, get the most out of it by following a few rules. 

  • Audit your link profile quarterly. Look for new toxic links, broken backlinks pointing to your site, and outreach wins worth replicating. 
  • Track referring domains, not just total backlinks. One link from 100 domains beats 100 links from one domain. If the difference between referring domains and backlinks is fuzzy, start there. 
  • Pay attention to link attributes. A lot of people get hung up on dofollow vs. nofollow backlinks when creating their strategy, but these attributes don’t change much. A toxic dofollow link can hurt your rankings, while a high-quality nofollow link still drives referral traffic. Your energy is better spent on routinely auditing and maintaining your profile. 
  • Use competitor gap reports. Every tool in this guide offers some version of a competitor link intersect. That report alone justifies the subscription for most users. 

If picking and running a backlink strategy still feels like a lot, my team handles this work for businesses every day. NP Digital builds custom link strategies, and I offer SEO consulting for businesses that want a more hands-on approach. 

FAQs

What is a backlink profile?

A backlink profile is the full picture of external links pointing to your site, including referring domains, anchor text, dofollow or nofollow attributes, linking-site authority, and link velocity. A healthy profile draws from varied, authoritative sources. Backlink tools like Ubersuggest, Ahrefs, and Moz can help you pull yours in seconds. 

What is a backlink analysis tool?

Backlink analysis tools help website owners analyze their website’s backlink profile. It provides information on the links pointing to their website from external sources, including the number, quality, and relevance of the links. You can use this information to identify areas for improvement in the website’s link-building strategy and improve its search engine rankings. 

How to check backlinks of a website?

Open Ubersuggest, Ahrefs, Moz Link Explorer, or Semrush and run the report for your target site’s root domain. You’ll see total backlinks, referring domains, anchor distribution, top-linked pages, and a domain authority score. Focus on referring domains rather than raw link count, and watch for unnatural anchor patterns to weed out bad links. You should also study top-linked pages for you and your competitors to see which content is working for specific keywords in your industry.  

How to check competitor backlinks?

Run three to five competitor domains through a tool with a link gap or link intersect report (most, if not all, of the tools in our list offer one). The report surfaces sites linking to your competitors but not to you. Sort by domain authority, then prioritize relevant high-authority targets for outreach.  

Why use a backlink monitor tool?

Manual tracking can’t keep up. The average site gains and loses dozens of links each month, and Search Console won’t catch a toxic link spike or a competitor pulling ahead. A monitoring tool automatically runs alerts for new links, lost-link notifications, toxic scoring, and trend data.  

Conclusion

Your link profile is one of the strongest signals Google uses to rank your site, making picking the right backlink tool an important decision for your business. 

The 14 options above cover virtually every budget and use case, so the right one for you is the one that fits the work you actually do and teaches you how to build backlinks correctly. Pick the tool that matches your goals, then commit to using it regularly. 

A tool you check once is wasted money. A tool you check weekly drives real results. 

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Foodblogger Q&A: Google updates, AI search, and what actually matters for your blog in 2026

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Foodblogger Q&A: Google updates, AI search, and what actually matters for your blog in 2026



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Search is changing fast – and if you’re a food blogger trying to keep up with Google updates, AI Overviews, and what actually moves the needle for your site in 2026, this Q&A is for you. On June 17, we’re sitting down live with Carolyn Shelby, SEO expert at Yoast, to break down the latest Google updates and what the rise of AI-driven search means for your content strategy. Bring your biggest SEO questions and get answers straight from one of the most knowledgeable people in the space – register now to save your spot.

Carolyn helps shape SEO strategy for millions of WordPress users around the world. With over 20 years of experience in technical SEO, site architecture, and digital growth, she’s known for translating complex SEO concepts into actionable strategies that actually make a difference – especially for creators who want to grow sustainable, long-term traffic.

P.S. Can’t attend the Q&A live? Register anyway and we’ll send you the replay!

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Cloudflare and beehiiv give publishers new AI crawler controls

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AI beehive crawlers

Cloudflare and beehiiv added AI crawl controls to beehiiv’s platform. This gives newsletter publishers a way to see, allow, or block AI bots from their dashboard as AI search becomes a new discovery path for web content.

The integration, announced Tuesday, embeds Cloudflare’s Crawl Control technology into beehiiv. It lets publishers manage how AI search engines and agents access their content, either by allowing crawlers for broader discovery or blocking scraping to protect archives for future licensing and monetization.

AI bot data comes to the dashboard. beehiiv publishers will get an on-platform dashboard showing which AI crawlers tried to access their content, which were blocked, and how much referral traffic those crawlers sent back. The dashboard gives publishers a side-by-side view of crawler activity, blocking decisions and referral traffic from AI services.

Publishers get simpler controls. The companies said publishers will be able to allow or block specific AI models with one-click permissions. Cloudflare will also update the system as new AI crawlers appear, reducing the need for publishers to manage robots.txt files, firewalls, or code changes themselves.

What they’re saying. Cloudflare CEO Matthew Prince said the partnership gives newsletter operators “transparency and control” as the internet changes; beehiiv CEO Tyler Denk said publishers need “real leverage” as AI changes how people find and consume content. From Cloudflare’s announcement:

  • “As AI models evolve to offer new forms of search and discovery, independent creators are looking for flexible ways to understand and manage how their content is accessed. This integration simplifies the process by letting beehiiv users manage their digital footprint through two clear choices: publishers can either opt-in to maximum discovery to allow AI search engines and agents to crawl their work freely for broader distribution, or choose content protection, blocking AI scraping to preserve their archives for future monetization and licensing opportunities.”

Why we care. The key question is whether publishers will actually use these controls once they are available. AI crawling has outpaced many creators’ ability to manage it, and adoption will show whether simple dashboard controls are enough to change publisher behavior.

Rollout starts now. The new controls are rolling out through beehiiv’s standard dashboard settings. All beehiiv users will get beta access to AI Crawl Control for visibility into AI crawler activity and traffic. beehiiv Max customers will also be able to block AI crawlers.

The announcement. Cloudflare and beehiiv Introduce AI Crawl Controls to Help Independent Publishers Navigate the AI Era

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Shopify launches AI-powered marketing automation tool

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Shopify is introducing Campaign Autopilot, a new AI-powered marketing tool that automatically creates, manages and optimizes campaigns across multiple channels, reducing the need for merchants to manually manage advertising and email marketing.

The feature is launching in early access and is available directly within the Shopify admin.

What’s happening. Campaign Autopilot uses AI to plan and run marketing campaigns on behalf of merchants across channels including Meta, Shop Campaigns and email.

Additional channels are already on the roadmap, including ChatGPT Ads, Microsoft Advertising and Snapchat.

Rather than requiring merchants to build campaigns manually, the system handles campaign creation, budget allocation and ongoing optimization automatically.

Why we care. Campaign Autopilot lowers the barrier to running multi-channel marketing campaigns by automating much of the work traditionally handled by agencies or in-house specialists. Instead of managing separate campaigns across Meta, email and other channels, merchants can set a budget and goals while Shopify handles campaign creation, optimization and budget allocation.

How it works. Merchants set a monthly budget, choose which channels to connect and define approval rules and guardrails.

From there, Campaign Autopilot:

  • Creates and launches campaigns.
  • Allocates budget across channels.
  • Adjusts spending based on performance.
  • Recommends email automations.
  • Monitors results and makes ongoing optimizations.

Merchants can approve campaigns before launch, modify budgets or pause activity at any time.

What’s different. Shopify is positioning Campaign Autopilot as an alternative to traditional campaign management tools and agency-led marketing.

The company says the system leverages performance data and patterns across millions of Shopify stores to inform recommendations and budget decisions.

Campaign Autopilot also operates separately from existing campaigns, meaning merchants already running Meta or Shop ads won’t see those campaigns altered.

The bigger picture. Shopify is increasingly embedding AI into merchant workflows, moving beyond ecommerce infrastructure and into growth and customer acquisition.

The launch reflects a broader industry trend toward autonomous marketing systems that can execute campaigns with limited human involvement while continuously optimizing performance.

What to watch. Shopify plans to expand channel support in the coming months, including integrations with ChatGPT Ads, Microsoft Advertising and Snapchat.

The company also says merchants can use its AI assistant, Sidekick, to review recommendations, trigger actions and monitor campaign performance.

Dig deeper. Introducing Campaign Autopilot: AI-powered Marketing Built into Shopify

First spotted. The update was spotted by Digital Marketing Consultant Susan Richards-Benson who suggested this feature for smaller ecommerce brands on Linkedin.

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Straight from the source: 2026 Search Engine Land Awards judges reveal what makes an application award-worthy

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search engine land awards winners

Since its inception in 2015, the Search Engine Land Awards have recognized exceptional marketers on an annual basis — showcasing outstanding work, providing well-earned exposure in coverage and interviews, and bestowing upon them the highest honor in search.

While there’s no single formula for creating a winning entry, our judges have seen enough submissions over the years to know what separates the truly exceptional from the merely good. The strongest applications don’t just share results, they tell a story. They provide context, demonstrate strategic thinking, and clearly communicate why the work mattered.

And because great advice shouldn’t be gatekept, we thought we’d bring some of those insights directly to you.

We asked several of this year’s Search Engine Land Awards judges to share their best advice for prospective entrants. From common mistakes to avoid to the elements that consistently stand out, their insights offer a valuable look inside the judging process and can help you build a stronger, more compelling submission.

Keep reading for a roundup of fresh insights from some of our judges. (And see the complete list of 2026 judges here!)

“A great entry is a story with a goal, an action, and a measurable outcome that ties back to it. Tell that story as well as you can, and include a deck that makes it easy to see exactly what you accomplished.”

– Amy Hebdon, Founder, Paid Search Magic

“Explain your tactics. Many entries just say “we used best practices”. Everyone’s best practices and tactics differ. Explaining the process that lead to your results will highlight your creative thinking, problem solving, and uniqueness. Showing your insights and thought processes helps your entry standout and showcase your company’s competitive edge.”

– Brad Geddes, Co-Founder, Adalysis

Brad Geddes

“I look for SAY which stands for: Situation, Action and Yield.
Applicants should write a clear example of the situation, what they did and the result achieved over the time period,”

– Jo Juliana Turnbull, Growth Marketing Senior Manager, Holafly

“Show me the humans behind the metrics. We’re in a time where AI is reshaping search at a pace none of us have seen, and that shift matters…but the applications that rise to the top will lead with empathy, not just analytics. I want stories where I can see how your work built genuine trust with real people, not simply visibility in search and AI engines. I’m especially drawn to entries that embrace a wellness-based approach to their craft, and to teams who pair their quantitative wins with qualitative insight: the quote, the aha moment, the change in how someone felt about a brand or experience. Tell me how you held the human at the center – as strategy. If your project made people feel seen, understood, or genuinely helped, lean into that. Those are the stories I’ll be looking for.”

– Danita Smith, Founder & CEO/Chief Innovation Strategist, Adanis Design

“Clearly state the challenge you solved, and back it up with data. Explain the strategy behind the tactics you used and the results they drove. Tell me not just what happened, but what impact did it have on your campaigns? What did you do differently as a result?”

– Melissa Mackey, Director of Paid Search, Compound Growth Marketing

“Evidence: charts, analytics, screenshots. Be detailed, specific, and share data.”

– Barry Schwartz, Editor, Search Engine Land

“Tell a story. Numbers get you in the room, but the story is what stays with the judges. I want to know what the problem was, why it was hard, what you tried, and what finally worked. That arc, the messiness of real work, is what separates a memorable entry from a forgettable one. The submissions that stick with me are the ones where I can feel the thinking behind the decisions, not just the outcome. You did great work this year; now, make the judges feel the weight of what you solved before you show them the numbers.”

– Ameet Khabra, Founder, Hop Skip Media

“The two main things all award-winning entries share are that they explain the whys behind the hows, and they bring receipts (data to back up claims). If you can’t share the data behind your entry (budgets, revenue, etc.), you are putting yourself at a distinct disadvantage and may end up wasting the entry fee. A lot of people submit the same practices – if you can distinguish yourself by showing innovative thinking, you’ll do well!”

– Navah Hopkins, Product Liaison, Microsoft

“Give me all the data you can. Show the numbers and the real impact of whatever you did; conversions, ROI, and whatever monetary increases you were able to cause.”

– Celeste Gonzalez, Content Implementation and Product Specialist, Lastmile Retail

“Show me something I haven’t seen before, then prove it worked. The applications that land are the ones with a genuinely unexpected approach backed by numbers that make the result undeniable.”

– Adam Tanguay, Head of Growth, Jordan Digital Marketing

“I am looking for an approach or strategy that challenges the norm of SEM. A unique approach that focuses on achieving the business goals by way of campaign structure across Brand, Non-Brand, Performance Max, Conquesting, and general upper-funnel tactics. An advanced way of thinking about the target audience, messaging, conversion goals, etc. that helps show a sophisticated way of managing the campaigns & overall strategy to exceed business goals.”

– Matt Devinney, Director, Client Partner, Tinuiti

“I am looking for projects that break new ground with innovative takes on SEO, and are backed up by data and numbers-driven insights every step of the way.”

– Olya Ianovskaia, Founder and Lead Consultant, MycoMinds SEO

“Make your entry easily readable. We are going to need to go through several entries – I know the entries could be quite technical (and the quality of that will take precedent), but I am more likely to vote for you if I enjoyed reading your entry.”

– Anu Adegbola, Paid Media Editor, Search Engine Land

“My #1 piece of advice is to showcase strategy that truly breaks new ground. Award-winning applications demonstrate innovation that anticipates where SEM is heading, whether that’s leveraging AI in novel ways, pioneering audience-targeting approaches, or developing unique cross-channel integration. But innovation alone isn’t enough. The most compelling entries connect these forward-thinking strategies directly to measurable business outcomes, providing clear evidence of how your work translated to client growth metrics that matter. We’re looking for that perfect balance: creative execution that pushes boundaries while delivering documented ROI that proves your approach wasn’t just innovative—it was transformative.”

– Joseph Kerschbaum, Senior Vice President, Search & Growth Labs, DEPT

And there you have it! Submit your entry today to be considered by this year’s esteemed judges. Early Bird rates expire July 10… so get a move on!

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YouTube rolls out new Gemini-powered insights tools

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YouTube is expanding its suite of creator marketing and campaign intelligence tools with new Gemini-powered features designed to help brands identify trends, understand creator audiences and improve campaign performance.

What’s happening. Google is introducing several new insights and optimization tools across YouTube and Google Ads that give marketers more visibility into trends, creator performance and audience behavior.

The company says the new capabilities are intended to help advertisers make better creative and media planning decisions in an increasingly AI-driven marketing landscape.

Why we care. These updates provide deeper visibility into what’s trending on YouTube, which creators are resonating with audiences, and how their brand is performing across both paid and organic content. That can help marketers make smarter decisions about creator partnerships, campaign planning and creative strategy.

What’s new:

More detailed trend insights.

Google Ads’ Insights Finder is gaining expanded trending insights in the U.S., providing advertisers with a more granular view of what’s gaining traction on YouTube.

Brand Pulse data comes to Insights Finder.

Select Brand Pulse metrics are now being integrated into Insights Finder, allowing brands to evaluate both their paid and organic presence in a single location.

New creator insights API.

The new Content & Creator Insights API gives agencies and partners deeper information about YouTube creators and their audiences, helping improve media planning and creator selection.

Gemini-powered creative recommendations.

Google says Gemini will soon provide creative optimization tips for Demand Gen campaigns, including recommendations on visuals and creative elements that may improve performance.

The bigger picture. As creator-led content becomes increasingly influential in purchase decisions and brand discovery, advertisers are looking for better ways to identify emerging trends and measure creator impact.

Google is betting that AI can help marketers surface those insights faster and make campaign planning more efficient.

Bottom line. YouTube is giving brands and agencies more data on trends, creators and campaign performance, while using Gemini to help turn those insights into stronger creative and media decisions.

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How to approach build-versus-buy decisions for SEO

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How to approach build-versus-buy decisions for SEO

AI has made SEO teams ambitious about what they can automate. Tasks that previously required engineering support can now be solved with the help of Claude or ChatGPT.

That’s exciting, but it also creates a new problem: thinking you can automate everything. In modern language, that often comes down to one question: Should we build or buy this new tool?

This build-versus-buy dilemma has never been simple, and AI has made it even more complicated. The challenge goes beyond cost. It involves security, maintenance, data access, internal capabilities, workflow fit, and whether a custom solution will remain maintainable, reliable, and useful six months from now.

How AI lowers the barrier to building

AI has lowered the barrier to experimentation. Even without technical knowledge, you can now create a custom GPT, build a workflow, connect data sources, or create an internal AI assistant.

But that doesn’t mean the same person can build and maintain a tool that will remain reliable over the next few years.

In most cases, AI can help SEO teams analyze data, identify patterns, summarize information, and recommend actions. It can save a lot of time, and teams that ignore AI are clearly falling behind.

But, at least for now, AI isn’t doing truly creative work in the same way humans do. It works from existing patterns and predicts likely outputs. That may change in the future.

AI also comes with hidden costs. Internally built tools are often treated as free because the invoice usually doesn’t sit with the SEO team. But that doesn’t mean token usage, API calls, infrastructure, engineering time, security reviews, and maintenance don’t cost money.

We are already seeing this effect. Reuters has described it as “corporate AI sticker shock,” with companies struggling to forecast usage-based AI costs. TechCrunch also reported that Uber introduced AI spending caps after blowing through its annual AI budget in four months.

Today, marketing teams aren’t the heaviest AI users, especially compared with engineering teams. But that can change quickly.

And when usage grows, the bills will grow too. That will naturally make companies ask which AI tools and AI-powered workflows create value and which ones only consume budget.

Be the brand AI recommends.

See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.

See your AI visibility

Start by defining what you need

Before deciding whether to build or buy, SEO teams need to define what they really need.

Different ways to use AI and automation

Many teams group these solutions together, but they vary significantly in cost, complexity, and maintenance requirements.

  • A custom tool: A more complex internal system that usually needs engineering support. It is often more about automation, but it can have an artificial intelligence aspect.
  • A custom workflow: A repeatable process built with different tools, such as a custom GPT, Claude project, spreadsheet, reporting template, and so on. It often includes automation, for example, a scheduled task in an AI tool, and it usually has an artificial intelligence layer.
  • A custom layer on top of SaaS: Using data from existing tools and shaping it into your own reporting, prioritization, or recommendation workflow.
  • A true AI agent: A system that can take more autonomous actions. For example, it can scan your Slack and follow up with people you are still waiting on.

These aren’t the same, but people often label them incorrectly. Calling everything an “AI agent” creates confusion and can lead to wrong estimates about cost and complexity.

Look for repetitive, context-rich tasks

We’re still experimenting. Most of what our team has built focuses on daily tasks that require a lot of manual work.

For example, we’ve created a custom GPT that evaluates whether our content matches our personas and their pain points. The goal is not to replace the human copywriter or reviewer. It is to determine whether a piece remains generic and whether a few additions can make it more relevant.

We are also using AI for translations, monthly reporting, and a weekly summary that combines meeting notes, Slack, and Jira, and helps me see whether I have missed adding a task to Jira or where I still need to follow up.

One of our latest workflows transforms recorded internal meetings into organized landing page briefs.

These types of tasks are good candidates for AI-powered custom workflows because they rely on internal context, repeatable processes, and company-specific knowledge.

Get the newsletter search marketers rely on.

See terms.

Not everything should be built

One example from our team was a prompt tracking tool that my colleague vibe-coded. It worked well as a starting point. But the data presentation was not perfect, and it was hard to create a trend graph without additional manual steps.

Soon, it became a maintenance burden because every external change in any of the LLM tools required fixes, for which we needed engineering help.

The real issue was reliability. For AI visibility and prompt tracking, we needed consistent data in one place, presented in a way we could analyze over time. That is why we moved to a specialized platform like Peec AI instead of continuing to maintain our own version.

That experiment was still valuable. It helped us understand the problem, the complexity, and the features we actually needed from an external vendor.

And this is one of my pieces of advice: whether you want to build a tool internally or buy one, always test what is already available on the market. Only then will you really understand what you actually need. You may think you need 10 features, only to realize you use only three.

For business-critical tools such as rank and AI visibility tracking, and website crawling, small SEO teams without dedicated technical support should usually be careful about building from scratch. If the data is fundamental to decision-making, reliability should be your main decision factor.

Use AI where your data already lives

Buy the crawler, rank tracker, or AI visibility platform. Then focus your internal efforts on connecting data from these tools to custom information, such as your GA and GSC accounts or even CRM data. Once connected, create reports that combine all these sources and enable you to analyze everything in one place.

MCP connections are also worth considering. The Model Context Protocol is an open standard for connecting AI applications to external systems, data sources, tools, and workflows. With MCP servers, you can analyze data from your primary tools directly using AI, taking your current workflows to the next level.

This doesn’t mean you’re required to learn how to code. But they need to know enough to ask the right questions.

If a tool connects to an internal knowledge base, customer data, or proprietary research, you should be aware that this could pose a security risk. And it might turn out that it is better for the company to dedicate an engineer to support you rather than risk exposing sensitive information.

You should also understand what the final cost will be for your company when you decide to go with a custom tool. Custom tools aren’t free just because the invoice doesn’t sit with SEO. Engineering time, security reviews, AI tokens, and API usage are all part of the cost.

Before asking leadership for a tool, SEO teams should be able to explain the workflow problem, the expected value, the cost of buying compared with the estimated cost of building, and what might happen if nothing is done.

The best requests don’t start with: “We need this tool.”

They start with: “Here is the problem, here is why it matters, here is what we’ve tested, and here is the best way we think we can solve it.”

How to prioritize what to build first

There’s no single prioritization matrix that will work for every situation.

A website crawler, a content evaluation tool, a report builder, or a competitive intelligence system can’t be judged by the same criteria.

If you are in a situation where you think you need more than one tool, start by mapping your current workflow and what your ideal situation looks like.

Once you do that, the patterns will be clear. Often, your strongest priorities will fall into two groups.

The first are tools that can support revenue creation. SEO teams are usually part of the marketing organization, and marketing is expected to bring visibility or leads. If a tool can help identify content opportunities, improve conversion rates, increase AI visibility, or surface gaps versus competitors, it can be seen as a priority.

The second group is workflows and tools that can help you minimize repetitive manual work. This category may not create revenue, but it will give your team time back to focus on more strategic work.

Don’t forget that quick wins also matter. Stakeholders don’t want to wait three months before seeing results. A smaller project that can bring value in three weeks will help you build trust and make it easier to get support for bigger initiatives.

Cross-team value should also be part of your decision.

SEO problems are often not just problems for your team. Competitive intelligence, for example, matters to PPC, ABM, content, product marketing, and sales, too. If several teams share the same pain, the business case becomes stronger.

So don’t be afraid to act as a cross-team synchronization layer when needed. Talk to the same teams you have already worked with, and try to understand their workflows and pain points, and where your needs overlap.

And remember, the best tool is not always the most ambitious one. Starting with something small is often the smartest move.

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Good decisions start with proper scoping

AI has made it easier to build, but that doesn’t mean you don’t need to think about what really needs to be built.

Before deciding whether to build, buy, or customize, take the time to properly scope the work.

  • Understand the problem, the value you expect, who will use the solution, and who will maintain it after launch.
  • Talk to your team and other teams. Determine whether this is only an SEO problem or a wider business problem.
  • Don’t build because AI makes it possible. Don’t buy because a demo looks impressive.

Without proper scoping, you can end up with an expensive SaaS tool that doesn’t fit your workflow or an internal tool your team can’t maintain.

Always think first. Dedicate enough time to scope properly. Then decide whether to build, buy, or customize.

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Google Search Console AI performance reports rolling out to more users

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Google has confirmed that it has expanded access to the new Google Search Console AI performance reports to more users. Google’s John Mueller wrote on Bluesky, “We’re just rolling these out incrementally to sites, and reviewing the feedback along the way. I know everyone wants the new shiny thing immediately… but first, patience.”

AI performance report. The report shows you how well your content and websites are performing in AI responses, AI Mode, and AI Overviews in Google Search. The reporting includes impressions, pages, countries, devices, and dates, but does not include click data. 

Expanding access. This morning, I spotted a number of SEOs posting that they are now seeing the report, and that it is not restricted to sites in the United Kingdom. Some are seeing the report for sites in the United States, India, Switzerland and so forth.

And as I quoted above, John Mueller from Google confirmed the search company is “rolling these out incrementally to sites.”

What it looks like. Here is a screenshot of this report:

Why we care. Site owners and publishers have been asking for controls over whether and how their content is shown in Google’s AI features since Google launched these a couple of years ago. Well, Google is rolling out this feature to more of its users today. It is unclear how soon everyone will gain access to these controls, but I am surprised that Google expanded access this quickly. Specifically within 20 days from its first release.

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Why some channels reward breadth and others require commitment

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Why some channels reward breadth and others require commitment

Many budget allocation strategies assume that every channel follows the same pattern: the first dollar is the most productive, and each additional dollar yields a slightly lower return.

The charts below show what that pattern looks like.

The log shape means that the first dollar is the most productive, and each subsequent dollar is worth a little less. When every channel looks like that, the game plan is to spread the budget to as many channels as possible and equalize the marginal CPAs to maximize profit.

But not every channel looks like that. Some have a warm-up region where the early spend is the least efficient, not the most. On those channels, the logic above breaks, and so does the “test small, scale the winners” playbook that most of the industry runs on autopilot. 

The difference comes down to one question about the channel: Is the response curve C-shaped or S-shaped?

The answer can change how you approach channel testing and channel measurement, including any MMM analysis. Moreover, Google has been incorporating more S-shaped campaign types, and after its Google Marketing Live announcements, this trend seems set to continue.

The two shapes — and the only part that matters

The response curve plots output (conversions, revenue) against input (spend). This generally results in two types of curves in marketing.

  • C-shaped (concave): Diminishing returns from the very first dollar. A log or power curve. Picture the top-left quarter of a circle: steep at the start, flattening as you go.
  • S-shaped (sigmoid): A slow, inefficient start, then an inflection point where it gets steep, followed by a flattening into saturation. A logistic curve.

The response curve itself isn’t what you allocate against. You allocate against the marginal curve, the derivative, which answers the question: “What did the next dollar buy me?” That’s where the shapes diverge in a way that matters.

  • For a C-curve, marginal return is highest at the first dollar and falls in only one direction. Marginal CPA rises from the first dollar onward. If conversions are a*ln(s), marginal conversions per dollar are a/s, so marginal CPA is s/a, climbing in a straight line as you scale. There’s no warm-up. The cheapest conversion you’ll ever buy is the first one.
  • For an S-curve, marginal return starts low, rises to a peak at the inflection point, then falls. Marginal CPA is U-shaped. It’s expensive at the start, bottoms out around the inflection point, then climbs into saturation.

That region of increasing marginal returns is the whole story. It’s the difference between a channel where small budgets are productive and one where they are wasted.

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How this looks in a marketing campaign

Say your CPA goal is $50. Here is an S-shaped channel, modeled as Conversions = 1000 / (1 + e^(-0.25(s – 20))), with spend in the thousands and the inflection at $20,000/month:

Run the $10,000 test that a sane person runs before committing real budget. Average CPA comes back at $132, marginal around $94. If those two metrics are all you look at, you conclude that this channel can’t hit $50, so let’s kill it.

That verdict is wrong. At $20,000 to $25,000, the channel is running at an average of $32 to $40, and the marginal dollar in the $15,000 to $25,000 band costs $18. That’s not “barely viable.” In that band, it’s the best marginal buy you have. The small test fell within the warm-up and reversed the conclusion.

In a C-shaped channel, the small test would have shown you the best the channel can do. On an S-shaped channel, it shows you the worst.

This is the trap. The standard playbook is “test small, scale what works.” On S-curves, small tests systematically condemn channels that would’ve worked at scale because the test is structurally stuck in the inefficient region.

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The allocation logic, restated

C-shaped channels, go wide

The optimization is convex. There’s one global optimum, the equimarginal rule from the marginal-CPA post applies cleanly, and the solution is usually interior, meaning lots of channels get funded.

Even a small allocation is productive because the first dollar is the best dollar. Run many channels lean, reallocate continuously at the margin, and pull back the instant marginal CPA crosses your goal.

S-shaped channels, go deep or skip

The optimization is non-convex. A small allocation can be strictly worse than zero because below the inflection your marginal return sits under your target, and you’ve sunk money to get nowhere.

The decision isn’t “how much.” It is binary: commit past the threshold, or don’t fund it at all. There’s a real minimum viable budget, and it’s often above normal test budgets. You can’t sprinkle an S-curve and expect efficiency, and you can’t evaluate one on an underfunded test.

Those two rules can look like they fight each other, but that’s only true to a certain point. Past the inflection, an S-curve is concave, so the equimarginal rule governs it exactly as it governs a true C. The S-specific instruction — commit a block instead of sprinkling — is only about the trip from zero to past the inflection.

Shape is therefore mostly a launch-and-evaluation problem. Getting a new prospecting channel into its efficient range requires a committed block and patience with ugly early numbers. Once it clears the inflection, you manage it at the margin like everything else, right up until you consider cutting it hard, where shape matters again because the downside is a cliff, not a ramp.

This is the part that’s genuinely counterintuitive, and it echoes the original marginal-return point: The right move isn’t always the one that looks most efficient at a small scale.

Which channels are which?

The historical default was concave. Simon and Arndt reviewed more than 100 studies and concluded that advertising follows the law of diminishing returns, a concave response. 

The dissent came later: Vakratsas, Feinberg, Bass, and Kalyanaram found that threshold effects do exist and that response is not necessarily globally concave. Their explanation for why thresholds were so hard to find is the useful part. Mature accounts already operate inside the effective range, so the warm-up never shows up in the data, and most studies fit a concave model (the double-log) that can’t reject an S-curve even when one is present.

The platform shift has made the threshold visible again. Here is a fuller map, ordered roughly from C to S. The shape column is an inference from how each system targets and learns, not a measured constant, and the right shape for your account still has to be measured.

Two rows do most of the work.

AI Max is the live example of a channel migrating from C toward S. Swapping explicit keywords for broad and keywordless matching means it needs conversion volume to learn which queries convert, so below a data threshold, it explores badly.

The mixed independent results fit that: Google reports about 14% more conversions on average and up to 27% for exact-match-heavy campaigns, while independent testing reports 84% of advertisers seeing neutral or negative results. Much of that spread is accounts that turned it on without the conversion volume to clear the learning region.

Performance Max is the trap, because its curve is a composite. It blends a harvesting layer (branded, retargeting, Shopping against existing intent) with a prospecting layer (keywordless expansion across surfaces). The harvesting layer is a cheap C that pays off on the first dollar. The prospecting layer is the S underneath.

Blended, the early efficiency looks great, because you are mostly skimming demand you already had, and the average hides the prospecting warm-up entirely. That is also why the platform is glad to optimize it for you: the blend flatters the headline number. You can’t read PMax or run the shape analysis on it until you split the harvesting from the prospecting.

The throughline runs in two layers. Rules-based auctions capture the best inventory first, which yields concavity; machine-learning systems must be fed before they are efficient, which introduces a threshold. Underneath both, harvesting existing demand is concave and mostly non-incremental, while creating new demand is the S-shaped part where the real growth and the real warm-up cost both sit.

Average versus marginal: total over spend, or the slope where you stand.

What you allocate against is marginal incremental return, the slope of the incremental curve at your operating point. A holdout fixes the first axis only. Time-sliced marginal CPA on attributed data fixes the second only. A multi-cell scaling test gets both, at a cost. 

MMM (method 1) estimates the whole curve from aggregate data and sidesteps click attribution entirely, but pays in identifiability and modeling assumptions instead. Most arguments about ‘what is working’ are two people standing on different axes.

There are two major cautions, and I would flag both as genuinely unsettled rather than settled facts. 

  • Separating a true S-curve from “concave with a high half-saturation point” is hard, because a concave model will fit S-shaped data well enough to hide the inflection (this is the Vakratsas point, and it applies to your own dashboards as much as to academic studies). 
  • The learning phase may be a one-time fixed cost to train the model rather than a permanent feature of the steady-state curve. If it is transient, the channel may behave concavely at the margin once it is trained, and the S you measured was a startup artifact. The truth is probably a mix: a one-time training cost, plus an ongoing minimum-volume requirement to stay efficient. Treat every shape call as provisional and re-check it.

One more failure mode, and this one is not unsettled science but a matter of where you are standing on the curve. An S only looks like an S if your data spans the inflection. 

Above the inflection, an S is concave, mathematically identical to a C. Look at only the $20,000-and-up rows of the table above: marginal CPA rises monotonically from $18, a textbook C-curve, and the convex warm-up is invisible because you are no longer operating in it. 

Established accounts usually sit past the inflection, which is exactly why Vakratsas found thresholds so hard to detect, and why you can run an S-shaped channel for years, correctly, while believing it is concave. The tell arrives the day you cut hard and fall off the inflection instead of easing down a slope.

When to go wide and when to go deep

The marginal-return post told you to equalize marginal CPAs across the program. That rule is still correct, but the shape of the curve tells you how you’re allowed to get there. 

  • On C-shaped channels, you can get there by sprinkling, because every dollar is productive and breadth is the natural answer. 
  • On S-shaped channels, you have to commit a block of budget past the inflection before the channel earns its place, and then concentrate rather than spread.

Lay the harvest-versus-create cut on top. Harvesting channels (branded, retargeting, non-brand search) are your C-curves: fund the first dollars, then cap them early, because they saturate fast and most of the tail isn’t incremental, no matter how strong the attributed ROAS looks. 

Prospecting channels (Meta, YouTube, LinkedIn, the expansion half of PMax) are your S-curves and your only real source of incremental growth: commit past the warm-up or don’t start, and judge them on incremental lift rather than attributed CPA, or you’ll kill the thing that was working.

Classic search rewards going wide. PMax, AI Max, and Meta prospecting reward going deep on fewer bets and giving each enough volume to clear the warm-up. Run an S-curve like a C-curve and you’ll starve it, read the underfunded result, and kill a channel that would’ve been one of your best.

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