Use this guide to evaluate AEO/AI visibility platforms through concrete questions and scoring criteria. It distills a full vendor workbook into a simple Q&A checklist you can copy into RFPs or internal reviews.
Why this matters
- AI answer engines are a top discovery channel; citations and answers drive real traffic and revenue.
- Visibility is shifting from blue links to in‑answer mentions, citations, and in‑chat shopping.
- Teams need verifiable data (not just synthetic screenshots) across engines, regions, and time.
- Enterprise‑grade ops (security, scale, governance) are mandatory for global brands.
How to use
- Start with the business need that matches your goal.
- Ask the vendor the questions; verify with demos and data.
- Score against the evaluation criteria.
Business need: Insight into actual conversations users are having with answer engines
| Question to ask | Evaluation criteria |
|---|
| How broad is the dataset? Is it available across multiple models? Multiple regions? | The dataset should have data from multiple top answer engines including ChatGPT, Claude, Gemini, and Perplexity and contain well over 100M conversations to reach the proper scale.The dataset should support multiple regions, at least 10. |
| How often is the dataset updated? | The dataset should be updated on at least a weekly basis |
| Are you able to conduct bulk analysis of multiple keywords at once? Can you save keywords? | Must have a simple tool to bulk uploadMust be able to create watchlists |
| Is the data secure? Is it GDPR and CCPA compliant? | Data should be anonymized, aggregated, scrubbed of PII, and compliant with GDPR and CCPA. Panels should be doubly opted-in and fully compliant with all modern privacy laws. |
| Question to ask | Evaluation criteria |
|---|
| Is prompt volume insights used to add suggestions to core prompt analytics? | Real conversation/prompt data is used to suggest additional prompts to track in answer engine insights tool (manual prompting of answer engines to retrieve and analyze data) |
| Is prompt volume able to be analyzed within synthetically generated prompt analysis? Helping to ground the synthetically generated data? | There should be easy ways to see estimated prompt volume in line with synthetically generated prompt analysis or topics |
| Question to ask | Evaluation criteria |
|---|
| Does the system use AI/ML to surface similar prompts based on keywords I’m searching for? | There should be relevant suggestions in the keyword exploration workflow |
| Does the system allow for both phrase and exact matching? | An easy toggle between matching methods |
| Does the system automatically label the keywords and associated prompts? | System should automatically label keywords as “informational” or “transactional” etc |
| Question to ask | Evaluation criteria |
|---|
| Can prompts and topics be automatically generated? | There should be a prompt generation tool built into the platform that automatically creates a set of suggested prompts at the brand level |
| Can prompts be dynamically suggested based on real world prompt data related to your brand? | There should be a tool that is proactivley suggesting new prompts to track based on real world data and prompt volumes |
| Can you track visibility score vs competitors? And you analyze over time periods? | There should be the ability to define competitors and easily track mentions |
| Can you analyze share of voice? | Should be able to configure competitors and measure share of voice (and share of voice rank) |
| Do you have the ability to parse entities? E.G. when analyzing answers, look for companies, products, people, product features, or publication sources | There should be robust entity parsing logic that allows you to narrow you insights down to the specific area of the business that you care about. |
| Are you able to see the prompt and response in a cohesive view? Are you able to also see associated mentions and citations alongside the prompt and answers? | Should be able to dig into a individual prompt and responses.The ability to see associated mentions and citations at the response level |
| Question to ask | Evaluation criteria |
|---|
| Does the prompting engine use the API or the frontend? If it’s the front end? Is web search enabled? | The platform should use the front end of the answer engines with web search enabled to ensure the most up to date and grounded answers. It should not leverage the API. |
| Is there coverage across all 10 major models? | Coverage for ChatGPT, Claude, Gemini, Google AI Overviews, Perplexity, Copilot, Deepseek, Grok, Meta AI, Google AI Mode |
| Is there coverage across all major regions, countries and cities? Can the data be dimensionalized? | There should be coverage across most of the global in order to support global organizations |
| Question to ask | Evaluation criteria |
|---|
| Do you have visibility into the in ChatGPT shopping experience? How is it triggered? | There should be out of the box visibility and tracking should be triggered any time a prompt triggers the AI shopping experience that is related to your products |
| Can you see which images are being referenced in chat? | Platform should pull in the images that were used in the in chat shopping experience |
| Question to ask | Evaluation criteria |
|---|
| Are you able to tag citations by type? For example earned, social, competition, owned or even custom? | Platform should have a level of automated tagging that can be supplemented with custom tagging |
| Are you able to measure both citation count and share? How about mentions of your company when a certain page is cited? | All metrics must be measured automatically by the platform |
| Are citations split out by subdomain? How about by page? | Should be able to see nested subdomains in the platformShould be able to see top cited pages and even the exact text chunks being cited |
| Can you visualize citations in multiple visualizations? | Platform should be able to visualize in data tables, line graphs, 3D relationship graphs and 2D relationship graphs |
| Able to visualized which prompts and topics are triggering which citations? | Platform must be able to see which prompts and topics are triggering which citations |
| Question to ask | Evaluation criteria |
|---|
| What types of data visualizations are available? Charts, line graphs, heatmaps, map overlays? | There should be multiple ways to slice and dice data. It should feel intuitive and easy to use. |
| Are you able to export data? | Should be able to easily export both prompts and answersData should also be accessible via an API |
| Are you able to easily filter across multiple dimensions including prompts, topics, platforms, regions and time period? | Filtering should have powerful logic but be simple to apply |
| Question to ask | Evaluation criteria |
|---|
| Can the platform analyze responses to understand and categorize sentiment? Can you filter across regions, tabs, topics, platform, and time period? | The platform must do this out of the box and it must be easy for any user to do. |
| Is the sentiment categorized in actionable ways such as positive, negative or trending? | The platform must do this out of the box. It must be easy to visualize sentiment. |
| Is the sentiment categorized by theme automatically? | Themes should be automatically generated and it should be easy to drill into the individual prompts supporting the theme |
Business need: A way to monitor and track how web agents use your website
| Question to ask | Evaluation criteria |
|---|
| Is there a way to capture log-level data for AI bot traffic on your website? Can you integrate with CDNs? | Platform should have easy integrations with Cloudflare, Vercel, Amazon CloudFront, Fastly and others |
| Can you integrate without a CDN? E.G directly ingest log data? | Platform should be able to directly integrate via an API with application servers and/or ingest server logs to understand AI interactions with your site |
| Question to ask | Evaluation criteria |
|---|
| Can you track human visits referred from answer engines? Does it integrate with Google analytics to further track conversion data? | Should be able to reliably track ever human referral from answer engines (even if they have an ad blocker on)Easy ways to integrate with Google analytics for full visibility |
| Are you able to ingest and analyze log data from the bots? Can you filter the data? | Should have ability to track and visualize human visits and easily integrate with Google analytics for transaction tracking |
| Can you track bot interactions and bot visits from all major answer engines? | Should be able to track across at least 10 major platforms |
| Question to ask | Evaluation criteria |
|---|
| What types of data can be analyzed in your agent analysis tool? | Track which content AI systems access, understand how your content appears in AI responses, identify content gaps and optimization opportunities, and analyze AI crawling patterns and frequenciesThere should also be easy ways to filter by any relevant dimension, compare time periods and visualize the data |
| Does the tool provide path and page analysis to see which bots are interacting with which pages? | Should provide sankey visualization to showcase which bots are visiting which pages |
| Does the tool automatically identify and classify the various web crawlers hitting your site? How are they classified? | The tool should track all bots and classify them into categories such as AI citations, AI training, and AI indexing |
Business need: Tools to generate new content and optimize existing content for AEO
Platform capability: Net new content generation and tailoring
| Question to ask | Evaluation criteria |
|---|
| Can you generate briefs automatically? Can you automatically create final content from the brief? | Platform must be able to both generate briefs and polished content automatically |
| Can I tailor the content to my brand or a specific audience segment? How about something completely custom? | Must be able to upload a brand kit (or automatically generate and apply one) or define audience segments |
| Can you easily customize the content with a built in editor? | Is there built in version control for each content iteration for easy tracking of progress |
| Can you easily customize the content with a built in editor? | Should be built in editing tools that are easy to use for any member of the team |
| Can I tailor the content to a specific set of prompts or a topic? How about to a particular answer engine? | Must be able to select a particular topic and associated set of prompts to help tailor the content |
Platform capability: AEO optimized content template libraries
| Question to ask | Evaluation criteria |
|---|
| Can you use a template to generate net new content? | The platform should be capable of generating blog posts, listicles, ultimate guides, how-to articles, comparison posts, and product listings |
| Are there content type recommendations built in? | The platform should also use citation data to recommend a template type to use based on the most opportunity for visibility improvement |
Platform capability: A data backed content generation methodology
| Question to ask | Evaluation criteria |
|---|
| How is the content optimized for AEO? What type of intelligence is built in? | Content generation should kick off a robust workflow that starts with analyzing the top performing citation pages (for the selected topic and prompt) for dozens of factors including title length, title semantic patterns, user intent, content type, and tone to identify patterns.It should reference an uploaded brand kit or generate on dynamically. From there is should conduct deep research on article topics - looking at market trends, consumer behavior, technological innovations, controversies, competitive landscape, and future outlook.At this point is should synthesize everything into a proven and researched content brief - in a matter of minutes |
| What dataset does the content generation engine reference? How big is the dataset? | Platform should take a two fold approach. They should look at ALL of their data to understand the format and structure, then they should look at the top citations for the specific topics/prompts the content is being for and build the content based on that structureThe dataset should be capable of leveraging hundreds of millions of citations |
| How are you confident that the generated content will perform? Do you have customer proof points? | Listen for customer win stories and examples of generated pages being heavily cited in a specific topic category - there should be tangible win stories |
Platform capability: Optimize existing content
| Question to ask | Evaluation criteria |
|---|
| Do you have a utility to optimize a URL slug for AEO purposes? | There should be a simple utility for optimizing a URL slug for maximum AEO visibility |
| Can you automate the surfacing of content opportunities? | The platform should scan your domain and surface AEO optimization opportunities automatically |
| Can I optimize existing content on my site for AEO? | The platform should allow for use a massive dataset to generate best practices that are baked into the content optimizer.You should then receive detailed set of recommendations for actionable content updates |
Business need: Enterprise capabilities that can scale with large businesses
| Question to ask | Evaluation criteria |
|---|
| Is all customer data encrypted at all times? When is data backed up? Are third-party pen tests conducted regularly? | All customer data must be encrypted both at rest and in transitDaily automated backups must be performedRegular third-party penetration tests must be conducted |
| Do employees undergo privacy and security training? | All employees should have required security and privacy training |
| What security certifications do you have? | At least SOC 2 type 1 certified. Also GDPR and CCPA. |
| Question to ask | Evaluation criteria |
|---|
| Are you able to support multiple brands (with differing use cases) in a single platform? | There should be a way to way to split prompts up among assets or brands |
| Do you have a global customer base? Do you support data capture in multiple languages? | The company should have multiple international customers and the ability to prompt in multiple languages |
| Have you worked with any Fortune 25 multinational organizations? Which ones? | The team should be able to share multiple examples from working with massive organization |
| Question to ask | Evaluation criteria |
|---|
| How many daily prompt executions are you capable of running? | Should be capable of up to 6,000,000 daily executions per customer |
| Are you able to run prompts across every permutation (region, brand, model) simultaneously? | Platform must handle millions of daily executions across multiple regions, brands, and models |
Business need: A proven and capable customer success & engineering practice
| Question to ask | Evaluation criteria |
|---|
| What teams can I interface with daily? | You should have access to a day to day operations role as well as a consultative contact |
| How do I engage with the CS team? | The CS team should be available via Slack, phone, zoom, email, and more |
| Do you have a dedicated AI strategy team? What do they do? | There should be a respected and tenured AI strategy team who is able to support teams with bespoke analysis |
| Question to ask | Evaluation criteria |
|---|
| How often is your team delivering new enhancements and features? Can I see a changelog? | The team should be delivering an enhancement or feature at least every day and they should be able to show you a representative changelog |
| Do you have an in house data science team? | There should be dedicated data science teams with significant experience handling massive dataset |
| What is the caliber of your engineering and data science teams? | You should hear names from leading technology companies such as Uber, Replit, Google Deepmind, Datadog, and more |
| Question to ask | Evaluation criteria |
|---|
| What type of research does you team conduct? Can I see some research? | The team should be able to share a research hub with multiple forms of research |
| What dataset is used to conduct research and how large is it? | The dataset should contain hundreds of millions of real user conversations and synthetic conversation for analysis |
How to use this buyers guide
Copy these questions into your RFP or vendor scorecard. During demos, ask vendors to show—not just tell—how they meet each criterion. Validate with exported data and reproducible examples.
See Also
