Service answerCan you help our brand appear when US shoppers ask AI for product recommendations?
Dahna can improve the product information and evidence that shoppers and search systems can find: clear product pages, useful answers, consistent brand facts and relevant content. Start with the US shopping questions you want to be considered for and record what the selected tools currently show.
The goal is a more understandable, credible brand presence and a usable path to purchase. An agency cannot control which products an external AI system recommends. Prioritize work that also helps your website and ordinary search, then measure AI observations separately from visits and orders.
Share a few real shopping questions and any AI answers that describe your products incorrectly or omit relevant information.
Make the brand easy to describe accurately
Expert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsHow to apply it
Start with information a shopper can verify: what the product is, who it may suit, what it costs and where it is available. Aleyda Solís’ ecommerce guidance helps with that foundation. Louise Linehan’s study examines a different question: how public brand mentions relate to observed AI visibility.
Choose a small set of genuine shopping situations and inspect what the systems say today. Identify wrong facts, missing evidence and unsuitable recommendations separately. Then improve the underlying information and relevant public explanations. A generic article claiming that your product is the best does little to help a shopper compare fit, price, limitations and delivery. The strongest starting point is a product a person can evaluate.
A dated question set, captured answers, cited sources and an issue log distinguishing factual corrections from missing coverage and discretionary recommendations.
Service answerWhy should an ecommerce brand care about AI search, and when is it worth prioritizing?
AI search matters when customers use it to compare products, understand a category or decide what fits their needs. A brand benefits from having clear, accurate information wherever that research leads. It is sensible to include AI discovery in a broader search plan while checking whether it matters for your actual customers.
Begin with work that also improves the store: useful product explanations, current facts and credible evidence. Do not divert a limited budget from a broken checkout or missing product information to an isolated AI visibility campaign. Platform-wide growth stories are context, not a forecast for your brand.
Collect a few real shopper questions and compare the usefulness of your product pages with the sources those tools cite.
Decide which shopping questions deserve AI-discovery attention
US audience researchAthena Chapekis and Anna Lieb on AI-summary clicks
900 US adults · March 2025 browsing; search results reconstructed in April
Pew observed traditional-result clicks on 8% of visits with an AI summary versus 15% without one. The analysis was published July 22, 2025.
Athena Chapekis and Anna Lieb, Pew Research Center
Observational Google-only research across query types. Results were reconstructed later, and shopping intent was not isolated. This is not a causal forecast of lost ecommerce revenue.
Read the source notes and related topicsExpert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
How to apply it
Find out which questions your customers use AI tools to research. Comparisons, product versions and where-to-buy questions are useful places to look. Pew’s research describes broader changes in search behavior; it does not establish how often your own customers use these tools.
Prioritize questions involving product fit, comparisons, current versions, availability and where to buy. Fix wrong or missing information that also affects people visiting the website. Avoid diverting the whole marketing budget because AI appears in industry headlines. The appropriate investment depends on your observed customer journey, current search opportunity and whether the foundational product information is already reliable.
A prioritized AI-discovery question set with customer relevance, current answer quality, underlying source gaps and the practical work that would improve the information.
Published guideWhat is the difference between SEO and GEO for an ecommerce brand?
SEO, GEO, and AEO share one foundation: make the business easy to crawl, understand, trust, quote, and choose. The winning difference is original evidence, not special AI markup.
Open the full guide for the examples and steps.
Keep a shared foundation and separate the observations
Expert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
Platform educationAlan Kent: the product-discovery foundation
Google Search Central · foundational 2021–2022 video series
The selected resources explain getting product information into Search and improving an ecommerce site’s search presentation. Current Google documentation accompanies the older videos.
Alan Kent, presenter in Google Search Central’s ecommerce videos
Platform education rather than an independent brand-results study. Older videos are learning resources; current documentation governs implementation details.
How to apply it
SEO and GEO often require the same underlying work: accurate product facts, useful explanations and pages people can reach. Aleyda Solís and Alan Kent discuss that ecommerce foundation. The work can overlap even though a search result and an AI answer look different.
Report the interfaces separately. A ranked URL, a product-result appearance, a named brand mention and a cited source are different observations. Check whether each leads to a useful destination and whether customers act. An agency can organize these tasks under SEO and GEO, but the labels should not result in duplicate content packages or two teams correcting the same product record independently.
A shared implementation backlog with separate reporting for ordinary search, product results, AI answers, referrals and customer outcomes.
Service answerWhy do AI answers mention competing brands but leave ours out?
Record the exact question, tool, date and cited sources before diagnosing the gap. A competitor may have a more relevant product, clearer information or coverage in sources used for that answer. One result is an observation, not a complete ranking of your market.
Look for a specific gap you can improve: a missing use case, a confusing product distinction or an unanswered comparison. Do not manufacture reviews or buy indiscriminate mentions. Dahna can turn the observation into a focused website and content task, then recheck the same question with the limits recorded.
Save three relevant AI answers and identify one missing fact or useful source in each.
Compare the evidence behind the answer before copying the competitor
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsPractitioner educationSam Oh: make videos answerable and findable
Ahrefs AEO course · official companion lessons
The selected lessons cover YouTube discoverability, brand-gap analysis and tracking AI referrals. They provide a practical learning sequence from content opportunities to measurement.
Sam Oh, Ahrefs educator
Educational guidance, not evidence that a featured technique guarantees citations or sales. Publisher lessons and chapter material were reviewed; full playback was not verified.
How to apply it
Save the question, tool, date and cited sources when a competitor appears. Read those sources to see what they say about the product. Sam Oh’s brand-gap lessons offer a process to explore; Louise Linehan’s study provides broader context about visibility.
A competitor may have clearer product facts, more relevant independent coverage or simply a better match for the prompt. Some differences will remain unexplained. Improve a specific missing answer where the evidence supports it, and repeat observations consistently. Do not assume that reproducing the competitor’s article count or inserting its name into your copy will produce the same recommendation.
A source-level comparison listing observed answers, cited evidence, product fit, verified information gaps and proposed actions with their uncertainty made explicit.
Detailed guideWhat to do when AI search shows the wrong product version
When AI search describes the wrong product version, save the exact answer and compare it with the current product record. Fix inconsistencies on your own pages, then contact any cited publisher that needs a factual correction. Recheck what appears; a source update does not guarantee every AI answer will change.
Read the detailed guideCorrect the product record before chasing every answer
Product-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsExpert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
How to apply it
Identify the wrong detail: an old formula, another size, a discontinued bundle or information from a different market. Glossier’s product page is a useful reference for describing variants clearly. It is not a reported example of an AI error.
Find the most authoritative current record and check the brand site, feed, structured data and support content against it. Explain changes clearly where a historical version remains relevant. Document the sources cited by the assistant and request corrections through appropriate channels when needed. Keep the observation open until a later check shows what changed; publishing a correction cannot guarantee when an external system will reflect it.
A product correction ledger with the wrong statement, exact current fact, applicable version and market, supporting source, changed surfaces and follow-up observations.
Service answerWhat product information should be clear on our website for AI-assisted shoppers?
Make the current product identity, intended use, size, variants, price, availability and purchase conditions easy to find. Explain meaningful differences between similar products and support claims with the evidence the brand can actually stand behind.
Keep these facts consistent across the page, catalog records and media descriptions. A list of ingredients or specifications is not always enough; explain the customer decision those facts support. Avoid promises that the product data cannot justify.
Create one approved product fact sheet and compare it with the page a new shopper reaches.
Write the product facts a careful shopper would verify
Product-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsExpert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
How to apply it
Keep one reliable product record for the current name, version, size, contents, ingredients or materials, supported claims and sales market. Glossier’s variant-specific information shows why a general brand description may leave important questions unanswered.
Keep those facts in readable page content and synchronize the relevant structured data and feeds. Distinguish factual attributes from recommendations about suitability. Include limitations that materially affect a purchase instead of describing every item as universally ideal. Assign an owner and update trigger so a new package or formula does not leave old information scattered across the site.
A maintained product fact sheet with source evidence, variant and market scope, content owner, last review date and the surfaces that depend on each field.
Service answerWhy do search and AI results sometimes show the wrong price or availability?
Check the live product and variant first, then the structured information, feed and source cited in the result. A mismatch may involve stale information, the wrong variant, a reseller or an update delay. The visible symptom alone does not reveal which system is responsible.
Correct the source you control and use the relevant platform's correction or refresh process where available. Record the error and recheck it. A change on your website does not guarantee that an external search or AI answer updates immediately.
Save the incorrect result with its date, URL and product variant, then compare it with the current store record.
Find where the stale commercial information enters the chain
Product-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsPlatform educationAlan Kent: the product-discovery foundation
Google Search Central · foundational 2021–2022 video series
The selected resources explain getting product information into Search and improving an ecommerce site’s search presentation. Current Google documentation accompanies the older videos.
Alan Kent, presenter in Google Search Central’s ecommerce videos
Platform education rather than an independent brand-results study. Older videos are learning resources; current documentation governs implementation details.
How to apply it
Compare the result with the actual item and market being sold. Check the selected variant, storefront, structured data and feed. A different size, currency or expired promotion may explain the mismatch before any deeper investigation is needed.
Correct the source you control and document the old and new values with dates. Inspect the external answer’s cited source when available; it may refer to a retailer or historical page rather than your current store. Use the relevant platform’s correction or refresh tools where appropriate. Avoid promising immediate propagation, and keep the customer-facing purchase information unambiguous while the discrepancy is investigated.
A price-and-stock discrepancy log identifying item, market, source surface, observed value, approved value, corrective action and next inspection date.
Service answerDo reviews and independent brand mentions matter for AI discovery?
Authentic reviews and relevant independent coverage can give shoppers information beyond a brand's own claims. They can also appear among the sources encountered during AI-assisted research. The useful question is whether the contribution helps a real customer understand or evaluate the product.
A paid creator placement is not independent evidence simply because it appears on another website. Disclose relevant relationships and keep paid production separate from editorial judgment. There is no responsible promise that a certain number of mentions will produce recommendations.
Identify one credible place where customers already compare products like yours and consider what useful, truthful contribution you can make.
Make independent experience useful without scripting the verdict
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsProduct-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsHow to apply it
Make current product facts available, then let customers and reviewers describe their own experience. Useful feedback can explain fit and limitations that a specification sheet cannot. Louise Linehan’s study gives context for public brand mentions, without proving that any particular review will earn an AI recommendation.
Invite specific, honest feedback about use, fit and limitations. Do not require a positive conclusion or invent an expert endorsement. Where there is a material commercial relationship, make the disclosure clear. Summarize feedback accurately on your own site with permission and context. Independent mentions may help customers evaluate the product, but their presence does not establish that an AI system will cite or recommend it.
A review and evidence process covering honest prompts, permissions, disclosures, product-version context, factual corrections and a useful route from feedback to product improvement.
Detailed guideCreator videos for ecommerce: supporting search and AI discovery
A useful creator video shows something a shopper struggles to judge from text: texture, size, application or the difference between products. Give the demonstration an accurate title, accessible explanation and matching product link. It can support ecommerce discovery without making AI visibility a promise.
Read the detailed guideGive the video a durable product question to answer
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsPractitioner educationSam Oh: make videos answerable and findable
Ahrefs AEO course · official companion lessons
The selected lessons cover YouTube discoverability, brand-gap analysis and tracking AI referrals. They provide a practical learning sequence from content opportunities to measurement.
Sam Oh, Ahrefs educator
Educational guidance, not evidence that a featured technique guarantees citations or sales. Publisher lessons and chapter material were reviewed; full playback was not verified.
UX researchChristian Holst on product-size clarity
Original usability research · May 30, 2017
Holst reports that shoppers used product images to judge size and sometimes rejected suitable products after misreading scale. The article recommends an image with a familiar size reference.
Christian Holst, Baymard research director and co-founder
A historical observed usability problem, not proof that a particular image will increase your conversion rate. Validate the task on your own store.
Read the source notes and related topicsHow to apply it
Choose a product question worth answering beyond the day the video is posted. Sam Oh’s lessons cover discoverability, Christian Holst’s research highlights visual understanding, and Louise Linehan’s study examines AI visibility. Those sources support different parts of the plan.
Brief the demonstration, verify the product version and publish accurate context alongside it. Link to the relevant product or comparison destination where appropriate and permitted. Track discovery, visits and orders separately, and keep observations from different AI systems distinct. If the video does not resolve a customer uncertainty, adding more distribution will not make it a better answer.
A video brief and measurement record tying the buyer question to demonstrable evidence, accurate metadata, destination, rights and separate discovery and commerce observations.
Service answerShould we create product comparisons and FAQs for AI search?
Create a comparison when customers need help choosing, and an FAQ when a question keeps blocking understanding or purchase. Use meaningful product differences and keep the answer close to the decision. A separate page is justified only when it can add enough useful detail beyond the product or collection page.
A comparison should be accurate about your own products and any alternatives it names. Avoid fabricated tests, unsupported superiority claims and nearly identical FAQ pages for every phrase. The content should earn its place even if no AI tool ever cites it.
Choose one repeated buying question and decide whether it belongs on a product, collection or substantive comparison page.
Write comparisons and FAQs that expose meaningful differences
Product-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsExpert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
How to apply it
Answer questions that come up while someone is choosing: what changed between versions, what is included or which option fits a stated need. Use product facts that let the reader check the answer. A long FAQ that repeats the same sales claim adds little.
Answer directly, then provide enough detail to verify the choice. Link to the exact product, policy or evidence that supports it. If information depends on a market or date, say so. A useful comparison should sometimes help a shopper decide that a product is not suitable. That honesty improves the decision even when it does not produce an immediate order.
A question-and-answer set with primary intent, verified facts, real tradeoffs, supporting links and an owner responsible for future changes.
Service answerDo we need dozens of AI-written articles or a special GEO version of our website?
No. Google says its AI search features do not require special AI text files, a particular content length or special schema. Its guidance still centers on useful, accessible content. Other services may have their own requirements, so evaluate a proposed implementation against the actual destination.
For a small brand, the better first task is often to improve an existing page. An agency should explain which customer question each new page answers and why the current site cannot already answer it. Publishing dozens of variations can consume review time without adding value.
Ask for the customer decision and distinct contribution behind each proposed article before approving a volume-based package.
Require a distinct customer need before creating another page
Expert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsHow to apply it
Ask what each proposed page will help a customer do that existing content cannot. A new title containing AI or GEO does not create a new topic. Aleyda Solís’ product-page guidance is a useful starting point for checking whether the answer belongs on a page you already have.
Improve an existing product or collection page when it can answer the question fully. Add a guide when the topic needs its own explanation, with relevant links and a route to it from the site. Check for overlap before publishing and name someone to maintain the facts afterward.
A proposed-page review showing the primary question, existing overlap, unique information, intended destination, internal links and the reason the page deserves to exist.
Service answerHow do we measure whether GEO helps our brand grow?
Keep three records: what selected AI tools show for relevant questions, what identifiable visits reach the site, and what commercial outcomes the store records. Add voluntary customer feedback about discovery where appropriate. Each record answers a different question.
A citation does not prove a visit, and a referral does not prove incremental revenue. Bot activity is not shopper demand. Compare dated observations and consistent reporting periods, retain unknown traffic, and use the result to choose the next product-information or content improvement.
Build a small repeatable question set and a separate referral-and-orders report; do not collapse them into one visibility score.
Track AI visibility without calling it revenue
US audience researchAthena Chapekis and Anna Lieb on AI-summary clicks
900 US adults · March 2025 browsing; search results reconstructed in April
Pew observed traditional-result clicks on 8% of visits with an AI summary versus 15% without one. The analysis was published July 22, 2025.
Athena Chapekis and Anna Lieb, Pew Research Center
Observational Google-only research across query types. Results were reconstructed later, and shopping intent was not isolated. This is not a causal forecast of lost ecommerce revenue.
Read the source notes and related topicsPractitioner educationSam Oh: make videos answerable and findable
Ahrefs AEO course · official companion lessons
The selected lessons cover YouTube discoverability, brand-gap analysis and tracking AI referrals. They provide a practical learning sequence from content opportunities to measurement.
Sam Oh, Ahrefs educator
Educational guidance, not evidence that a featured technique guarantees citations or sales. Publisher lessons and chapter material were reviewed; full playback was not verified.
How to apply it
Choose a repeatable set of customer questions and record what each tool returns. Note whether the brand is mentioned, a source is cited and the information is correct. Keep those observations separate from the referral visits covered in Sam Oh’s tracking lesson.
Then review identifiable referrals and what those visitors do on the store. Some discovery will not produce a click, and some visits will have no reliable source. Report those gaps openly. Compare purchases, refunds and costs over the same period instead of combining mentions and orders into a single success score.
A report with separate panels for answer accuracy, mention and citation observations, identifiable referrals, verified customer outcomes and measurement limitations.
Service answerWhy does our brand appear in one AI tool but not another?
Different tools and modes can retrieve different sources and produce different answers. The exact question, market context and date also matter. Being mentioned in one answer does not establish consistent visibility everywhere.
Choose the tools and shopping situations relevant to your customers, then record observations consistently. Look for repeated factual or content gaps rather than reacting to every variation. The agency's report should say what was checked and what was not.
Repeat the same useful shopping question in your selected tools and compare the cited evidence, not just whether your name appears.
Compare tools using the same customer situation
Observational researchLouise Linehan’s AI visibility study
Ahrefs · December 12, 2025 · 75,000 brands
The study associates YouTube mentions with AI visibility. Its sample selected domains with DR above 40 and a highest-volume keyword of at least 800 estimated monthly searches.
Louise Linehan, author; Xibeijia Guan, contributor; Ryan Law, reviewer
Correlation cannot establish that buying more videos causes AI recommendations. The dataset is not a US beauty or small-brand sample.
Read the source notes and related topicsUS audience researchAthena Chapekis and Anna Lieb on AI-summary clicks
900 US adults · March 2025 browsing; search results reconstructed in April
Pew observed traditional-result clicks on 8% of visits with an AI summary versus 15% without one. The analysis was published July 22, 2025.
Athena Chapekis and Anna Lieb, Pew Research Center
Observational Google-only research across query types. Results were reconstructed later, and shopping intent was not isolated. This is not a causal forecast of lost ecommerce revenue.
Read the source notes and related topicsHow to apply it
Use the same shopping situation when comparing tools, and record the question, date, location settings and visible sources. Louise Linehan’s cross-platform study and Pew’s Google-only research cover different systems; findings from one should not be assumed to describe them all.
Distinguish a missing mention from a wrong product fact and from a recommendation that is simply unsuitable for the prompt. Repeat a limited set of observations rather than treating one answer as a permanent ranking. Prioritize improvements to underlying product information that help a real customer across tools. Keep tool-specific tactics provisional unless you can show an actual, repeatable benefit.
A comparison log with controlled question wording, tool context, factual accuracy, cited sources, repeated observations and the issue that warrants action.
Service answerCan an agency guarantee ChatGPT recommendations or first place in AI search?
No agency can control an external AI system's recommendations or promise a permanent first position. A useful engagement commits to work the agency can deliver: accurate product content, relevant pages, evidence review, implementation and transparent measurement.
Ask a prospective partner to distinguish an observation from a result it caused. A screenshot of one favorable answer is not a guarantee for other shoppers. Dahna's role is to improve the information and purchase journey within its control, with clear limits on what the work can establish.
Evaluate the proposed deliverables and evidence instead of buying a guaranteed recommendation claim.
Ask what the agency controls and what it can only observe
Expert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
US audience researchAthena Chapekis and Anna Lieb on AI-summary clicks
900 US adults · March 2025 browsing; search results reconstructed in April
Pew observed traditional-result clicks on 8% of visits with an AI summary versus 15% without one. The analysis was published July 22, 2025.
Athena Chapekis and Anna Lieb, Pew Research Center
Observational Google-only research across query types. Results were reconstructed later, and shopping intent was not isolated. This is not a causal forecast of lost ecommerce revenue.
Read the source notes and related topicsHow to apply it
Ask the agency to separate work it controls from outcomes it can observe. It can commit to checking facts, improving pages and reporting results. It cannot choose every external system’s future answer to every shopper.
Ask for the exact wording behind a promised result. Does it refer to one selected prompt, a stable measurement set, a source citation, a brand mention or actual qualified demand? Request the baseline, method, time period and conditions. A credible scope remains useful even when the output of an AI system changes, because it improves product information and supplies evidence for the next decision.
A proposal review distinguishing controllable deliverables, observation methods, outcome targets, uncertainty and any claim the provider cannot substantiate.
Service answerWhat would Dahna do first to improve our ecommerce brand’s AI visibility?
Dahna would start with the product, intended customer and current store, then review a small set of relevant shopping questions. The first scope should address the most useful gap: an unclear product page, inconsistent facts, a missing comparison or a demonstration that customers need.
That first project can bring together website, SEO, content and creator work around the same product information. You should be able to see which pages will change, who handles each task and how the results will be reviewed. Compare that scope and Dahna’s documented experience with what your team needs.
Share your website, priority product and the questions you want US shoppers to understand before they buy.
Start Dahna’s GEO work with a small, inspectable product set
Product-page exampleGlossier: identify the exact formula
US Balm Dotcom page · inspected October 12, 2026
The inspected page distinguishes ingredient lists by flavor and includes original-formula wording. A shopper can inspect a specific product’s information rather than relying on a general brand description.
Glossier’s own product documentation
This is a factual product-page example, not an observed AI-error case or a study of ranking effects. Live product information can change.
Read the source notes and related topicsExpert discussionAleyda Solís on ecommerce SEO and GEO
Official webinar recap · July 2025
The recap emphasizes agreement between visible product information, structured data and Merchant Center feeds. It also discusses useful product-page reviews and expert context.
Aleyda Solís, SEO consultant; Will Critchlow, SearchPilot host
Expert guidance, not a controlled GEO uplift study. We reviewed the official recap, not the complete video transcript. Inclusion in an AI answer remains outside an agency’s control.
Practitioner educationSam Oh: make videos answerable and findable
Ahrefs AEO course · official companion lessons
The selected lessons cover YouTube discoverability, brand-gap analysis and tracking AI referrals. They provide a practical learning sequence from content opportunities to measurement.
Sam Oh, Ahrefs educator
Educational guidance, not evidence that a featured technique guarantees citations or sales. Publisher lessons and chapter material were reviewed; full playback was not verified.
How to apply it
Choose a few important products and the questions people ask before buying them. Dahna can review the pages and current AI answers together, then show you which gaps need attention first. Save the starting information so later changes are easy to compare.
Start with wrong facts, unclear product differences and missing explanations on existing pages. Bring in website, SEO or creator-content work where it helps solve the problem. The proposal should name the pages, assets and checks included, followed by a review of customer questions, relevant visits and purchases.
A first-scope document with selected products, baseline observations, proposed corrections, content needs, owners, acceptance checks and a dated commercial review.