The Winning Global AI Search Strategy Playbook

Transcript

1. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF The Winning Global AI Search Strategy Playbook
2. Welcome to the state of Google SERPs in 2026, Powered by AI Overviews, SERP Features and Ads above the fold BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
3. https://www.advancedwebranking.com/free-seo-tools/google-serp-features The integration of AIOs has steadily grown for all intents & markets in SERPs DESKTOP MOBILE
4. https://blog.google/products-and-platforms/products/search/search-io-2026/ Even if Google hasn’t flip the AI Mode switch, it’s rebuilding the search doorway to become a flexible AI-assisted journey with their intelligent search box
5. https://blog.google/products/ads-commerce/google-marketing-live-search-ads/ Google is also expanding their ads formats and integration for what they call the “AI era of search”
6. https://blog.google/products-and-platforms/products/shopping/google-shopping-cart/ This is happening while Google also releases a new Universal Cart experience taking new steps toward agentic commerce
7. https://sparktoro.com/blog/in-2026-less-than-one-third-of-google-searches-still-send-a-click/ The outcome of all this is that only ⅓ of Google searches end up in a click
8. https://sparktoro.com/blog/zero-click-searches-highest-in-the-uk-lowest-in-germany-and-france-has-the-most-efficient-searchers/ Not only in the US, but across the UK and European markets as well
9. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF We can expect search traffic to continue dropping due to AI search further integration & nature
10. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF AI search act as a decision engine, is both a branding & performance channel, and transactions are directly moving into AI platforms
11. https://storage.googleapis.com/gweb-uniblog-publish-prod/documents/AI-Mode-US-Insights.pdf In the recently shared AI Mode trends usage by Google, it’s shown how people are engaging more and using it directly for decision making
12. So if sites are getting less search traffic due to AI experiences & are expected to get even less: Does it mean SEO is dead? BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
13. SEO is not dead. AI search rely on grounding when current, factual info is needed, meaning SEO is vital. LLMs Answers Retrieval / Grounding Data For dynamic, factual queries In “search mode” (like ChatGPT’s browsing) the model goes beyond static memory, retrieving real-time external information using it as grounding to produce more accurate, up-to-date answers. Pre-training Data For General knowledge Publicly available text (websites, books, papers, code, forums, etc.) and licensed/curated data, until the model’s knowledge cutoff date. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
14. So, good SEO is good GEO. But is it enough? What about AI shifts and traffic loss? https:/ /developers.google.com/search/docs/fundamentals/ai-optimization-guide
15. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF Let’s see how to grow your brand by taking AI search shifts into account 1. Stop tracking rankings, traffic & last-click conversions and start measuring AI presence, readiness and business Impact 2. Create content for topical completeness, rather than product keyword targeting 3. Optimize for brand authority and trust as a ranking gate
16. Metric Layer Why it matters KPI Roles 1. Presence Are you actually appearing, and how? Replaces traffic-only thinking with visibility and representation measurement Visibility KPIs Optimization and monitoring 2. Readiness Are you structurally prepared to be surfaced? Explains why visibility is weak, strong, or unstable; the diagnostic layer Diagnostic KPIs Diagnosis and prioritization 3. Business Impact Are visibility and readiness translating into value? Connects AI search activity to commercial outcomes without overclaiming attribution Outcome KPIs Executive reporting and decision-making 1. Measure search across AI Presence, Readiness & Biz Impact not just traffic BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
17. BRAND RECALL AI SEARCH REVENUE AI SEARCH TRAFFIC OFF PLATFORM INFLUENCE DECISION IN AI PLATFORM WEBSITE VISIT INDIRECT & MULTI-TOUCH AI SEARCH VISIBILITY PURCHASE IN AI PLATFORM DIRECT CLICK Influence happens without a click, AI search is both a branding & performance channel, and traffic fails to reflect it CHECKOUT & AGENTIC COMMERCE BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
18. https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/ Similarweb found users were 2.5x more likely to visit the AI recommended brand over competitors
19. https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/ When users visit AI recommended brands, Search is the dominant channel: users remember the brand and actively seek it out.
20. https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/ Attribution models have a blind spot: AI traffic also arrives via search & direct
21. Start by monitoring AI presence: Is the brand shown in the answers that matter, and how is it being represented when it does? Presence KPIs Question it answers How to calculate 1. Prompt coverage Are we showing up where we need to? Prompts where brand appears ÷ total tracked prompts 2. Recommendation rate Are we being endorsed, or just included? Appearances where AI explicitly recommends ÷ appearances 3. Linked citation rate Is this visibility capable of driving visits or purchases? Appearances with a clickable link ÷ appearances 4. Comparative win rate Are we winning the shortlist when users compare options? Comparison prompts won ÷ comparison prompts where brand appears 5. Representation accuracy Are we being understood properly, or misrepresented? Factually correct appearances ÷ appearances BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
22. https://www.aleydasolis.com/en/ai-search/ai-search-prompt-library/ A representative prompt library is critical for an accurate view of your AI presence
23. Track presence creating prompt libraries that reflect the full customer journey for product lines & personas Constraint / dimension Pattern Example prompt Category Specific product/subvertical “Best sites to buy running shoes online in the US?” Use case Purchase situation “Best running shoes for beginners training for a 10K?” Attributes Fit, specs, material, ingredients “Best non-comedogenic moisturizers for oily skin?” Price Budget / value / premium “Best wireless headphones under $150?” Trust Safety, authenticity, warranty, returns “Is Back Market reliable for refurbished iPhones?” Logistics Shipping, stock, delivery, returns “Where can I buy a dishwasher with delivery this week?” Comparison Retailer / product / brand shortlist “Amazon vs Walmart for buying baby products online?” Market Country / language / local availability “Best online fashion stores in Spain with easy returns?” https://www.aleydasolis.com/en/ai-search/ai-search-prompt-library/
24. Bing Webmaster Tools, Similarweb We’re getting more AI search behavior data now that we can use as an input
25. https://www.aleydasolis.com/en/ai-search/ai-search-prompt-library/ Start with a minimum viable representative AI search prompt library to reveal patterns 1. Start with 30 to 50 commercially relevant prompts. Group them by product or service line, audience, market, language and journey stage. 2. Make sure the prompts reflect business priorities. Include the products, services, markets, audiences and conversion paths that matter most right now. 3. Add realistic buyer constraints. Use constraints such as budget, location, use case, industry, integrations, urgency, trust requirements, feature needs or preferences. 4 .Use real audience language where possible. Pull from search demand, GSC long-tail queries, People Also Ask, internal site search, sales calls, CRM notes, support tickets, reviews, communities and AI-related data sources. 5. Run the first set across the top 2-3 platforms. Begin with the AI search platforms most relevant to your audience instead of trying to test everything at once. 6. Record the core visibility signals. Track whether your brand appears, whether it is recommended or only mentioned, whether it is cited or linked, which competitors appear, which sources shape the answer and whether the brand is represented accurately.
26. https://www.aleydasolis.com/en/ai-search/ai-search-prompt-library/ I’ve created a Representative AI Search Prompt Library Workbook to help you
27. https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/ Measure your brand AI presence using these 5 minimum KPIs for key questions AI Presence KPIs What it measures Prompt coverage Are we showing up where we need to? Measures whether the brand appears at all across the prompts that matter. Recommendation rate Are we being endorsed, or just included? Measures whether the brand is actively recommended when it appears, rather than simply mentioned in a list or cited in passing. Linked citation rate Is this visibility capable of driving visits or purchases? Measures how often the brand is not only mentioned but also cited with a clickable link or linked source. Comparative win rate Are we winning the shortlist when users compare options? Measures how often the brand is framed as the stronger or preferred option in prompts where multiple brands are evaluated against each other. Representation accuracy Are we being understood properly, or misrepresented? Measures whether the brand is described correctly when it appears: what it does, who it is for, and why it is relevant.
28. AI Presence KPIs What to learn / action Prompt coverage Shows whether the brand appears at all where it matters; low values point to visibility or distribution gaps Recommendation rate Shows whether the brand is actively endorsed; low values often point to trust, corroboration, or differentiation gaps Linked citation rate Shows traffic opportunity, not just awareness; low values often point to extractability or page-structure gaps Comparative win rate Shows whether the brand is framed as the stronger option; low values often point to positioning or proof gaps Representation accuracy Shows whether the brand is being described correctly; low values point to entity clarity or consistency issues Each AI search presence KPI should help to focus your AI readiness / optimization efforts https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
29. Readiness explains the structural optimization reasons behind AI visibility gaps Weak category visibility often points to Corroborated, Differentiated, or Useful gaps Weak recommendation rate often points to Credible, Corroborated, or Differentiated gaps Poor representation accuracy often points to Recognizable or Consistent gaps Weak commercial visibility often points to Transactable, Extractable, or Useful gaps https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
30. Can the relevant pages be reached and fetched reliably by AI crawlers? Accessible Does the content solve the user need competitively — better than what else is on the first page of AI answers? Useful Are brand and entity signals explicit (name, category, founder, HQ, funding, product lines) and machine-readable? Recognizable Are key answers, positioning, and differentiators easy to parse and summarize from the page? Extractable Do those entity signals match across site, Wikipedia/Wikidat a, LinkedIn, review sites, and press? Consistent Do multiple independent third-party sources reinforce the same positioning and claims? Corroborated Do the sources that reinforce the brand carry weight (recognized publications, analyst coverage, peer-reviewed or primary data)? Credible Is the positioning clear, specific, and ownable — or is the language interchangeable with competitors? Differentiated Is the content recent enough (publish/update dates, current facts, live pricing) to remain credible and citable? Fresh Are pricing, plan logic, feature comparisons, and evaluation surfaces clear enough that AI systems can answer “which plan fits my case” questions? Transactable Assess & measure 10 key AI readiness characteristics by asking these questions https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
31. Here’s an AI Search Readiness Checklist to use, with relevant tools & how to verify each https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
32. With your AI presence & readiness, you can assess biz impact via 3 metrics layers Metrics from platforms passing a referrer or a UTM. Highest confidence, lowest coverage. Eg. AI referred sessions, AI conversion rate, revenue per AI visit, AI-assisted conversions. Directional signals from your own analytics or tools that sample AI traffic across the web. Medium to medium-low confidence, broader coverage. Eg. 1. Own: branded search lift, direct/unattributed lift, demand for pages known to be surfaced in AI answers, survey-based discovery. 2. External: Similarweb AI traffic behavior vs. competitors, prompt samples per page, etc. Estimates produced by applying assumptions to observed and proxy data. Lowest confidence, used for planning, never for proof. Eg. influenced pipeline, influenced revenue, incrementality estimates. Observed Proxy (own & third party) Modeled https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
33. Metrics from platforms passing a referrer or a UTM. Highest confidence, lowest coverage. Directional signals that correlate with AI influence but do not prove it. Medium to medium-low confidence, broader coverage. Estimates produced by applying assumptions to observed and proxy data. Lowest confidence, used for planning, never for proof. Observed Modeled Proxy (own & third party) Question: How many users clicked and converted from an AI answer? Question: 1. Own: Is there evidence users are seeing us in AI answers even when they do not click? 2. Third Party: How does our AI presence compare to competitors and which prompts are driving AI traffic? Question: If we assume X% of branded search lift is AI-attributable, what is the implied pipeline? Each metric layer answers a question to help assess your AI search business impact https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
34. AI sessions by platform, landing page, device, and product line. Engagement rate and average engagement time vs. organic / shopping benchmarks. AI conversion rate, AOV, and revenue per visit by platform, where volume allows. AI-assisted add-to-carts, checkouts, purchases, and revenue. Top AI landing pages: category, PDP, guide, and comparison pages. Track these observed metrics to measure your AI biz impact with the highest confidence although lowest coverage https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
35. The observed layer is the floor. Proxy metrics fill some of the ceiling. They should follow a pattern consistent with an AI story. Own Site Proxy Signals How to use them Branded search trend GSC query report filtered to brand terms, or the native branded/non-branded toggle. Track week-over-week and month-over-month. Direct and unattributed traffic trend GA4 Direct channel, especially to pages that are not shared in email or paid campaigns. Demand for frequently-surfaced pages Impressions and direct/organic traffic to the pages you have verified are being cited in AI answers. Survey-based discovery One question added to signup, demo, or post-purchase flows Bing Webmaster Tools AI Performance First-party citation counts, cited URLs, and grounding queries for Microsoft Copilot and Bing AI summaries. The only first-party citation data available from any AI ecosystem today. Social listening on brand mentions in AI-adjacent contexts Reddit, LinkedIn, Slack communities where “has anyone used X?” conversations happen. https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
36. Eg. Add one AI survey discovery question and use incrementality selectively: “Did you come across your brand in an AI assistant before buying?” https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
37. Third party proxies like Similarweb or Semrush data can also directionally fill competitors & prompts behavior for relative reads https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
38. https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/ Here are 3 third-party proxies reads worth running monthly 1. Prompt samples driving traffic to your top AI landing pages. Use it to: • Extend your Presence prompt set • Diagnose landing-page mismatch • Inform Readiness work 2. Competitive benchmarking of AI traffic share, top landing pages, and top prompts per page. Use it to assess: • AI traffic share trend vs competitors over time • Which pages competitors are getting AI traffic to and which are distinctively yours. • Prompt overlap per page vs competitors 3. AI platform mix over time, benchmarked. Which AI platforms refer traffic to your site and to competitors. Use it to assess: • Platform specific decay • Platform specific wins • Catch category shifts early
39. https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/ Finally, build the business impact modelled layer to estimate what you can’t measure directly (Incremental branded clicks, visits, leads, or pipeline above baseline) × (stated AI influence assumption %) = modelled influenced value
40. https://www.aleydasolis.com/en/ai-search/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/ Here’s an example of how a modelled estimate would work in practice
41. Each biz KPI should help understand your AI search presence & readiness impact Shows whether known AI traffic is growing or shrinking. Remember this is the floor, not the ceiling. AI-referred sessions Shows whether known AI traffic is growing or shrinking. Remember this is the floor, not the ceiling. AI conversion rate / revenue per visit Shows whether AI contributes to conversion paths even when it is not the final click. AI-assisted conversions Detects recall and downstream demand effects beyond measurable referrals. Branded search / direct / surfaced page demand Surfaces AI influence on users who arrive via branded or direct, otherwise invisible. Survey AI discovery rate Shows whether observed growth is share-taking or category-riding. Flat share during category growth = loss. Third-party AI traffic share vs. peers Fills the gap analytics cannot: what question triggered the traffic. Drives prompt set updates and page fixes. Third-party prompt samples per top landing page Surfaces platform specific risks and opportunities early. Over indexing on one platform is a fragility signal. Third-party AI platform mix vs. peer average Useful for planning, never for proof. Overclaiming here erodes trust in the whole dashboard. Modeled influenced pipeline / revenue https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
42. Tying AI presence, readiness & biz KPIs is what drives AI understanding & action Metric How to select it What to learn / action Low readiness + low visibility Structural conditions are holding the brand back. Prioritize access, extractability, entity clarity, corroboration. High readiness + low visibility Brand is underdistributed or underrepresented in the source ecosystem. Focus on source presence, distribution, trust ecosystem, competitive disadvantage. Visibility improving + impact flat Brand is appearing but not memorably, persuasively, or on the right pages. Improve recommendation quality, linked citations, memorability, landing-page fit. Strong informational + weak commercial visibility Visible early in the journey but not winning shortlist or selection moments. Improve commercial prompt coverage and transaction-ready surfaces. High visibility + strong recommendation + weak representation accuracy Being talked about but described wrong. Entity and source correction: Wikipedia/Wikidata, schema consistency, review sites, supplier pages, analyst briefings. One segment strong, another weak Issue is segment-specific, not brand-wide. Run a segment-specific readiness and source-ecosystem review. https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
43. A lot to digest? Don’t worry, check out my “Success Metrics for the AI Search Era” guide going through it with examples https://bit.ly/4tOjbyJ
44. https://docs.google.com/spreadsheets/d/135MVnhLoxcytDhskhZXfyqg21HQtBJjeQz6DNObrCYg/edit?gid=519624647#gid=519624647 I’ve also added a 3 Layer AI Search Diagnostic & Measurement Workbook
45. 2. Create content for topical completeness, rather than keyword targeting AI platforms need full topic graphs to safely recommend under diverse constraints. 1. For each product line, define a topical map: Core entity (e.g. “women’s road running shoes”), subtypes (daily trainer, long-run, speed, recovery), alternatives, etc. 2. Cover all decision dimensions , not just popular queries (Use cases, constraints, trade offs, risks, edge cases, etc.) 3. Create topic-level summaries above product-level content. 4. Assess & monitor topic completeness gaps: % of subtypes with content, % of products with full attribute sets, % of decision scenarios covered, etc. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
46. https:/ /www.aleydasolis.com/en/ai-search/ai-traffic-citations-research/ Although AI traffic is concentrated in brand-entry and action/task pages, AI citations are much more distributed for validation & evidence
47. You need an “on brand”, topical authority, targeting the full customer purchase journey Consideration * Reviews & Testimonials * Studies & Research * Comparison & Alternatives * Product Q&As * Community & Forum Content Decision * Comprehensive Product Description * Documentation & Manuals * Pricing & Plans Pages * Case Studies * Compliance content * Products How-To Guides & Tutorials * Thought Leadership & Expert Advice * FAQs * New product releases Awareness * Knowledge base articles * Troubleshooting Guides & FAQs * Community & support forum * Video tutorials Post-Purchase Support BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
48. Replace keyword maps with product constraint matrices that align with the decision reasoning performed by AI platforms 1. Re-model demand as jobs × constraints, not queries: • Rows: use cases / jobs-to-be-done • Columns: constraints (price, size, compatibility, delivery, risk, performance, context) 2. Ensure every meaningful intersection is supported by: Product attributes, content modules, filters, internal links 3. Align filters to natural language constraints : “Good for long runs”, “Easy to travel with”, “Soft cushioning” BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
49. Eg. Don’t target "best running shoes 2026", but map against product constraints Take "Marathon training × Cushioning (Max)": You'd ensure you have the product attributes tagged (cushion level: maximum), a content module explaining why max cushioning matters for long distances, a filter like "Soft cushioning for long runs," and internal links connecting the marathon training guide to the product listing. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
50. Informational content investment is hard, but needed for topical authority & getting cited, even for ecom BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
51. You can integrate informational content to support your customer journey & sales BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
52. https://www.aleydasolis.com/en/ai-search/global-ai-search-strategy/ To win in global markets you’ll also need real localization efforts to compete with local players leaders
53. Personalization resilience comes from covering all intents across the customer journey for each personas in each market Cover multiple intents for the same topic, so your content aligns with many personalized subqueries, increasing surface area. Add contextual signals that aligns content with profile-based personalization, segmenting content for specific personas or use cases. Retain attention and engagement with fast, useful content that gives a satisfying user experience since AI search systems refine results based on user behavior, thumbs up/down, etc. This feedback loops into ranking and synthesis decisions for future answers. BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
54. Use EEAT for easy to cite structured, accurate, fresh & authoritative content EEAT Content Quality Checklist
55. Remember this content should be also easily extractable by AI bots Pages are no longer the unit of value but extractable modules are. 1. Structure content with: Lists, Tables, Clear headings, Short factual paragraphs 2. Separate: Facts, Explanations, Comparisons, Policies 3. Make tradeoffs explicit (“best for / not ideal for”) BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
56. Don’t assume this is happening: Top AI platforms have no client-side JavaScript support when crawling at the moment https:/ /www.searchengineworld.com/do-ai-assistants-actually-render-your-javascript-when-grounding-we-put-it-to-the-test
57. https:/ /technicalseo.com/tools/ai-bot-access/ Audit your site content & resources crawlability for each relevant AI bot
58. Rendering Difference Engine Chrome Extension & Sitebulb Default to server-visible HTML for critical content data: From descriptions to reviews
59. This applies to images & videos, that should be crawlable, indexable & relevant BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
60. Use tools like Glippy that validate your site tech optimization for AI systems https:/ /www.glippy.dev/
61. Make your site agent-ready by optimizing what they can see: page screenshots, raw HTML, and the accessibility tree Agent-ready guideline Ecommerce implication Make actions explicit Add to cart, select size, check stock, compare, return, and track order actions should be clearly visible. Keep layouts stable Product info, variants, price, delivery, returns, and CTAs should appear in predictable places across templates. Avoid ghost elements / overlays Pop-ups, transparent layers, or hidden elements shouldn’t cover selectors, filters, cart, or checkout steps. Use semantic HTML Use real buttons, links, labels, selects, and forms so agents can identify and interact with commerce flows. Label forms clearly Checkout, delivery, payment, account, return, and support fields should have connected, descriptive labels. Signal actionability Interactive elements should be visible, large enough, and use clear affordances such as cursor: pointer. Audit the accessibility tree Ensure PDPs, PLPs, guides, reviews, FAQs, and policy pages are machine-readable and structurally stable. https:/ /web.dev/articles/ai-agent-site-ux
62. 3. Optimize for brand authority and trust as a ranking gate AI systems use brand consistency and external validation to reduce recommendation risk 1. Secure third-party mentions and reviews on authoritative sites 2. Ensure consistent brand information across the web 3. Maintain visible customer support, returns, and company info 4. Avoid contradictory claims across channels BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
63. https:/ /ai-visibility-index.semrush.com/ Most of AI citations come from 3rd-parties: Brand recognition and optimization should align
64. Growing 3rd party brand authority is a must via link building, community & PR Digital PR Positive coverage, citations, backlinks from Media Sites Community Management Positive mentions from relevant social platforms and communities Link Building Backlinks from related, authoritative sites reviewing relevant businesses Branding Mentions, promotion, visibility alignment with brand positioning and voice BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
65. It’s critical that brand mentions (and backlinks) also have a positive sentiment and are aligned with your brand positioning SEMRUSH
66. Identify sites used as citation sources for your tracked topics vs your competitors: where do they have presence you don’t? SEMRUSH
67. Cited sources can change meaningfully between platforms & markets, assess each independently https://ai-visibility-index.semrush.com/
68. Semrush See the differences in cited domains in ChatGPT for jeans prompts in US vs UK vs
69. You can’t work on a silo anymore: Alignment with PR & social is fundamental BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
70. Use Buzzabout to assess social presence of your brand & competitors for opportunities BUZZABOUT
71. Need inspiration for PR campaigns that get citations? Check Trending PR Campaigns https:/ /finchling.com/campaigns
72. Use tools like Finchling that scans the news cycle to give relevant PR campaigns ideas Finchling
73. https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/ Align your traditional SEO efforts too! Optimize for your branded terms: Over half of AI influenced visits come via Search
74. You’ll need to expand your SEO efforts based on these AI shifts & own context Differences in User Search Behavior / Intents to further expand your site topical authority targeting the full journey Bigger Role of third-party Citations / Mentions Different bots/user agents for which you might have specific crawlability rules Lack of CSR JS support by AI bots From Performance (traffic, conversions) only to Brand (visibility, sentiment, share of voice) and Performance metrics and goals Crawlability Indexability Relevance Popularity Metrics/Goals BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
75. Here’s an AI search optimization checklist to make all this easier https://www.aleydasolis.com/en/ai-search/ai-search-optimization-checklist/
76. Remember we’re just starting! We still have little data and need to leave space for experimentation and to adapt for shifts to come SEOTesting.com
77. It’s a must to keep up with the latest AI search updates! Use these free resources + https:/ /learningaisearch.com/ + https:/ /seofomo.co/
78. Long Live SEO… for [AI Search / AI Mode / ChatGPT / TikTok / YouTube / Baidu / Any Platform Used for Search] BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF
79. Thanks! Questions? SEO Consultant & Founder ❏ International SEO Consultant & Founder at Orainti ❏ Co-founder at Finchling ❏ Creator of the SEOFOMO & AI Marketers Newsletters ❏ Maker of LearningAIsearch.com & LearningSEO.io Speaker & Author ❏ Author of SEO, Las Claves Esenciales ❏ Spoke at +200 events in +30 countries BY ALEYDA SOLIS FROM ORAINTI & SEOFOMO AT SEARCH ‘N STUFF