Dec 4 2025
Google AI Overviews: How To Measure Impressions & Track Visibility

AIO Is Reshaping Click Distribution On SERPs

AI Overviews change how clicks flow through search results. Position 1 organic results that previously captured 30-35% CTR might see rates drop to 15-20% when an AI Overview appears above them.

Industry observations indicate that AI Overviews appear 60-80% of the time for certain query types. For these keywords, traditional CTR models and traffic projections become meaningless. The entire click distribution curve shifts, but we lack the data to model it accurately.

Brands And Agencies Need To Know: How Often AIO Appears For Their Keywords

Knowing how often AI Overviews appear for your keywords can help guide your strategic planning.

Without this data, teams may optimize aimlessly, possibly focusing resources on keywords dominated by AI Overviews or missing chances where traditional SEO can perform better.

Check For Citations As A Metric

Being cited can enhance brand authority even without direct clicks, as people view your domain as a trusted source by Google.

Many domains with average traditional rankings lead in AI Overview citations. However, without citation data, sites may struggle to understand what they’re doing well.

How CTR Shifts When AIO Is Present

The impact on click-through rate can vary depending on the type of query and the format of the AI Overview.

To accurately model CTR, it’s helpful to understand:

  • Whether an AI Overview is present or not for each query.
  • The format of the overview (such as expanded, collapsed, or with sources).
  • Your citation status within the overview.

Unfortunately, Search Console doesn’t provide any of these data points.

Without Visibility, Client Reporting And Strategy Are Based On Guesswork

Currently, reporting relies on assumptions and observed correlations rather than direct measurements. Teams make educated guesses about the impact of AI Overview based on changes in CTR, but they can’t definitively prove cause and effect.

Without solid data, every choice we make is somewhat of a guess, and we miss out on the confidence that clear data can provide.

How To Build Your Own AIO Impressions Dashboard

One Approach: Manual SERP Checking

Since Google Search Console won’t show you AI Overview data, you’ll need to collect it yourself. The most straightforward approach is manual checking. Yes, literally searching each keyword and documenting what you see.

This method requires no technical skills or API access. Anyone with a spreadsheet and a browser can do it. But that accessibility comes with significant time investment and limitations. You’re becoming a human web scraper, manually recording data that should be available through GSC.

Here’s exactly how to track AI Overviews manually:

Step 1: Set Up Your Tracking Infrastructure

  • Create a Google Sheet with columns for: Keyword, Date Checked, Location, Device Type, AI Overview Present (Y/N), AI Overview Expanded (Y/N), Your Site Cited (Y/N), Competitor Citations (list), Screenshot URL.
  • Build a second sheet for historical tracking with the same columns plus Week Number.
  • Create a third sheet for CTR correlation using GSC data exports.

Step 2: Configure Your Browser For Consistent Results

  • Open Chrome in incognito mode.
  • Install a VPN if tracking multiple locations (you’ll need to clear cookies and switch locations between each check).
  • Set up a screenshot tool that captures full page length.
  • Disable any ad blockers or extensions that might alter SERP display.

Step 3: Execute Weekly Checks (Budget 2-3 Minutes Per Keyword)

  • Search your keyword in incognito.
  • Wait for the page to fully load (AI Overviews sometimes load one to two seconds after initial results).
  • Check if AI Overview appears – note that some are collapsed by default.
  • If collapsed, click Show more to expand.
  • Count and document all cited sources.
  • Take a full-page screenshot.
  • Upload a screenshot to cloud storage and add a link to the spreadsheet.
  • Clear all cookies and cache before the next search.

Step 4: Handle Location-specific Searches

  • Close all browser windows.
  • Connect to VPN for target location.
  • Verify IP location using whatismyipaddress.com.
  • Open a new incognito window.
  • Add “&gl=us&hl=en” parameters (adjust country/language codes as needed).
  • Repeat Step 3 for each keyword.
  • Disconnect VPN and repeat for the next location.

Step 5: Process And Analyze Your Data

  • Export last week’s GSC data (wait two to three days for data to be complete).
  • Match keywords between your tracking sheet and GSC export using VLOOKUP.
  • Calculate AI Overview presence rate: COUNT(IF(D:D=”Y”))/COUNTA(D:D)
  • Calculate citation rate: COUNT(IF(F:F=”Y”))/COUNT(IF(D:D=”Y”))
  • Compare the average CTR for keywords with vs. without AI Overviews.
  • Create pivot tables to identify patterns by keyword category.

Step 6: Maintain Data Quality

  • Re-check 10% of keywords to verify consistency.
  • Document any SERP layout changes that might affect tracking.
  • Archive screenshots weekly (they’ll eat up storage quickly).
  • Update your VPN locations if Google starts detecting and blocking them.

For 100 keywords across three locations, this process takes approximately 15 hours per week.

The Easy Way: Pull This Data With An API

If ~15 hours a week of manual SERP checks isn’t realistic, automate it. An API call gives you the same AIO signal in seconds, on a schedule, and without human error. The tradeoff is a little setup and usage costs, but once you’re tracking ~50+ keywords, automation is cheaper than people.

Here’s the flow:

Step 1: Set Up Your API Access

  • Sign up for SerpApi (free tier includes 250 searches/month).
  • Get your API key from the dashboard and store it securely (env var, not in screenshots).
  • Install the client library for your preferred language.

Step 2, Easy Version: Verify It Works (No Code)

Paste this into your browser to pull only the AI Overview for a test query:

https://serpapi.com/search.json?engine=google&q=best+laptop+2026&location=United+States&json_restrictor=ai_overview&api_key=YOUR_API_KEY

If Google returns a page_token instead of the full text, run this second request:

https://serpapi.com/search.json?engine=google_ai_overview&page_token=PAGE_TOKEN&api_key=YOUR_API_KEY
  • Replace YOUR_API_KEY with your key.
  • Replace PAGE_TOKEN with the value from the first response.
  • Replace spaces in queries and locations with +.

Step 2, Low-Code Version

If you don’t want to write code, you can call this from Google Sheets (see the tutorial), Make, or n8n and log three fields per keyword: AIO present (true/false), AIO position, and AIO sources.

No matter which option you choose, the:

  • Total setup time: two to three hours.
  • Ongoing time: five minutes weekly to review results.

What Data Becomes Available

The API returns comprehensive AI Overview data that GSC doesn’t provide:

  • Presence detection: Boolean flag for AI Overview appearance.
  • Content extraction: Full AI-generated text.
  • Citation tracking: All source URLs with titles and snippets.
  • Positioning data: Where the AI Overview appears on page.
  • Interactive elements: Follow-up questions and expandable sections.

This structured data integrates directly into existing SEO workflows. Export to Google Sheets for quick analysis, push to BigQuery for historical tracking, or feed into dashboard tools for client reporting.

Demo Tool: Building An AIO Reporting Tool

Understanding The Data Pipeline

Whether you build your own tracker or use existing tools, the data pipeline follows this pattern:

  • Input: Your keyword list (from GSC, rank trackers, or keyword research).
  • Collection: Retrieve SERP data (manually or via API).
  • Processing: Extract AI Overview information.
  • Storage: Save to database or spreadsheet.
  • Analysis: Calculate metrics and identify patterns.

Let’s walk through implementing this pipeline.

You Need: Your Keyword List

Start with a prioritized keyword set.

Include categorization to identify AI Overview patterns by intent type. Informational queries typically show higher AI Overview rates than navigational ones.

Step 1: Call SerpApi To Detect AIO blocks

For manual tracking, you’d check each SERP:

  • Individually. (This tutorial takes 2 – 3 minutes per manual check.)
  • Instantly. (This returns structured data instantly.)

Step 2: Store Results In Sheets, BigQuery, Or A Database

View the full tutorial for:

Step 3: Report On KPIs

Calculate the following key metrics from your collected data:

  • AI Overview Presence Rate.
  • Citation Success Rate.
  • CTR Impact Analysis.

Combine with GSC data to measure CTR differences between keywords with and without AI Overviews.

These metrics provide the visibility GSC lacks, enabling data-driven optimization decisions.

Clear, transparent ROI reporting for clients

With AI Overview tracking data, you can provide clients with concrete answers about their search performance.

Instead of vague statements, you can present specific metrics, such as: “AI Overviews appear for 47% of your tracked keywords, with your citation rate at 23% compared to your main competitor’s 31%.”

This transparency transforms client relationships. When they ask why impressions increased 40% but clicks only grew 5%, you can show them exactly how many queries now trigger AI Overviews above their organic listings.

More importantly, this data justifies strategic pivots and budget allocations. If AI Overviews dominate your client’s industry, you can make the case for content optimization targeting AI citation.

Early Detection Of AIO Volatility In Your Industry

Google’s AI Overview rollout is uneven, occurring in waves that test different industries and query types at different times.

Without proper tracking, you might not notice these updates for weeks or months, missing crucial optimization opportunities while competitors adapt.

Continuous monitoring of AI Overviews transforms you into an early warning system for your clients or organization.

Data-backed Strategy To Optimize For AIO Citations

By carefully tracking your content, you’ll quickly notice patterns, such as content types that consistently earn citations.

The data also reveals competitive advantages. For example, traditional ranking factors don’t always predict whether a page will be cited in an AI Overview. Sometimes, the fifth-ranked page gets consistently cited, while the top result is overlooked.

Additionally, tracking helps you understand how citations relate to your business metrics. You might find that being cited in AI Overviews improves your brand visibility and direct traffic over time, even if those citations don’t result in immediate clicks.

Stop Waiting For GSC To Provide Visibility – It May Never Arrive

Google has shown no indication of adding AI Overview filtering to Search Console. The API roadmap doesn’t mention it. Waiting for official support means flying blind indefinitely.

Start Testing SerpApi’s Google AI Overview API Today

If manual tracking isn’t sustainable, we offer a free tier with 250 searches/month so you can validate your pipeline. For scale, our published caps are clear: 20% of plan volume per hour on plans under 1M/month, and 100,000 + 1% of plan volume per hour on plans ≥1M/month.

We also support enterprise plans up to 100M searches/month. Same production infrastructure, no setup.

Build Your Own AIO Analytics Dashboard And Give Your Team Or Clients The Insights They Need

Whether you choose manual tracking, build your own scraping solution, or use an existing API, the important thing is to start measuring. Every day without AI Overview visibility is a day of missed optimization opportunities.

The tools and methods exist. The patterns are identifiable. You just need to implement tracking that fills the gap Google won’t address.

Get started here →

For those interested in the automated approach, access SerpApi’s documentation and test the playground to see what data becomes available. For manual trackers, download our spreadsheet template to begin tracking immediately.

Ecommerce MGMT 0 Comments
Nov 18 2025
From Listings to Loyalty: The New Role of Local Search in Customer Experience

Ask yourself the following:

  • Do you reply to reviews?
  • Do you engage?
  • Do you make the interaction feel personal?
  • Do you follow through on your promises?
  • Do you keep information consistent across every platform?
  • Do you share fresh updates (ex: photos, posts, or promotions) that show you’re active?
  • Do you provide transparent details like pricing, wait times, or insurance accepted?

If you answered no to any of the aforementioned, it’s time to switch to a brand experience mentality. That shift shows up clearly in the data. Six in ten people say they at least sometimes click on Google’s AI-generated overviews, which means discovery is no longer only about traditional rankings. It’s about whether your brand shows up well when search engines pull together information in context.

Reputation follows the same logic. In Rio SEO’s latest study, three out of four consumers said they read at least four reviews before deciding where to go. And it’s not just the rating itself. Many put just as much weight on whether a business responds; silence feels like neglect, while engagement signals you’re listening.

The clock has also sped up. Nearly six in ten customers now expect a reply within 24 hours, a sharp jump from last year. For many, that means a same-day response is the expectation. Fast, human replies aren’t a nice touch anymore; they’re the baseline.

The major search platforms reinforce this reality. Google’s local pack favors businesses that post fresh photos, keep details up to date, and engage with reviews (and not just negative reviews but positive ones too). Apple Maps is becoming harder to ignore as well, Rio SEO’s research reveals about a third of consumers now use it frequently. With Siri, Safari, and iPhones all pulling from Apple Business Connect as the default, accurate profiles there can tip the balance just as much as on Google.

Put it all together, and the picture is clear: search visibility and customer experience are already intertwined. The brands thriving in 2025 treat local search as part of a unified Brand Experience strategy and Rio SEO helps brands stay visible, responsive, and trusted wherever customers are searching.

The BX Advantage: Connecting Signals to Action

Every brand gathers signals. Search clicks, review scores, survey feedback; it all piles up. The trouble is most of it never makes it past a slide deck. Customers don’t feel or see the difference.

That’s where Brand Experience (BX) comes in. BX connects visibility and reputation with actionable insights, so signals don’t just sit in a dashboard.

At Rio SEO, we put BX into motion. Our Local Experience solutions help brands connect discovery with delivery and turn what customers see in search into what they feel in real life. It’s the bridge between data and experience, helping enterprise marketers identify patterns, respond faster, and build trust at every location.

The goal isn’t to watch the numbers. It’s to quickly identify and make changes customers notice, such as faster check-ins, smoother booking, and clearer answers in search; all of which amount to better experiences and outcomes, for customers and employees alike.

Technology helps make this possible. AI platforms now tie search data, reviews, and feedback into one view. With predictive analytics layered in, teams can see trouble before it shows up at the front desk or checkout line. And with Google’s AI Overviews and Bing’s Copilot changing how people discover businesses, brands that prepare for those formats now will have an edge when others are still catching up.

Industry context shapes how this plays out. A retailer might connect “near me” searches to what’s actually on the shelf that week. A bank has to prove reliability every time someone checks a branch profile. A hospital needs to make sure that when a patient searches for “urgent care,” the hours, insurance info, and provider reviews are accurate that very day. Different settings, same principle: close the gap between what people see online and what they experience in real life.

And this isn’t just about dashboards. The real win comes from acting quickly on what the signals show. Think about two retailers with dipping review scores. One shrugs and logs it. The other digs deeper, notices the complaints all mention stockouts in one region, and shifts supply within days. Customers stay loyal because the brand responded, not because it had a prettier chart.

That’s the difference BX is designed to create. Reports tell you what already happened. Acting on those signals shapes what happens next.

The New Mandate for Marketing Leaders

In the experience economy, BX isn’t abstract; it’s actionable. And Rio SEO gives brands the tools, data, and automation to operationalize it, turning every search, review, and update into a moment that builds loyalty and long-term growth.

Today’s marketing leaders aren’t being judged on traffic spikes anymore. What matters now is whether customers stick around, how much value they bring over time, and what it costs to serve them. That shift changes everything about the role of local search and puts Brand Experience (BX) at the center of the conversation.

When search is treated as a checklist—hours updated, pin fixed, job done—brands miss the bigger opportunity. Worse, they give ground to competitors who recognize that discovery is experience, and experience drives revenue.

BX gives CMOs and marketing leaders a framework for connecting visibility, reputation, and responsiveness. It bridges the gap between what people see in search and what they experience when they engage. And that’s where Rio SEO delivers real advantage: by giving brands the unified data, automation, and insights to make BX tangible in every market, every listing, and every moment.

You can see the difference in how leaders approach it across divergent industries:

  • Retail: Linking “near me” searches directly to in-stock inventory so shoppers know what’s available before they walk in.
  • Restaurants: Connecting menu updates and “order online” links directly to local search profiles, so when a customer searches “Thai takeout near me,” they see real-time specials, accurate hours, and an easy path to order.
  • Financial Services: Displaying verified first-party reviews on branch profiles to boost credibility and reassure customers choosing where to bank.
Image by Rio SEO, Nov 2025

The common thread is dependability. Local search is no longer about being visible once. It’s about proving, again and again, that your brand can be trusted in the small but decisive moments when customers are making up their minds. BX provides the vision; Rio SEO provides the infrastructure to bring it to life: connecting discovery with loyalty in a world where customers expect precision, empathy, and instant answers.

The Strategic Case for Local Search

The business case for local search doesn’t sit on the margins anymore. It ties directly to growth, trust, and efficiency. Within a Brand Experience (BX) framework, it links customer intent with measurable business outcomes, and Rio SEO gives brands the precision tools to manage that connection at scale.

Revenue Starts Here

Local search is full of high-intent signals: someone taps “call now,” asks for directions, or books an appointment. These metrics are crucial moments that can lead to sales, often within hours. In fact, most local searchers buy within 48 hours: three-quarters of restaurant seekers and nearly two-thirds of retail shoppers. That urgency makes consistency and accessibility non-negotiable.

Trust is Built in the Details

Reviews have become a kind of reputation currency, and customers spend it carefully. Three out of four people read at least four reviews before making a choice. If the basics are wrong—a missing phone number, the wrong hours—trust evaporates. More than half of consumers say they won’t visit a business if the listing details are off. Rio SEO’s centralized platform keeps data clean and consistent, ensuring that every profile communicates reliability, the foundation of trust in BX.

Efficiency That Pays for Itself

Every time insights from search and feedback flow back into operations, friction disappears before it gets expensive. Accurate listings mean fewer misrouted calls. Quick review responses calm frustration before it snowballs. Clear online paths reduce the burden on service teams.

In healthcare, that can mean shorter call center queues. In financial services, fewer “where do I start?” calls during onboarding. For retailers, avoiding wasted trips when hours are wrong keeps customers coming back instead of leaving disappointed. Each fix trims cost-to-serve while strengthening trust—a rare double win. Rio SEO automates these workflows, saving teams time while enhancing experience quality.

Your Edge Over the Competition

Too many organizations still keep SEO and CX in separate lanes. BX unites them and Rio SEO operationalizes that unity. The ones who bring those signals together see patterns earlier, act faster, and pull ahead of rivals who are still optimizing for clicks instead of experiences.

The Power of Brand Experience

BX blends rigorous data with customer-centric urgency. It gives leaders a way to not only show up in search but to be chosen, trusted, and remembered.

Winning the Experience Economy Starts in Local Search

Search no longer waits for a typed query. With AI Overviews, predictive results, and personalized recommendations, it increasingly anticipates what people want and surfaces the businesses most likely to deliver.

That shift raises the bar. In this new environment, local search isn’t a maintenance task but rather the front line of Brand Experience (BX). Accuracy, responsiveness, and reputation aren’t side jobs anymore; they’re the signals that decide who gets noticed, who gets trusted, and who gets passed over.

The companies setting the pace already treat local presence as a growth engine, not a maintenance task. They link discovery with delivery, reviews with real replies, and feedback with action. Competitors who don’t will find themselves playing catch-up in an economy where expectations reset every day.

The message is clear: customers don’t separate search from experience, and neither can you. Local search is now where growth, trust, and efficiency intersect. Handle it as a checklist, and you’ll fall behind. Treat it as a lever for Brand Experience, and you’ll define the standard others have to meet.

That’s where Rio SEO makes the difference. We help enterprise brands connect the dots between visibility, data, and experience, empowering marketers to act on signals faster, measure impact clearly, and deliver consistency at scale. With Rio SEO, brands don’t just show up in search; they stand out, stay accurate, and turn visibility into measurable growth.

Image by Rio SEO, Nov 2025

Ready to lead in the era of AI-driven discovery?

Partner with Rio SEO to transform your local presence into a connected, data-powered experience that builds trust, drives action, and earns loyalty at every location, on every platform, every day.

Learn more about Rio SEO’s Local Experience solutions today.

Ecommerce MGMT 0 Comments
Nov 14 2025
Data: Translated Sites See 327% More Visibility in AI Overviews

This post was sponsored by Weglot. The opinions expressed in this article are the sponsor’s own.

When Google’s AI Overviews launched in 2024, dozens of questions quickly surfaced among SEO professionals, one being: if AI now curates and summarizes search results, how do websites earn visibility, especially across languages?

Weglot recently conducted a data-driven study, analyzing 1.3 million citations across Google AI Overviews and ChatGPT to determine if LLMs cite content in one language, would they also cite it in others?

The result: translated websites saw up to 327% more visibility in AI Overviews than untranslated ones, a clear signal that international SEO is becoming inseparable from AI search.

Read The Full Study

What’s more, websites with another language available were also more likely to be cited in AI Overviews, regardless of the language the search was made.

This shift is redefining the rules of visibility. AI Overviews and large language models (LLMs) now mediate how information is discovered. Instead of ranking pages, they “cite” sources in generated responses.

But with that shift comes a new risk: if your website isn’t available in the user’s search language, does AI simply overlook it, or worse, send users to Google Translate’s proxy page instead?

The risk with Google’s Translate proxy is that while it does the translation work for you, you have no control over the translations of your content. Worse still, you don’t get any of the traffic benefits, as users are not directed to your site.

The Study

Here’s how the research worked. To understand how translation affects AI visibility, Weglot focused the research on Spanish-language websites across two markets: Spain and Mexico.

The study was then split into two phases. Phase one focused on websites that weren’t translated, and therefore only displayed the language intended for their market, in this case, Spanish.

In that phase, Weglot looked at 153 websites without English translations: 98 from Spain and 55 from Mexico. Weglot deliberately selected high-traffic sites because they offered no English versions.

Phase two involved a comparison group of 83 Spanish and Mexican sites with versions in both Spanish and English. This allowed Weglot to directly compare the performance of translated versus untranslated content.

In total, this generated 22,854 queries in phase one and 12,138 in phase two. The methodology converted the top 50 non-branded keywords of each site into queries that users would likely search, and then these were translated between the Spanish and English versions.

In total, 1.3 million citations were analyzed.

The Key Results

Untranslated Sites Have Very Low AI Search Visibility

The findings show that untranslated websites experience a substantial drop in visibility for searches conducted in non-available languages, despite maintaining strong visibility in the current available language.

Diving deeper into this, untranslated sites essentially lose massive visibility. From the study, even when these Spanish websites performed well in Spanish searches, the sites virtually disappeared in English searches.

Looking at this data further within Google AI Overviews:

  • The sample size of 98 untranslated sites from Spain had 17,094 citations for Spanish queries vs 2,810 citations for the equivalent search in English, a 431% gap in visibility.
  • Taking a look at untranslated sites in Mexico, the study identified a similar pattern. 12,038 citations for Spanish queries vs 3,450 citations for English, showing 213% fewer citations when searching English.

Even ChatGPT, though slightly more balanced, still favored translated sites, with Spanish sites receiving 3.5% fewer citations in English and 4.9% fewer with Mexican sites.

Image created by Weglot, November 2025

Translated Sites Have 327% More AI Search Visibility

But what happens when you do translate your site?

Bringing in the comparison group of Spanish websites that also have an English version, we can see that translated sites dramatically close the visibility gap and that having a second language transformed visibility within Google AI Overviews.

Google AI Overviews:

  • Translated sites in Spain saw 10,046 citations vs 8,048 in English, showcasing only a 22% gap.
  • Translated sites in Mexico showed 5,527 citations for Spanish queries and 3,325 citations for English, and a difference of 59%.

Overall, translated sites achieved 327% more visibility than untranslated ones and earned 24% more total citations per query.

When looking at ChatGPT, the bias almost vanished. Translated sites saw near-equal citations in both languages.

Image created by Weglot, November 2025

Next Steps: Translate Your Site To Boost Global Visibility In AI SERPs

Translation does more than boost visibility, it multiplies it.

Not only does having multiple languages across your site ensure your site gets picked up for searches in multiple languages, but it also adds to the overall visibility of your site as a whole.

The study found that translated sites perform better across all metrics. The data shows that translated sites received 24% more citations per prompt than untranslated sites.

Looking at this by language, translation resulted in a 33% increase in English citations and a 16% increase in Spanish citations per query.

Weglot’s findings indicate that translation acts as a signal of authority and reliability for AIOs and ChatGPT, boosting citation performance across all languages, not only the ones content is translated.

Image created by Weglot, November 2025

AI Search Rewards Translated Content as a Visibility Signal

Traditional international SEO has long focused on hreflang tags and localized keywords. But in the age of AI search, translation itself becomes a visibility signal:

  1. Language alignment: AI engines prioritize content matching the query’s language.
  2. Authority building: Translated content attracts engagement across markets, improving perceived reliability.
  3. Traffic control: Proper translations prevent Google Translate proxies from intercepting clicks.
  4. Semantic reach: Multilingual content broadens your surface area for AI training and citation.

Put simply: If your content isn’t in the language of the question, it’s unlikely it will be in the answer either.

The Business Impact

The consequences aren’t theoretical. One case in Weglot’s dataset, a major Spanish book retailer selling English-language titles worldwide without an English version of its site, shows the impact.

When English speakers searched for relevant books:

  • The site appeared 64% less often in Google AI Overviews and ChatGPT.
  • In 36% of the cases where it did appear, the link pointed to Google Translate’s proxy, not the retailer’s own domain.

Despite offering exactly what English users wanted, the business lost visibility, traffic, and ultimately, sales.

The Bigger Picture: AI Search Is Redefining SEO and Translation Is Now a Growth Strategy

The implications reach far beyond Spain or Mexico, or even the Spanish language.

As AI search evolves, the SEO playbook is expanding. Ranking isn’t just about “position one” anymore; it’s about being cited, summarized, and surfaced by machines trained on multilingual web content.

Weglot’s findings point to a future where translation is both an SEO and an AI strategy and not a localization afterthought.

With Google AIOs now live in multiple languages and ChatGPT integrating real-time web data, multilingual visibility has become an equity issue: sites optimized for one language risk being invisible in another.

Image created by Weglot, November 2025

Final Takeaway: Untranslated Sites Are Invisible in AI Search

The evidence is clear: Untranslated = unseen. Website translation is high up there for AIO visibility.

As AI continues to shape how search engines understand relevance, translation isn’t just about accessibility; it’s how your brand gets recognized by algorithms and audiences alike.

For the easiest way to translate a website, start your free trial now!

Plus, enjoy a 15% discount for 12 months on public plans by using the promo code SEARCH15 on a paid plan purchase.

Read The Full Study

Image Credits

Featured Image: Image by Weglot. Used with permission.

In-Post Images: Image by Weglot. Used with permission.

Ecommerce MGMT 0 Comments
Nov 10 2025
A Step-By-Step AEO Guide For Growing AI Citations & Visibility via @sejournal, @fthead9

This post was sponsored by TAC Marketing. The opinions expressed in this article are the sponsor’s own.

After years of trying to understand the black box that is Google search, SEO professionals have a seemingly even more opaque challenge these days – how to earn AI citations.

While at first glance inclusion in AI answers seems even more of a mystery than traditional SEO, there is good news. Once you know how to look for them, the AI engines do provide clues to what they consider valuable content.

This article will give you a step-by-step guide to discovering the content that AI engines value and provide a blueprint for optimizing your website for AI citations.

Take A Systematic Approach To AI Engine Optimization

The key to building an effective AI search optimization strategy begins with understanding the behavior of AI crawlers. By analyzing how these bots interact with your site, you can identify what content resonates with AI systems and develop a data-driven approach to optimization.

While Google remains dominant, AI-powered search engines like ChatGPT, Perplexity, and Claude are increasingly becoming go-to resources for users seeking quick, authoritative answers. These platforms don’t just generate responses from thin air – they rely on crawled web content to train their models and provide real-time information.

This presents both an opportunity and a challenge. The opportunity lies in positioning your content to be discovered and referenced by these AI systems. The challenge is understanding how to optimize for algorithms that operate differently from traditional search engines.

The Answer Is A Systematic Approach

  • Discover what content AI engines value based on their crawler behavior.
    • Traditional log file analysis.
    • SEO Bulk Admin AI Crawler monitoring.
  • Reverse engineer prompting.
    • Content analysis.
    • Technical analysis.
  • Building the blueprint.

What Are AI Crawlers & How To Use Them To Your Advantage

AI crawlers are automated bots deployed by AI companies to systematically browse and ingest web content. Unlike traditional search engine crawlers that primarily focus on ranking signals, AI crawlers gather content to train language models and populate knowledge bases.

Major AI crawlers include:

  • GPTBot (OpenAI’s ChatGPT).
  • PerplexityBot (Perplexity AI).
  • ClaudeBot (Anthropic’s Claude).
  • Googlebot crawlers (Google AI).

These crawlers impact your content strategy in two critical ways:

  1. Training data collection.
  2. Real-time information retrieval.

Training Data Collection

AI models are trained on vast datasets of web content. Pages that are crawled frequently may have a higher representation in training data, potentially increasing the likelihood of your content being referenced in AI responses.

Real-Time Information Retrieval

Some AI systems crawl websites in real-time to provide current information in their responses. This means fresh, crawlable content can directly influence AI-generated answers.

When ChatGPT responds to a query, for instance, it’s synthesizing information gathered by its underlying AI crawlers. Similarly, Perplexity AI, known for its ability to cite sources, actively crawls and processes web content to provide its answers. Claude also relies on extensive data collection to generate its intelligent responses.

The presence and activity of these AI crawlers on your site directly impact your visibility within these new AI ecosystems. They determine whether your content is considered a source, if it’s used to answer user questions, and ultimately, if you gain attribution or traffic from AI-driven search experiences.

Understanding which pages AI crawlers visit most frequently gives you insight into what content AI systems find valuable. This data becomes the foundation for optimizing your entire content strategy.

How To Track AI Crawler Activity: Find & Use Log File Analysis

The Easy Way: We use SEO Bulk Admin to analyze server log files for us.

However, there’s a manual way to do it, as well.

Server log analysis remains the standard for understanding crawler behavior. Your server logs contain detailed records of every bot visit, including AI crawlers that may not appear in traditional analytics platforms, which focus on user visits.

Essential Tools For Log File Analysis

Several enterprise-level tools can help you parse and analyze log files:

  • Screaming Frog Log File Analyser: Excellent for technical SEOs comfortable with data manipulation.
  • Botify: Enterprise solution with robust crawler analysis features.
  • Semrush: Offers log file analysis within its broader SEO suite.
Screenshot from Screaming Frog Log File AnalyserScreenshot from Screaming Frog Log File Analyser, October 2025

The Complexity Challenge With Log File Analysis

The most granular way to understand which bots are visiting your site, what they’re accessing, and how frequently, is through server log file analysis.

Your web server automatically records every request made to your site, including those from crawlers. By parsing these logs, you can identify specific user-agents associated with AI crawlers.

Here’s how you can approach it:

  1. Access Your Server Logs: Typically, these are found in your hosting control panel or directly on your server via SSH/FTP (e.g., Apache access logs, Nginx access logs).
  2. Identify AI User-Agents: You’ll need to know the specific user-agent strings used by AI crawlers. While these can change, common ones include:
  • OpenAI (for ChatGPT, e.g., `ChatGPT-User` or variations)
  • Perplexity AI (e.g., `PerplexityBot`)
  • Anthropic (for Claude, though often less distinct or may use a general cloud provider UAs)
  • Other LLM-related bots (e.g., “GoogleBot” and `Google-Extended` for Google’s AI initiatives, potentially `Vercelbot` or other cloud infrastructure bots that LLMs might use for data fetching).
  1. Parse and Analyze: This is where the previously mentioned log analyzer tools come into play. Upload your raw log files into the analyzer and start filtering the results to identify AI crawler and search bot activity. Alternatively, for those with technical expertise, Python scripts or tools like Splunk or Elasticsearch can be configured to parse logs, identify specific user-agents, and visualize the data.

While log file analysis provides the most comprehensive data, it comes with significant barriers for many SEOs:

  • Technical Depth: Requires server access, understanding of log formats, and data parsing skills.
  • Resource Intensive: Large sites generate massive log files that can be challenging to process.
  • Time Investment: Setting up proper analysis workflows takes considerable upfront effort.
  • Parsing Challenges: Distinguishing between different AI crawlers requires detailed user-agent knowledge.

For teams without dedicated technical resources, these barriers can make log file analysis impractical despite its value.

An Easier Way To Monitor AI Visits: SEO Bulk Admin

While log file analysis provides granular detail, its complexity can be a significant barrier for all but the most highly technical users. Fortunately, tools like SEO Bulk Admin can offer a streamlined alternative.

The SEO Bulk Admin WordPress plugin automatically tracks and reports AI crawler activity without requiring server log access or complex setup procedures. The tool provides:

  • Automated Detection: Recognizes major AI crawlers, including GPTBot, PerplexityBot, and ClaudeBot, without manual configuration.
  • User-Friendly Dashboard: Presents crawler data in an intuitive interface accessible to SEOs at all technical levels.
  • Real-Time Monitoring: Tracks AI bot visits as they happen, providing immediate insights into crawler behavior.
  • Page-Level Analysis: Shows which specific pages AI crawlers visit most frequently, enabling targeted optimization efforts.
Screenshot of SEO Bulk Admin AI/Bots ActivityScreenshot of SEO Bulk Admin AI/Bots Activity, October 2025

This gives SEOs instant visibility into which pages are being accessed by AI engines – without needing to parse server logs or write scripts.

Comparing SEO Bulk Admin Vs. Log File Analysis

Feature Log File Analysis SEO Bulk Admin
Data Source Raw server logs WordPress dashboard
Technical Setup High Low
Bot Identification Manual Automatic
Crawl Tracking Detailed Automated
Best For Enterprise SEO teams Content-focused SEOs & marketers

For teams without direct access to server logs, SEO Bulk Admin offers a practical, real-time way to track AI bot activity and make data-informed optimization decisions.

Screenshot of SEO Bulk Admin Page Level Crawler ActivityScreenshot of SEO Bulk Admin Page Level Crawler Activity, October 2025

Using AI Crawler Data To Improve Content Strategy

Once you’re tracking AI crawler activity, the real optimization work begins. AI crawler data reveals patterns that can transform your content strategy from guesswork into data-driven decision-making.

Here’s how to harness those insights:

1. Identify AI-Favored Content

  • High-frequency pages: Look for pages that AI crawlers visit most frequently. These are the pieces of content that these bots are consistently accessing, likely because they find them relevant, authoritative, or frequently updated on topics their users inquire about.
  • Specific content types: Are your “how-to” guides, definition pages, research summaries, or FAQ sections getting disproportionate AI crawler attention? This can reveal the type of information AI models are most hungry for.

2. Spot LLM-Favored Content Patterns

  • Structured data relevance: Are the highly-crawled pages also rich in structured data (Schema markup)? It’s an open debate, but some speculate that AI models often leverage structured data to extract information more efficiently and accurately.
  • Clarity and conciseness: AI models excel at processing clear, unambiguous language. Content that performs well with AI crawlers often features direct answers, brief paragraphs, and strong topic segmentation.
  • Authority and citations: Content that AI models deem reliable may be heavily cited or backed by credible sources. Track if your more authoritative pages are also attracting more AI bot visits.

3. Create A Blueprint From High-Performing Content

  • Reverse engineer success: For your top AI-crawled content, document its characteristics.
  • Content structure: Headings, subheadings, bullet points, numbered lists.
  • Content format: Text-heavy, mixed media, interactive elements.
  • Topical depth: Comprehensive vs. niche.
  • Keywords/Entities: Specific terms and entities frequently mentioned.
  • Structured data implementation: What schema types are used?
  • Internal linking patterns: How is this content connected to other relevant pages?
  • Upgrade underperformers: Apply these successful attributes to content that currently receives less AI crawler attention.
  • Refine content structure: Break down dense paragraphs, add more headings, and use bullet points for lists.
  • Inject structured data: Implement relevant Schema markup (e.g., `Q&A`, `HowTo`, `Article`, `FactCheck`) on pages lacking it.
  • Enhance clarity: Rewrite sections to achieve conciseness and directness, focusing on clearly answering potential user questions.
  • Expand Authority: Add references, link to authoritative sources, or update content with the latest insights.
  • Improve Internal Linking: Ensure that relevant underperforming pages are linked from your AI-favored content and vice versa, signaling topical clusters.

This short video walks you through the process of discovering what pages are crawled most often by AI crawlers and how to use that information to start your optimization strategy.

Here is the prompt used in the video:

You are an expert in AI-driven SEO and search engine crawling behavior analysis.

TASK: Analyze and explain why the URL [https://fioney.com/paying-taxes-with-a-credit-card-pros-cons-and-considerations/] was crawled 5 times in the last 30 days by the oai-searchbot(at)openai.com crawler, while [https://fioney.com/discover-bank-review/] was only crawled twice.

GOALS:

– Diagnose technical SEO factors that could increase crawl frequency (e.g., internal linking, freshness signals, sitemap priority, structured data, etc.)

– Compare content-level signals such as topical authority, link magnet potential, or alignment with LLM citation needs

– Evaluate how each page performs as a potential citation source (e.g., specificity, factual utility, unique insights)

– Identify which ranking and visibility signals may influence crawl prioritization by AI indexing engines like OpenAI’s

CONSTRAINTS:

– Do not guess user behavior; focus on algorithmic and content signals only

– Use bullet points or comparison table format

– No generic SEO advice; tailor output specifically to the URLs provided

– Consider recent LLM citation trends and helpful content system priorities

FORMAT:

– Part 1: Technical SEO comparison

– Part 2: Content-level comparison for AI citation worthiness

– Part 3: Actionable insights to increase crawl rate and citation potential for the less-visited URL

Output only the analysis, no commentary or summary.

Note: You can find more prompts for AI-focused optimization in this article: 4 Prompts to Boost AI Citations.

By taking this data-driven approach, you move beyond guesswork and build an AI content strategy grounded in actual machine behavior on your site.

This iterative process of tracking, analyzing, and optimizing will ensure your content remains a valuable and discoverable resource for the evolving AI search landscape.

Final Thoughts On AI Optimization

Tracking and analyzing AI crawler behavior is no longer optional for SEOs seeking to remain competitive in the AI-driven search era.

By using log file analysis tools – or simplifying the process with SEO Bulk Admin – you can build a data-driven strategy that ensures your content is favored by AI engines.

Take a proactive approach by identifying trends in AI crawler activity, optimizing high-performing content, and applying best practices to underperforming pages.

With AI at the forefront of search evolution, it’s time to adapt and capitalize on new traffic opportunities from conversational search engines.

Leverage AI Insights

Image Credits

Featured Image: Image by TAC Marketing. Used with permission.

In-Post Images: Image by TAC Marketing. Used with permission. 

Ecommerce MGMT 0 Comments
Nov 6 2025
Why AI Content All Sounds the Same & How SEO Pros Can Fix It via @sejournal, @mktbrew

This post was sponsored by Market Brew. The opinions expressed in this article are the sponsor’s own.

If your AI-generated articles don’t rank but sound fine, you’re not alone.

AI has made it effortless to produce content, but not to stand out in SERPs.

Across nearly every industry, brands are using generative AI tools like ChatGPT, Perplexity, Claude, and more to scale content production, only to discover that, to search engines, everything sounds the same.

But this guide will help you build E-E-A-T-friendly & AI-Overview-worthy content that boosts your AI Overview visibility, while giving you more control over your rankings.

Why Does All AI-Generated Content Sound The Same?

Most generative AI models write from the same training data, producing statistically “average” answers to predictable prompts.

The result is fluent, on-topic copy that is seen as interchangeable from one brand to the next.

To most readers, it may feel novel.

To search engines, your AI content may look redundant.

Algorithms can now detect when pages express the same ideas with minor wording differences. Those pages compete for the same meaning, and only one tends to win.

The challenge for SEOs isn’t writing faster, it’s writing differently.

That starts with understanding why search engines can tell the difference even when humans can’t.

How Do Search Engines & Answer Engines See My Content?

Here’s what Google actually sees when it looks at your page:

  • Search engines no longer evaluate content by surface keywords.
  • They map meaning.

Modern ranking systems translate your content into embeddings.

When two pages share nearly identical embeddings, the algorithm treats them as duplicates of meaning, similar to duplicate content.

That’s why AI-generated content blends together. The vocabulary may change, but the structure and message remain the same.

What Do Answer Engines Look For On Web Pages?

Beyond words, engines analyze the entire ecosystem of a page:

These structural cues help determine whether content is contextually distinct or just another derivative variant.

To stand out, SEOs have to shape the context that guides the model before it writes.

That’s where the Inspiration Stage comes in.

How To Teach AI To Write Like Your Brand, Not The Internet

Before you generate another article, feed the AI your brand’s DNA.

Language models can complete sentences, but can’t represent your brand, structure, or positioning unless you teach them.

Advanced teams solve this through context engineering, defining who the AI is writing for and how that content should behave in search.

The Inspiration Stage should combine three elements that together create brand-unique outputs.

Step 1 – Create A Brand Bible: Define Who You Are

The first step is identity.

A Brand Bible translates your company’s tone, values, and vocabulary into structured guidance the AI can reference. It tells the model how to express authority, empathy, or playfulness. And just as important, what NOT to say.

Without it, every post sounds like a tech press release.

With it, you get language that feels recognizably yours, even when produced at scale.

“The Brand Bible isn’t decoration: it’s a defensive wall against generic AI sameness.”

A great example: Market Brew’s Brand Bible Wizard

Step 2 – Create A Template URL: Structure How You Write

Great writing still needs great scaffolding.

By supplying a Template URL, a page whose structure already performs well, you give the model a layout to emulate: heading hierarchy, schema markup, internal link positions, and content rhythm.

Adding a Template Influence parameter can help the AI decide how closely to follow that structure. Lower settings would encourage creative variation; higher settings would preserve proven formatting for consistency across hundreds of pages.

Templates essentially become repeatable frameworks for ranking success.

An example of how to apply a template URL

Step 3 – Reverse-Engineer Your Competitor Fan-Out Prompts: Know the Landscape

Context also means competition. When you are creating AI content, it needs to be optimized for a series of keywords and prompts.

Fan-out prompts are a concept that maps the broader semantic territory around a keyword or topic. These are a network of related questions, entities, and themes that appear across the SERP.

In addition, fan-out prompts should be reverse-engineered from top competitors in that SERP.

Feeding this intelligence into the AI ensures your content strategically expands its coverage; something that the LLM search engines are hungry for.

“It’s not copying competitors, it’s reverse-engineering the structure of authority.”

Together, these three inputs create a contextual blueprint that transforms AI from a text generator into a brand and industry-aware author.

Market Brew’s implementation of reverse engineering fan-out prompts

How To Incorporate Human-Touch Into AI Content

If your AI tool spits out finished drafts with no checkpoints, you’ve lost control of what high-quality content is.

That’s a problem for teams who need to verify accuracy, tone, or compliance.

Breaking generation into transparent stages solves this.

Incorporate checkpoints where humans can review, edit, or re-queue the content at each stage:

  • Research.
  • Outline.
  • Draft.
  • Refinement.

Metrics for readability, link balance, and brand tone become visible in real time.

This “human-in-the-loop” design keeps creative control where it belongs.

Instead of replacing editors, AI becomes their analytical assistant: showing how each change affects the structure beneath the words.

“The best AI systems don’t replace editors, they give them x-ray vision into every step of the process.”

How To Build Content The Way Search Engines Read It

Modern SEO focuses on predictive quality signals: indicators that content is likely to perform before it ever ranks.

These include:

  • Semantic alignment: how closely the page’s embeddings match target intent clusters.
  • Structural integrity: whether headings, schema, and links follow proven ranking frameworks.
  • Brand consistency and clarity: tone and terminology that match the brand bible without losing readability.

Tracking these signals during creation turns optimization into a real-time discipline.

Teams can refine strategy based on measurable structure, not just traffic graphs weeks later.

That’s the essence of predictive SEO: understanding success before the SERP reflects it.

The Easy Way To Create High-Visibility Content For Modern SERPs

Top SEO teams are already using the Content Booster approach.

Market Brew’s Content Booster is one such example.

It embeds AI writing directly within a search engine simulation, using the same mechanics that evaluate pages to guide creation.

Writers begin by loading their Brand Bible, selecting a Template URL, and enabling reverse-engineered fan-out prompts.

Next, the internal and external linking strategy is defined, which uses a search engine model’s link scoring system, plus its entity-based text classifier as a guide to place the most valuable links possible.

This is bolstered by a “friends/foes” section that allows writers to define quoting / linking opportunities to friendly sites, and “foe” sites where external linking should be avoided.

The Content Booster then produces and evaluates a 7-stage content pipeline, each driven by thousands of AI agents.

Stage Function What You Get
0. Brand Bible Upload your brand assets and site; Market Brew learns your tone, voice, and banned terms. Every piece written in your unique brand style.
1. Opportunity & Strategy Define your target keyword or prompt, tone, audience, and linking strategy. A strategic blueprint tied to real search intent.
2. Brief & Structure Creates an SEO-optimized outline using semantic clusters and entity graphs. Perfectly structured brief ready for generation.
3. Draft Generation AI produces content constrained by embeddings and brand parameters. A first draft aligned with ranking behavior, not just text patterns.
4. Optimization & Alignment Uses cosine similarity and Market Brew’s ranking model to score each section. Data-driven tuning for maximum topical alignment.
5. Internal Linking & Entity Enrichment Adds schema markup, entity tags, and smart internal links. Optimized crawl flow and contextual authority.
6. Quality & Compliance Checks grammar, plagiarism, accessibility, and brand voice. Ready-to-publish content that meets editorial and SEO standards.

Editors can inspect or refine content at any stage, ensuring human direction without losing automation.

Instead of waiting months to measure results, teams see predictive metrics: like fan-out coverage, audience/persona compliance, semantic similarity, link distribution, embedding clusters and more. The moment a draft is generated.

This isn’t about outsourcing creativity.

It’s about giving SEO professionals the same visibility and control that search engineers already have.

Your Next Steps

If you teach your AI to think like your best strategist, sameness stops being a problem.

Every brand now has access to the same linguistic engine; the only differentiator is context.

The future of SEO belongs to those who blend human creativity with algorithmic understanding, who teach their models to think like search engines while sounding unmistakably human.

By anchoring AI in brand, structure, and competition, and by measuring predictive quality instead of reactive outcomes, SEOs can finally close the gap between what we publish and what algorithms reward.

“The era of AI sameness is already here. The brands that thrive will be the ones that teach their AI to sound human and think like a search engine.”

Ready to see how predictive SEO works in action?

Explore the free trial of Market Brew’s Light Brew system — where you can model how search engines interpret your content and test AI writing workflows before publishing.

Get Started Here

Image Credits

Featured Image: Image by Market Brew. Used with permission.

Ecommerce MGMT 0 Comments
Oct 28 2025
The AI Search Visibility Audit: 15 Questions Every CMO Should Ask

This post was sponsored by IQRush. The opinions expressed in this article are the sponsor’s own.

Your traditional SEO is winning. Your AI visibility is failing. Here’s how to fix it.

Your brand dominates page one of Google. Domain authority crushes competitors. Organic traffic trends upward quarter after quarter. Yet when customers ask ChatGPT, Perplexity, or others about your industry, your brand is nowhere to be found.

This is the AI visibility gap, which causes missed opportunities in awareness and sales.

“SEO ranking on page one doesn’t guarantee visibility in AI search.  The rules of ranking have shifted from optimization to verification.”

Raj Sapru, Netrush, Chief Strategy Officer

Recent analysis of AI-powered search patterns reveals a troubling reality: commercial brands with excellent traditional SEO performance often achieve minimal visibility in AI-generated responses. Meanwhile, educational institutions, industry publications, and comparison platforms consistently capture citations for product-related queries.

The problem isn’t your content quality. It’s that AI engines prioritize entirely different ranking factors than traditional search: semantic query matching over keyword density, verifiable authority markers over marketing claims, and machine-readable structure over persuasive copy.

This audit exposes 15 questions that separate AI-invisible brands from citation leaders.

Download the Full Audit

We’re sharing the first 7 critical questions below, covering visibility assessment, authority verification, and measurement fundamentals. These questions will reveal your most urgent gaps and provide immediate action steps.

Question 1: Are We Visible in AI-Powered Search Results?

Why This Matters: Commercial brands with strong traditional SEO often achieve minimal AI citation visibility in their categories. A recent IQRush field audit found fewer than one in ten AI-generated answers included in the brand, showing how limited visibility remains, even for strong SEO performers. Educational institutions, industry publications, and comparison sites dominate AI responses for product queries—even when commercial sites have superior content depth. In regulated industries, this gap widens further as compliance constraints limit commercial messaging while educational content flows freely into AI training data.

How to Audit:

  • Test core product or service queries through multiple AI platforms (ChatGPT, Perplexity, Claude)
  • Document which sources AI engines cite: educational sites, industry publications, comparison platforms, or adjacent content providers
  • Calculate your visibility rate: queries where your brand appears vs. total queries tested

Action: If educational/institutional sources dominate, implement their citation-driving elements:

  • Add research references and authoritative citations to product content
  • Create FAQ-formatted content with an explicit question-answer structure
  • Deploy structured data markup (Product, FAQ, Organization schemas)
  • Make commercial content as machine-readable as educational sources

IQRush tracks citation frequency across AI platforms. Competitive analysis shows which schema implementations, content formats, and authority signals your competitors use to capture citations you’re losing.

Question 2: Are Our Expertise Claims Actually Verifiable?

Why This Matters: Machine-readable validation drives AI citation decisions: research references, technical standards, certifications, and regulatory documentation. Marketing claims like “industry-leading” or “trusted by thousands” carry zero weight. In one IQRush client analysis, more than four out of five brand mentions were supported by citations—evidence that structured, verifiable content is far more likely to earn visibility. Companies frequently score high on human appeal—compelling copy, strong brand messaging—but lack the structured authority signals AI engines require. This mismatch explains why brands with excellent traditional marketing achieve limited citation visibility.

How to Audit:

  • Review your priority pages and identify every factual claim made (performance stats, quality standards, methodology descriptions)
  • For each claim, check whether it links to or cites an authoritative source (research, standards body, certification authority)
  • Calculate verification ratio: claims with authoritative backing vs. total factual claims made

Action: For each unverified claim, either add authoritative backing or remove the statement:

  • Add specific citations to key claims (research databases, technical standards, industry reports)
  • Link technical specifications to recognized standards bodies
  • Include certification or compliance verification details where applicable
  • Remove marketing claims that can’t be substantiated with machine-verifiable sources

IQRush’s authority analysis identifies which claims need verification and recommends appropriate authoritative sources for your industry, eliminating research time while ensuring proper citation implementation.

Question 3: Does Our Content Match How People Query AI Engines?

Why This Matters: Semantic alignment matters more than keyword density. Pages optimized for traditional keyword targeting often fail in AI responses because they don’t match conversational query patterns. A page targeting “best project management software” may rank well in Google but miss AI citations if it doesn’t address how users actually ask: “What project management tool should I use for a remote team of 10?” In recent IQRush client audits, AI visibility clustered differently across verticals—consumer brands surfaced more frequently for transactional queries, while financial clients appeared mainly for informational intent. Intent mapping—informational, consideration, or transactional—determines whether AI engines surface your content or skip it.

How to Audit:

  • Test sample queries customers would use in AI engines for your product category
  • Evaluate whether your content is structured for the intent type (informational vs. transactional)
  • Assess if content uses conversational language patterns vs. traditional keyword optimization

Action: Align content with natural question patterns and semantic intent:

  • Restructure content to directly address how customers phrase questions
  • Create content for each intent stage: informational (education), consideration (comparison), transactional (specifications)
  • Use conversational language patterns that match AI engine interactions
  • Ensure semantic relevance beyond just keyword matching

IQRush maps your content against natural query patterns customers use in AI platforms, showing where keyword-optimized pages miss conversational intent.

Question 4: Is Our Product Information Structured for AI Recommendations?

Why This Matters: Product recommendations require structured data. AI engines extract and compare specifications, pricing, availability, and features from schema markup—not from marketing copy. Products with a comprehensive Product schema capture more AI citations in comparison queries than products buried in unstructured text. Bottom-funnel transactional queries (“best X for Y,” product comparisons) depend almost entirely on machine-readable product data.

How to Audit:

  • Check whether product pages include Product schema markup with complete specifications
  • Review if technical details (dimensions, materials, certifications, compatibility) are machine-readable
  • Test transactional queries (product comparisons, “best X for Y”) to see if your products appear
  • Assess whether pricing, availability, and purchase information is structured

Action: Implement comprehensive product data structure:

  • Deploy Product schema with complete technical specifications
  • Structure comparison information (tables, lists) that AI can easily parse
  • Include precise measurements, certifications, and compatibility details
  • Add FAQ schema addressing common product selection questions
  • Ensure pricing and availability data is machine-readable

IQRush’s ecommerce audit scans product pages for missing schema fields—price, availability, specifications, reviews—and prioritizes implementations based on query volume in your category.

Question 5: Is Our “Fresh” Content Actually Fresh to AI Engines?

Why This Matters: Recency signals matter, but timestamp manipulation doesn’t work. Pages with recent publication dates, but outdated information underperforms older pages with substantive updates: new research citations, current industry data, or refreshed technical specifications. Genuine content updates outweigh simple republishing with changed dates.

How to Audit:

  • Review when your priority pages were last substantively updated (not just timestamp changes)
  • Check whether content references recent research, current industry data, or updated standards
  • Assess if “evergreen” content has been refreshed with current examples and information
  • Compare your content recency to competitors appearing in AI responses

Action: Establish genuine content freshness practices:

  • Update high-priority pages with current research, data, and examples
  • Add recent case studies, industry developments, or regulatory changes
  • Refresh citations to include latest research or technical standards
  • Implement clear “last updated” dates that reflect substantive changes
  • Create update schedules for key content categories

IQRush compares your content recency against competitors capturing citations in your category, flagging pages that need substantive updates (new research, current data) versus pages where timestamp optimization alone would help.

Question 6: How Do We Measure What’s Actually Working?

Why This Matters: Traditional SEO metrics—rankings, traffic, CTR—miss the consideration impact of AI citations. Brand mentions in AI responses influence purchase decisions without generating click-through attribution, functioning more like brand awareness channels than direct response. CMOs operating without AI visibility measurement can’t quantify ROI, allocate budgets effectively, or report business impact to executives.

How to Audit:

  • Review your executive dashboards: Are AI visibility metrics present alongside SEO metrics?
  • Examine your analytics capabilities: Can you track how citation frequency changes month-over-month?
  • Assess competitive intelligence: Do you know your citation share relative to competitors?
  • Evaluate coverage: Which query categories are you blind to?

Action: Establish AI citation measurement:

  • Track citation frequency for core queries across AI platforms
  • Monitor competitive citation share and positioning changes
  • Measure sentiment and accuracy of brand mentions
  • Add AI visibility metrics to executive dashboards
  • Correlate AI visibility with consideration and conversion metrics

IQRush tracks citation frequency, competitive share, and month-over-month trends across across AI platforms. No manual testing or custom analytics development is required.

Question 7: Where Are Our Biggest Visibility Gaps?

Why This Matters: Brands typically achieve citation visibility for a small percentage of relevant queries, with dramatic variation by funnel stage and product category. IQRush analysis showed the same imbalance: consumer brands often surfaced in purchase-intent queries, while service firms appeared mostly in educational prompts. Most discovery moments generate zero brand visibility. Closing these gaps expands reach at stages where competitors currently dominate.

How to Audit:

  • List queries customers would ask about your products/services across different funnel stages
  • Group them by funnel stage (informational, consideration, transactional)
  • Test each query in AI platforms and document: Does your brand appear?
  • Calculate what percentage of queries produce brand mentions in each funnel stage
  • Identify patterns in the queries where you’re absent

Action: Target the funnel stages with lowest visibility first:

  • If weak at informational stage: Build educational content that answers “what is” and “how does” queries
  • If weak at consideration stage: Create comparison content structured as tables or side-by-side frameworks
  • If weak at transactional stage: Add comprehensive product specs with schema markup
  • Focus resources on stages where small improvements yield largest reach gains

IQRush’s funnel analysis quantifies gap size by stage and estimates impact, showing which content investments will close the most visibility gaps fastest.

The Compounding Advantage of Early Action

The first seven questions and actions highlight the differences between traditional SEO performance and AI search visibility. Together, they explain why brands with strong organic rankings often have zero citations in AI answers.

The remaining 8 questions in the comprehensive audit help you take your marketing further. They focus on technical aspects: the structure of your content, the backbone of your technical infrastructure, and the semantic strategies that signal true authority to AI. 

“Visibility in AI search compounds, making it harder for your competition to break through. The brands that make themselves machine-readable today will own the conversation tomorrow.”
Raj Sapru, Netrush, Chief Strategy Officer

IQRush data shows the same thing across industries: early brands that adopt a new AI answer engine optimization strategy quickly start to lock in positions of trust that competitors can’t easily replace. Once your brand becomes the reliable answer source, AI engines will start to default to you for related queries, and the advantage snowballs.

The window to be an early adopter and take AI visibility for your brand will not stay open forever.  As more brands invest in AI visibility, the visibility race is heating up.

Download the Complete AI Search Visibility Audit with detailed assessment frameworks, implementation checklists, and the 8 strategic questions covering content architecture, technical infrastructure, and linguistic optimization. Each question includes specific audit steps and immediate action items to close your visibility gaps and establish authoritative positioning before your market becomes saturated with AI-optimized competitors.

Download the Full Audit

Image Credits

Featured Image: Image by IQRush. Used with permission.

In-Post Images: Image by IQRush. Used with permission.

Ecommerce MGMT 0 Comments
Oct 24 2025
Holiday Email Deliverability: 4 Expert Tips To Reach More Inboxes

This post was sponsored by Campaign Monitor. The opinions expressed in this article are the sponsor’s own.

Does it seem like fewer emails are getting delivered?

Are bounce rates and spam numbers too high for your liking?

Your well-crafted campaigns are at risk.

They are at risk of missing the mark if deliverability isn’t a priority.

Why Are My Email Delivery Scores So Low?

Black Friday, Cyber Monday, and year-end sales push email volume to record highs, prompting mailbox providers (MBPs) like Gmail and Yahoo to tighten spam filters and raise the bar for acceptable sending practices.

How Can I Ensure Marketing Emails Reach Inboxes?

To help your emails reach subscribers when it matters most, our email deliverability experts outline four practical tips for safeguarding inbox placement, without sounding “salesy” or relying on quick fixes.

1. Understand & Strengthen Deliverability For Better Results

What Is Email Deliverability?

Email deliverability refers to whether your message actually reaches the recipient’s inbox.

What Determines Email Deliverability?

Each time an email is sent, the email passes through two critical stages.

Stage 1: Delivery.

  1. Your email is sent to an MBP (e.g., Gmail, Outlook).
  2. It is either accepted or rejected.

Rejections can be hard bounces (invalid addresses) or soft bounces (temporary issues like a full mailbox).

Stage 2: Inbox placement.

Once accepted, MBPs decide whether to:

  1. Place your email in the inbox.
  2. Route it to promotions.
  3. Filter it as spam.

What Causes Marketing Emails To Be Marked As Spam?

The judgment to flag an email as spam depends on:

During peak season, email volume can double or triple, especially around Black Friday/Cyber Monday.

MBPs must guard against spammers, so legitimate senders face stricter scrutiny.

Understanding these mechanics helps marketers avoid being mistaken for unwanted senders and improves inbox placement.

For a deeper dive into how email deliverability works, check out this full guide.

2. Build & Maintain a Strong Sender Reputation

Mailbox providers rely on sender reputation to separate trusted messages from spam.

What Is Sender Reputation?

Two factors determine sender reputation:

  • Audience Engagement. High open and click rates send positive signals. MBPs also track how long recipients read messages, whether they add you to contacts, or delete without opening.
  • List Quality. Permission and relevance are critical. New holiday sign-ups should go through a compliant opt-in process, supported by a welcoming automation that sets expectations.

How Do I Get A Better Sender Reputation?

To keep your reputation strong:

  • Re-engage inactive subscribers early, well before the holiday surge.
  • Remove dormant contacts if they stay unresponsive.
  • Honor unsubscribe requests promptly.

Maintaining this “good standing” ensures your campaigns consistently reach the inbox.

For practical steps, explore best practices for building healthy lists: https://www.campaignmonitor.com/resources/guides/building-an-email-list/

3. Don’t Over-Spice Your Email Program

It’s tempting to send more emails to more people as the holidays approach.

However, sudden changes can trigger spam filters.

MBPs closely monitor sending patterns, and abrupt spikes can undo months of good reputation.

Do:

  • Keep your cadence steady and test any new segments early.
  • Maintain clear, bot-protected signup forms and offer preference options so users can “opt down” rather than unsubscribe entirely.

Don’t:

  • Send to old or inactive lists, or change your sending domain in Q4.
  • Ignore warning signs like falling open rates or rising complaints.

For guidance on email frequency and audience expectations, see Campaign Monitor’s insights on email engagement: https://www.campaignmonitor.com/resources/guides/email-engagement/

4. Monitor Key Metrics Like a Hawk

Even seasoned marketers may see deliverability metrics fluctuate during the holidays. Careful monitoring helps catch issues before they escalate:

  • Bounce rates: Hard bounces above 2% call for immediate action.
  • Complaint rates: Aim for 0.1% or lower to avoid spam folder placement.
  • Opt-out rates: A sudden rise means your frequency or content may need adjustment.
  • Open rates by domain: Consistency across Gmail, Yahoo, and others indicates healthy inbox placement.
  • Reputation signals: Tools like Gmail Postmaster reveal if your domain is being flagged.

Remember that mailbox providers increasingly use AI and machine learning to evaluate sender behavior and content quality. Authentic engagement is key. To learn more about measuring success, visit Campaign Monitor’s email marketing benchmarks: https://www.campaignmonitor.com/resources/guides/email-marketing-benchmarks/

How To Use These Tips To Create High-Deliverability Holiday Email Campaigns

Landing in the inbox is a privilege, not a guarantee, so always be sure to:

  1. Secure explicit opt-in and send only wanted content.
  2. Keep your sender reputation strong with healthy engagement and clean lists.
  3. Avoid sudden changes in cadence or audience.
  4. Watch key metrics and adapt quickly when anomalies appear.

These steps help marketers navigate heavy holiday email traffic while maintaining trust and engagement with subscribers.

Campaign Monitor’s tools can further support these efforts by simplifying list management, automating welcome journeys, and providing detailed reporting, without overcomplicating your workflow.

By combining smart strategy with careful monitoring, you’ll set the stage for a successful holiday season where every email has the best chance to shine in the inbox.

Start reaching more inboxes this holiday season

Image Credits

Featured Image: Image by Campaign Monitor. Used with permission.

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Oct 15 2025
The AI Search Effect: What Agencies Need To Know For Local Search Clients

This post was sponsored by GatherUp. The opinions expressed in this article are the sponsor’s own.

Local Search Has Changed: From “Found” to “Chosen”

Not long ago, showing up in a Google search was enough. A complete Google Business Profile (GBP) and a steady stream of reviews could put your client in front of the right customers.

But today’s local search looks very different. It’s no longer just about being found; it’s about being chosen.

That shift has only accelerated with the rise of AI-powered search. Instead of delivering a list of links, engines like ChatGPT, Google’s Gemini, and Perplexity now generate instant summaries. Changing the way consumers interact with search results, these summaries are the key to whether or not your client’s business gets seen at all.

Reality Check: if listings aren’t accurate, consistent, and AI-ready, businesses risk invisibility.

AI Search Is Reshaping Behavior & Brand Visibility

AI search is already reshaping behavior.

Only 8% of users click a traditional link when an AI summary appears. That means the majority of your clients’ potential customers are making decisions without ever leaving the AI-generated response.

So, how does AI decide which businesses to include in its answers? Two categories of signals matter most:

Put simply, if a client’s listings are messy, incomplete, or outdated, AI is far less likely to surface them in a summary. And that’s a problem, considering more than 4 out of 5 people use search engines to find local businesses.

The Hidden Dangers of Neglected Listings

Agencies know the pain of messy listings firsthand. But your clients may not realize just how damaging it can be:

  • Trust erosion: 80% of consumers lose trust in businesses with incorrect or inconsistent.
  • Lost visibility: Roughly a third of local organic results now come from business directories. If listings are incomplete, that’s a third of opportunities gone.
  • Negative perception: A GBP with outdated hours or broken URLs communicates neglect, not professionalism.

Consider “Mary,” a marketing director overseeing 150+ locations. Without automation, her team spends hours chasing duplicate profiles, correcting seasonal hours, and fighting suggested edits. Updates lag behind reality. Customers’ trust slips. And every inconsistency is another signal to search engines, and now AI, that the business isn’t reliable.

For many agencies, the result is more than frustrated clients. It’s a high churn risk.

Why This Matters More Than Ever to Consumers

Consumers expect accuracy at every touchpoint, and they’re quick to lose confidence when details don’t add up.

  • 80% of consumers lose trust in a business with incorrect or inconsistent information, like outdated hours, wrong addresses, or broken links.
  • A Google Business Profile with missing fields or duplicate entries signals neglect.
  • When AI engines surface summaries, they pull from this. Inconsistencies make it less likely your client’s business will appear at all.

Reviews still play a critical role, but they work best when paired with clean, consistent listings. 99% of consumers read reviews before choosing a business, and 68% prioritize recent reviews over overall star ratings. If the reviews say “great service” but the business shows the wrong phone number or closed hours, that trust is instantly broken.

In practice, this means agencies must help clients maintain both accurate listings and authentic reviews. Together, they signal credibility to consumers and to AI search engines deciding which businesses make the cut.

Real-World Data: The ROI of Getting Listings Right

Agencies that take listings seriously are already seeing outsized returns:

  • A healthcare agency managing 850+ locations saved 132 hours per month and reduced costs by $21K annually through listings automation, delivering a six-figure annual ROI.
  • A travel brand optimizing global listings recorded a 200% increase in Google visibility and a 30x rise in social engagement.
  • A retail chain improving profile completeness saw a 31% increase in revenue attributed to local SEO improvements.

The proof is clear: accurate, consistent, and scalable listings management is no longer optional. It’s a revenue driver.

Actionable Steps Agencies Can Take Right Now

AI search is moving fast, but agencies don’t have to be caught flat-footed. Here are five practical steps to protect your clients’ visibility and trust.

1.  Audit Listings for Accuracy and Consistency

Start with a full audit of your clients’ GBPs and directory listings. Look for mismatches in hours, addresses, URLs, and categories. Even small discrepancies send negative signals to both consumers and AI search engines.

I know you updated your listings last year, and not much has changed, but unless your business is a time capsule, your customers expect real-time accuracy.

2.  Eliminate Duplicates

Duplicate listings aren’t just confusing to customers; they actively hurt SEO. Suppress duplicates across directories and consolidate data at the source to prevent aggregator overwrites. Google penalized 6.1% of business listings flagged for duplicate or spam entries in Q1 alone, underscoring how seriously platforms are taking accuracy enforcement.

3.  Optimize for Engagement

Encourage clients to respond authentically to reviews. Research shows 73% of consumers will give a business a second chance if they receive a thoughtful response to a negative review. Engagement isn’t just customer service; it’s a ranking signal.

4.  Create AI-Readable Content

AI thrives on structured, educational content. Encourage clients to build out their web presence with FAQs, descriptive product or service pages, and customer-centric content that mirrors natural language. This makes it easier for AI to pull them into summaries.

5.  Automate at Scale

Manual updates don’t cut it for multi-location brands. Implement automation for bulk publishing, data synchronization, and ongoing updates. This ensures accuracy and saves agencies countless hours of low-value labor.

The AI Opportunity: Agencies as Strategic Partners

For agencies, the rise of AI search is both a threat and an opportunity. Yes, clients who ignore their listings risk becoming invisible. But agencies that lean in can position themselves as strategic partners, helping businesses adapt to a disruptive new era.

That means reframing listings management not as “background work,” but as the foundation of trust and visibility in AI-powered search.

As GatherUp’s research concludes, “In the AI-driven search era, listings are no longer background work; they are the foundation of visibility and trust.”

The Time to Act Is Now

AI search is here, and it’s rewriting the rules of local visibility. Agencies that fail to help their clients adapt risk irrelevance.

But those that act now can deliver measurable growth, stronger client relationships, and defensible ROI.

The path forward is clear: audit listings, eliminate duplicates, optimize for engagement, publish AI-readable content, and automate at scale.

And if you want to see where your clients stand today, GatherUp offers a free listings audit to help identify gaps and opportunities.

👉 Run a free listings audit and see how your business measures up.

Run A Free Listings Audit

Image Credits

Featured Image: Image by GatherUp. Used with permission.

In-Post Images: Image by GatherUp. Used with permission.

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Sep 24 2025
From SEO To GEO: How Can Marketers Adapt To The New Era Of Search Visibility? via @sejournal, @Semji_fr

This post was sponsored by Semji. The opinions expressed in this article are the sponsor’s own.

For three decades, SEO has been the cornerstone of digital visibility.

Keywords, backlinks, and technical optimization determined whether your brand appeared at the top of search results.

However, the landscape is shifting, and it’s likely that if you’re reading this article, you already know it.

Download The Full Guide

With generative AI tools like ChatGPT, Google AI Overviews, Gemini, or Perplexity, users no longer rely solely on lists of blue links.

Instead, searchers and researchers receive synthesized, conversational answers that draw content from high-authority sources.

The message is clear: ranking alone is no longer enough.

To be visible in the age of AI, marketers need a complementary discipline, Generative Engine Optimization (GEO).

To do so, you need concrete methods and best practices to add GEO efficiently into your strategy.

What Is Generative Search Optimization (GEO)?

Generative Search Optimization (GEO) is the practice of ensuring that your content is selected, understood, and cited by large language models (LLMs) and generative engines.

How Does GEO Differ From Traditional SEO?

Traditional search engines use bots to crawl webpages and rank them.

LLMs synthesize patterns from massive pre-ingested datasets. LLMs and answer engines don’t index; they use them as their conversational padding.

What Is A Pre-Ingested Data Set?

Pre-ingested datasets are content that is pulled from websites, reviews, directories, forums, and even brand-owned assets.

This means your visibility no longer depends only on keywords

What Do I Need To Do To Show Up In AI Overviews & SERPs?

To increase your visibility in LLMs, your content must be:

Put simply: GEO ensures your brand shows up in the answers themselves as well as in the links beneath them.

How To Optimize For LLMs In GEO

Optimizing for LLMs is about aligning with how these systems select and reuse content.

From our analysis, three core principles stand out in consistently GEO-friendly content:

1. Provide Structure & Clarity

Generative models prioritize content that is well-organized and easy to parse. Clear headings, bullet points, tables, summaries… help engines extract information and recompose it into human-like answers.

2. Include Trust & Reliability Signals

LLMs reward factual accuracy, consistency, and transparency. Contradictions between your site, profiles, and third-party sources weaken credibility. Conversely, quoting sources, citing data, and showcasing expertise increase your chances of being cited!

3. Contextual & Semantic Depth Are Key

Engines rely less on keywords and more on contextual signals (as it has been more and more the case with Google these last years–hello BERT, haven’t heard from you in a while!). Content enriched with synonyms, related terms, and variations is more flexible and better aligned with diverse queries, which is especially important as AI queries are conversational, not just transactional.

3 Tips For Creating GEO-Friendly Content

In the GEO guide we’re sharing with you in this article, 15 tips are delivered–here are 3 of the most important ones:

1. Be Comprehensive & Intent-Driven

LLMs favor complete answers.

Cover not just the main query but related terms, variations, and natural follow-ups.

For example, if writing about “content ROI,” anticipate adjacent questions like “How do you measure ROI in SEO?” or “What KPIs prove content ROI?”!

By aligning with user intent, not just keywords, you increase the likelihood of your content being surfaced as the “best available answer” for the LLMs.

Learn how to do this.

2. Showcase E-E-A-T Signals

GEO is inseparable from trust. Engines look for identifiable signals of credibility:

  • Author bylines with expertise.
  • Real-world examples, roles, or case insights.
  • Transparent sourcing of statistics and references.
  • And many more opportunities to prove your credibility and authority.

Think of it as content that doesn’t just “read well,” but feels safe to reuse by the LLMs.

3. Optimize format for machine & human readability

Beyond clarity, formats like FAQs, how-tos, comparisons, and lists make your content both user-friendly and machine-friendly. Many SEO techniques are just as powerful and efficient in GEO:

  • Add alt text for visuals.
  • Include summaries and key takeaways in long-form content.
  • Use structured data and schema where relevant.

This dual optimization increases both discoverability and reusability in AI-generated answers.

Why It’s Essential To Optimize For LLMs

Skeptical about GEO? Consider this: 74% of problem-solving searches now surface AI-generated responses, and AI Overviews already appear in more than 1 in 10 Google queries in the U.S. AI Overviews, Perplexity summaries, and Gemini snapshots are becoming default behaviors in information-seeking. The line between “search” and “chat” is blurring.

The risk of ignoring GEO is not just lower traffic—it’s invisibility in the answer layer where trust and decisions are increasingly formed.

By contrast, marketers who embrace GEO can:

  • Defend brand presence where AI engines consolidate attention.
  • Create future-forward SEO strategies as search continues to evolve.
  • Maximize ROI by aligning content with both human expectations and machine logic.

In other words, GEO is not a trend: it’s a structural shift in digital visibility, where SEO remains essential but is no longer sufficient. GEO adds the missing layer: being cited, trusted, and reused by the engines that increasingly mediate how users access information.

GEO As A New Competitive Advantage

The age of GEO is here. For marketing and SEO leaders, the opportunity is to adapt faster than competitors—aligning content with the standards of generative search while continuing to refine SEO.

To win visibility in this environment, prioritize:

  • Auditing your current content for GEO readiness.
  • Enhancing clarity, trust signals, and semantic richness.
  • Monitoring your presence in AI Overviews, ChatGPT, and other generative engines.

Those who invest in GEO today will shape how tomorrow’s answers are written.

Want to explore the full framework of GEO?

Download the complete guide on Generative Engine Optimization

Image Credits

Featured Image: Image by Semji. Used with permission.

Ecommerce MGMT 0 Comments
Sep 23 2025
SERP Visibility Decline: How To Grow Brand Awareness When Organic Traffic Stalls

This post was sponsored by AdRoll. The opinions expressed in this article are the sponsor’s own.

Text‑heavy AI Overviews blocking your brand?

The “People Also Ask” that you could scroll through forever, effectively hiding position 1?

Knowledge panels and rich snippets hogging the view?

The majority of people who entered a search query never made it past the top of the search result page (SERP) in 2024.

For users, these updates to Google’s SERPs are technically efficient.

For you, changes like AI Overviews are another strategy to master, and at worst, a direct competitor for attention.

So how do you increase brand awareness and search presence when Google is taking away your bids for top-of-funnel (TOFU) content?

The Rise of Zero-Click: Why Rankings Don’t Equal Traffic Anymore

As search evolves, AI-powered summaries now appear in more than 13% of queries.

This resulted in nearly 60% of Google searches ending without a click last year, dramatically shrinking the traditional flow of search traffic to a website.

Not only are you fighting for space against the usual blue links, you’re now competing with AI-generated answers that package everything up before a user even considers a click.

Which means that “we made it to the top” moment doesn’t guarantee anyone actually sees your brand.

So, even if your brand earns a top ranking, it may never translate into visibility. That’s the reality of today’s zero-click environment, and it is what creates the awareness gap — a challenge that every marketer now has to solve.

What Is Zero Click?

A “zero-click” search happens when a user gets their answer directly on the search results page through featured snippets, knowledge panels, or AI-generated overviews without ever clicking through to a website.

For users, it’s fast and convenient. For brands, it means fewer chances for visitors to actually land on your site, even when you’ve earned a top ranking. Think of it as Google (and increasingly, AI) keeping people inside its own ecosystem rather than sending them out to explore yours.

This is where the awareness gap comes in.

What Is The Awareness Gap?

The awareness gap is the space in which your content is seen, but it is not tied to your brand.

Even if your brand appears in these results, you may never see the traditional signals like traffic or time on site that prove your influence. People might recognize your name or absorb part of your story, but that exposure is not reflected in your metrics.

The gap is the difference between being seen and being measured, and closing it requires a new playbook for visibility and recall.

How Zero-Click Reshapes Discovery

The zero-click trend is most disruptive at the very start of the customer journey. Your website used to be Rome; eventually, all roads led there. Now? Fewer and fewer organic roads exist. That means the earliest brand touchpoints are disappearing.

Here’s what that means for marketers today:

  • Fewer chances for discovery. If users never click, they never see your story. All things that shape early perception, such as your messaging, your visuals, your value props, get skipped.
  • SEO loses some steam. While organic optimization still matters for long-term discoverability (hello, LLMs absorbing and citing content), its ability to drive top-of-funnel awareness isn’t what it used to be. In a zero-click world, amazing content may rank, but still never get seen.
  • Competition gets fiercer. If you’ve relied heavily on organic strategies alone, competitors who invest in paid ads are now likely to edge you out. Ads still sit above AI overviews in many results, and that’s prime real estate that’s hard to ignore.
  • Research shifts elsewhere. With crowded SERPs and often confusing AI answers, users are taking their research off of traditional search platforms to other places. Social media, communities, and unowned channels are becoming important sources for educational content that feels clearer and more trustworthy.

Bottom line: the early doors to discovering your brand are closing faster than they’re opening. It takes a new mix of channels to ensure you’re still part of the conversation.

3 Steps to Reclaim Top-of-Funnel Presence

So what’s a marketer to do? Is all hope lost?

Show up where they are still landing: relevant active sites that deliver clear ad space to your target audience.

Advertising offers a direct and reliable solution to the awareness gap.

Unlike organic results, paid campaigns guarantee an immediate and prominent presence on SERPs and other digital platforms. That means eyeballs on your ads, even if a user doesn’t click on them.

Consider paid campaigns as a type of insurance policy against brand invisibility on the SERP.

Remember: early impressions = stronger recall later in the funnel. The power of showing up first cannot be overstated. Even if a user doesn’t click on your ad, the exposure to your name, logo, or key message fosters familiarity. Early recognition makes your brand more memorable when it comes time to convert.

Step 1: Implement An Awareness-Focused Advertising Strategy

If you’ve made it this far, you’re likely nodding along: zero-click is here, and advertising has to play a bigger role. But where do you start? The good news is you don’t need to overhaul everything overnight. Instead, think of paid as a strategic layer that enhances the visibility you’ve already worked hard to build organically.

Here’s the first step in making that shift in a way that feels purposeful, not scattered:

Leverage common queries

Run search and display ads tied to common zero-click queries. Many of the searches most impacted by zero-click are informational: “what is,” “how to,” and “why does” questions that rarely result in clicks. Instead of letting that traffic disappear into AI overviews, run search and display campaigns against these queries. Your brand may not get the click, but it will get the visibility, ensuring you stay part of the conversation even when Google is trying to keep people on the page.

Connect with tomorrow’s customers today. AdRoll makes brand awareness ads work for you. Get started with a demo.

Use what you already know

Build awareness campaigns in categories where your brand already shows up. If you’ve earned a featured snippet or knowledge panel, don’t leave it unsupported. Pair that organic placement with a targeted ad so your brand appears twice on the same page. This kind of overlap creates a halo effect: users perceive your brand as both authoritative and unavoidable. It’s one of the fastest ways to reinforce recall.

Enhance, don’t replace SEO

Paid advertising isn’t a substitute for strong organic presence, it’s an amplifier. Use ads to reinforce your authority and extend the reach of your organic work, not cover for it. Think of the two channels as partners: SEO earns you credibility, while ads guarantee visibility. Together, they create a more holistic visibility strategy that keeps you top of mind across formats and touchpoints. And don’t forget: LLMs and AI overviews are still learning from organic signals. If your content isn’t strong, your ads won’t carry the same weight.

At the end of the day, this isn’t about abandoning what has always worked. It’s about making sure your brand shows up where discovery is actually happening, whether that’s in a blue link, a snippet, or a sponsored placement.

Step 2: Measure Zero-Click Strategies The Right Way

Here’s the tricky part: in a zero-click world, traditional metrics don’t always tell the whole story. If you’re only watching organic traffic, it may look like your efforts are failing. But the reality is that influence is happening upstream, before a user ever lands on your site.

Here’s what to measure instead:

  • Branded search volume. If more people are searching for your brand name specifically, you know your awareness strategy is working. This is often the clearest leading indicator of recall.
  • Visibility share. Track how often your brand appears in SERPs, featured snippets, AI overviews, and paid placements, even if it doesn’t result in a click.
  • Impression lift. Ads may not drive immediate conversions, but consistent exposure increases recognition. Measuring impressions alongside recall surveys can help connect the dots.
  • Engagement on unowned channels. As research moves to social and communities, track where your educational content sparks conversations and shares outside of your own site.

The key is to shift from measuring traffic to measuring presence. Visibility in high-authority spaces, whether through organic or paid efforts, is the new top-of-funnel KPI.

Step 3: Connect The C-Suite To Zero-Click Strategies

Of course, metrics only matter if your leadership team understands them. However, many executives are still trained to see organic traffic as the gold standard. So when traffic dips, even for reasons outside your control, it can look like a problem.

This is where your role as translator becomes critical. You need to reframe the conversation from clicks to visibility, from pageviews to presence. The message to the C-suite should sound less like an apology and more like a strategic shift:

  • A decline in organic traffic doesn’t equal a decline in influence. Zero-click means users may never land on your site, but they’re still seeing your brand. Visibility is impact.
  • Your brand may actually be showing up more often. The problem is measurement, not presence. Snippets, AI overviews, and social conversations don’t show up in traffic charts, but they absolutely shape perception.
  • Advertising fills the gap. Paid campaigns guarantee your brand isn’t invisible at the exact moment prospects are forming their first impressions, making it the perfect complement to organic efforts.

The way to make this stick with leaders is through narrative. Show them that early impressions are building brand memory. Connect branded search growth to that recall. Paint the picture that what looks like “less traffic” is often “more visibility in new places.”

Executives care about competitive positioning and long-term growth, not just line graphs. So remind them: being the brand people remember when it’s time to buy is the real win. Presence is what creates that memory, and memory is what drives future pipeline.

Zero-Click Isn’t the End. It’s Your Advantage If You Move First

Zero-click isn’t the end of marketing as we know it. It’s just the latest evolution in how people discover and remember brands. The marketers who win will be the ones who adapt their strategies, blending organic authority with paid presence, reframing their KPIs, and helping their companies understand what visibility really means today.

The awareness gap is real, but it’s also an opportunity. By rethinking how you measure, how you communicate results, and how you show up at the top of the funnel, you can set your brand up to thrive in an environment where discovery no longer depends on a click.

And this is only Part 1. In Part 2, we’ll dig into the real secret weapon in a clickless world: recall. Because the brands that stay top of mind are the ones that get chosen later. Advertising’s biggest power isn’t in driving a click, it’s in building the kind of recognition that lasts.

Check back soon on the AdRoll website for Part 2: How to Build Recall in a Clickless World.

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Image Credits

Featured Image: Image by AdRoll. Used with permission.

In-Post Images: Image by AdRoll. Used with permission.

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