impact as a marketing channel: Its influence extends beyond the traditionally tracked session https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/
when current, factual info is needed, meaning SEO is also vital for it 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 - SEO Consultant & Founder at Orainti & SEOFOMO 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.
based on top performers patterns, research and what specialists shared in the State of AI Search https://hub.seofomo.co/surveys/state-ai-search-optimization/
& conversions and start measuring AI presence, readiness and business Impact BRAND RECALL DIRECT CLICK CHECKOUT & AGENTIC COMMERCE AI SEARCH TRAFFIC DECISION IN AI PLATFORM PURCHASE IN AI PLATFORM INDIRECT & MULTI-TOUCH WEBSITE VISIT AI SEARCH REVENUE By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO OFF PLATFORM INFLUENCE
Business Impact 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 be surfaced? Explains why visibility is weak, strong, or unstable; the diagnostic layer Diagnostic KPIs Diagnosis and prioritization Connects AI search activity to commercial outcomes without overclaiming attribution Outcome KPIs Executive reporting and decision-making 3. Business Impact Are visibility and readiness translating into value? to By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO
the answers that matter, and how is it represented when it does? By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 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
purchase decisions across the SaaS customer journey By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO Pattern Example prompt Category Specific software category / subcategory “What are the best project management tools for marketing teams?” Use case Job to be done / business challenge “What software can help a remote team manage projects, resources, and deadlines?” Capabilities Features / functionality / technical requirements “Which CRM platforms offer lead scoring, workflow automation, and revenue attribution?” Price Budget / value / pricing model “What is the best accounting software for a small business under €50 per month?” Trust Security / compliance / reliability / support “Which customer-data platforms are GDPR-compliant and offer EU data hosting?” Implementation Integrations / migration / onboarding / time to value “Which CRM is easiest to migrate to from Salesforce and integrates with HubSpot?” Comparison Vendor / product / alternative shortlist “Asana vs Monday.com vs ClickUp: which is best for a 100-person agency?” Market Country / language / local availability “What are the best payroll platforms for a company with employees in Spain and France?”
using these 5 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 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 link or linked source. than clickable 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. 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/
to understand your AI readiness / optimization efforts 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 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 how it’s done for SaaS brands 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/
optimization reasons behind your AI visibility gaps https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/ 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
these questions Accessible Useful Recognizable Extractable Consistent Can the relevant pages be reached and fetched reliably by AI crawlers? Does the content solve the user need competitively — better than what else is on the first page of AI answers? Are brand and entity signals explicit (name, category, founder, HQ, funding, product lines) and machine-readable? Are key answers, positioning, and differentiators easy to parse and summarize from the page? Do those entity signals match across site, Wikipedia/Wikidat a, LinkedIn, review sites, and press? Corroborated Credible Differentiated Fresh Transactable Do multiple independent third-party sources reinforce the same positioning and claims? Do the sources that reinforce the brand carry weight (recognized publications, analyst coverage, peer-reviewed or primary data)? Is the positioning clear, specific, and ownable — or is the language interchangeable with competitors? Is the content recent enough (publish/update dates, current facts, live pricing) to remain credible and citable? Are pricing, plan logic, feature comparisons, and evaluation surfaces clear enough that AI systems can answer “which plan fits my case” questions? https://www.aleydasolis.com/en/ai-search/ai-search-winning-brands-characteristics/
a SaaS site 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/
biz impact via 3 metrics layers Observed Proxy (own & third party) Modeled 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. 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/
AI search business impact Observed Proxy (own & third party) Modeled 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? 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. 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/
readiness efforts ROI AI-referred sessions Shows whether known AI traffic is growing or shrinking. Remember this is the floor, not the ceiling. Branded search / direct / surfaced page demand AI conversion rate / revenue per visit Shows whether known AI traffic is growing or shrinking. Remember this is the floor, not the ceiling. Survey AI discovery rate AI-assisted conversions Shows whether AI contributes to conversion paths even when it is not the final click. Third-party AI traffic share vs. peers Detects recall and downstream demand effects beyond measurable referrals. Surfaces AI influence on users who arrive via branded or direct, otherwise invisible. Shows whether observed growth is share-taking or category-riding. Flat share during category growth = loss. Third-party prompt samples per top landing page Third-party AI platform mix vs. peer average Modeled influenced pipeline / revenue Fills the gap analytics cannot: what question triggered the traffic. Drives prompt set updates and page fixes. Surfaces platform specific risks and opportunities early. Over indexing on one platform is a fragility signal. Useful for planning, never for proof. Overclaiming here erodes trust in the whole dashboard. 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/
biz KPI for SaaS 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/
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/a-3-layer-framework-to-measure-ai-presence-readiness-and-business-impact-redefining-metrics-for-the-ai-search-era/
Metrics for the AI Search Era” guide going through it with examples 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/
for products The best cited AI brands provide full topic graphs to safely recommend them under diverse constraints. By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 1. For each product line, define a topical map: Core category (e.g. “CRM software”), subcategories (sales CRM, enterprise CRM, small-business CRM), use cases, capabilities, integrations, alternatives, etc. 2. Cover all decision dimensions , not just popular queries (Use cases, company size, industry, required capabilities, integrations, constraints, trade-offs, risks, edge cases, etc.) 3. Create topic-level summaries above feature-, use-case-, and integration-level content. 4. Assess & monitor topic completeness gaps : % of subtopics covered, % of features with complete information, % of integrations documented, % of ICPs and decision scenarios addressed, etc.
authority, and content across the SaaS customer journey • • • How-to Guides & Tutorials Thought Leadership & Expert Advice Educational Guides & Glossaries Original Research & Industry Insights Templates, Frameworks & Best Practices Decision • • • • • Comprehensive Product & Feature Pages Pricing & Plan Pages Demos, Free Trials & Product Tours Case Studies by Use Case, Industry & ICP Security, Compliance, Migration & Implementation Content Consideration Use Case & Industry Solution Pages Reviews & Customer Testimonials Comparisons & Alternatives Feature & Integration Content Community & Forum Discussions • • • • • Adoption & Support • • • • • • By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO Onboarding & Implementation Guides Knowledge Base & Troubleshooting Content Integration & API Documentation Training Resources & Video Tutorials Customer Community & Support Forums Product Updates & Release Notes
now directly influence which product gets selected: AI systems pull reasoning from this content when recommending solutions By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 1. Create expert-authored category guides, “Which software should I choose?” comparisons, alternatives pages, use-case explainers and trade-off content. 3. Maintain consistency between guides and product, feature, integration and pricing pages. 2. Explicitly connect products, plans and features with relevant use cases, ICPs, requirements and constraints.
effort, etc. To Avoid To Prioritize Brand and entity pages Original market, audience and usage research Evidence led comparisons and selection guides Standalone commodity definitions without brand or journey context High volume tangential topics without a credible business journey Transaction and task-completion pages Live first-party databases and reference hubs Personalized tools using live or proprietary data Rehashed explainers and how to guides without original value Biased or mass produced ‘best’, comparison and alternatives pages Official product documentation, specifications and policies Documented customer outcomes, experiments and case studies Curated community and practitioner knowledge Fragmented FAQ and keyword variant pages serving one intent Generic calculators, quizzes and generators without distinctive inputs First-hand product tests and performance reviews Product specific implementation and troubleshooting guides Original reporting and source analysis Third-party news and press release rewrites without original input Programmatic pages built from public or competitor data https://www.aleydasolis.com/en/ai-search/content-prioritization-ai-search/
no longer the unit of value but extractable modules are. By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 1. Structure content with: Lists, Tables, Clear headings, Short factual paragraphs 3. Make tradeoffs explicit (“best for / not ideal for”) 2. Separate: Facts, Explanations, Comparisons, Policies
gate AI systems use brand consistency and external validation to reduce recommendation risk By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 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
link building, community & digital PR Link Building Backlinks from related, authoritative sites reviewing relevant businesses Digital PR Positive coverage, citations, backlinks from Media Sites Community Management Positive mentions from relevant social platforms and communities Branding Mentions, promotion, visibility alignment with brand positioning and voice By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO
evidence for SaaS brands, so it’s fundamental to assess where your specific citations come from https://www.aleydasolis.com/en/ai-search/saas-ai-search-optimization/
biz value, etc. To Avoid To Prioritize Independent first-hand reviews and tests Specialist editorial coverage and original reporting Complete marketplace, retailer and reseller listings Generic brand mentions with no clear evidence role Promotional guest posts or sponsored articles repeating brand claims Evidence-led comparisons and recommendation shortlists Expert commentary, interviews, podcasts and event coverage Partner, integration and ecosystem documentation Reach first coverage on irrelevant generalist sites Generic social posts and short-form clips without demonstration Practitioner demonstrations and task led tutorials Data-led articles and reports citing first-party research Third-party case studies and customer stories Syndicated press releases and copied announcements Low-quality directory and profile creation Authentic community Q&A and troubleshooting discussions Detailed customer reviews and maintained review profiles Industry directories, credentials and local or vertical profiles Thin best of listicles and paid inclusions without methodology Manufactured reviews, astroturfed discussions and undisclosed endorsements https://www.aleydasolis.com/en/ai-search/third-party-citation-optimization-ai-search/
shifts & your own optimization context Crawlability Different bots/user agents for which you might have specific crawlability rules Indexability Relevance Lack of CSR JS support by AI bots Differences in User Search Behavior / Intents to further expand your site topical authority targeting the full journey By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO Popularity Metrics/Goals Bigger Role of third-party Citations / Mentions From Performance (traffic, conversions) only to Brand (visibility, sentiment, share of voice) and Performance metrics and goals
based on impact & effort 1. How much are AI platforms already bringing to your revenue and impacting marketing goals? 4. How’s your content already optimized for relevant AI search topics? What’s the gap vs competitors? 2. How do your AI search behavior differ from traditional search? 5. How do the needed optimization actions overlap with existing or planned SEO, Digital PR & Community management efforts? What additional actions / investments are needed? By Aleyda Solis - SEO Consultant & Founder at Orainti & SEOFOMO 3. What’s your traffic, visibility, sentiment and traffic from relevant topics vs competitors in AI platforms? What’s the gap and growth opportunity? 6. What’s the ROI from the additional efforts? Are they worthy? Prioritize accordingly!
& 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 - SEO Consultant & Founder at Orainti & SEOFOMO
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