Key takeaways
- Most GEO demos open with an impressive visibility score. Your job is to find out what you would do with that score on Monday morning.
- Ask which AI engines are tracked through their real interfaces, and whether results are reported per engine instead of one blended number.
- Separate monitoring-only tools from platforms that trace sources, help write content, publish it and measure whether it worked.
- Pin down contract terms, response limits and what happens to your price after the intro period.
- Send your questions ahead of time and ask the vendor to run the demo on your brand, not a canned example.
Why demo prep matters more for GEO than for most software
The vendor controls what you see in a demo, the order you see it in, and how long each feature gets. That is true for any software category, and Roofr's guide to software demos makes the point well: people sit back and let the salesperson run the show. In GEO the problem is worse, because the category is young, definitions vary, and every vendor has a proprietary score you cannot verify.
Seer Interactive looked back at hundreds of GEO sales calls and concluded that many GEO buying processes are just SEO RFPs with "AI visibility" swapped in. Their GEO RFP guide (August 2026) points out why that fails. SEO had clean math: search volume, ranking, click-through curve, conversion. GEO has no real search volume, visibility is less stable because of personalization and probabilistic answers, and you cannot tell whether you are the fourth recommended brand or the twentieth.
So the questions you bring need to be different. Here are the ten I would ask, roughly in the order they should come up on the call.
The 10 questions
1. Which AI engines do you track, and do you collect from the real interfaces?
A vague answer like "all major AI search engines" is a warning. Ask for the exact list: ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, Google AI Mode, Copilot and so on. Then ask the sharper follow-up: is the data collected from the actual user-facing interfaces, or from API calls? User-facing answers, citations and shopping results can differ from API output, because the API model answers from training data while the product runs live search.
Also ask whether you can pick country and language per monitor. A brand tracking only US English prompts is blind everywhere else.
2. How do you calculate visibility, and can I see the formula?
A single score is easy to demo and hard to trust. Ask what goes into it: placement, share of attention, depth, position, sentiment. Ask whether a response that never mentions you counts as zero or gets dropped from the average. Dropping those flatters everyone.
The more useful test is diagnostic. Can the platform tell you whether you have a coverage problem (low share of voice), a prominence problem (late position), a content or crawlability problem (mentions without citations to your own domain), or a reputation problem (weak sentiment)? A score that cannot locate the problem is decoration.
3. How do you separate real changes from engine noise?
This is the question that makes vendors squirm, and it matters. Promptwatch Data's average sources per response report shows how different the engines behave: ChatGPT cites about 5 sources per web-search answer, Google AI Overviews about 10, and Perplexity almost exactly 10 every day with barely any movement. Copilot swung from under 2 to nearly 17 sources within a few weeks before settling. If a platform blends all of that into one line, you will chase noise.
Ask whether results are reported per engine, whether trends are smoothed for volatile engines, and whether the tool re-baselines when an engine changes its search behaviour. Promptwatch's ChatGPT query fanout data is a good example of why: average fanouts per response and fanout query length shifted noticeably between December and April, which changes what your tracked prompts should look like.
4. Can I see the query fan-outs behind each response?
A single prompt can trigger several separate web searches, and those sub-queries are what actually decide which pages get retrieved. Ask whether the platform shows them per response and per model. Also ask whether it suggests prompts from your own Search Console data, People Also Ask and competitor pages instead of making you guess. Prompt volume and difficulty scores are a bonus; since real AI search volume is largely unknowable, ask how the vendor estimates them and be skeptical of precision.
5. Does it only report, or does it help me fix what it finds?
Launchmind's checklist for choosing a GEO platform puts it bluntly: a tool that only flags issues is a dashboard, not a growth engine. Ask the vendor to show the path from "you are invisible for this prompt" to a published page. Who writes it? Is there a content gap analysis? Does it connect to WordPress, Webflow or Framer? Is there a review step before anything goes live?
Then the question that separates optimization from monitoring: after a page is published, does the platform tell you whether AI crawled it, cited it, and sent traffic?
6. Where does the data on my own site come from?
Visibility data tells you what AI says. It does not tell you why. Ask whether the platform includes IP-verified AI crawler logs, so you can tell an access problem (bots blocked or erroring) from a content problem (bots read the page but never cite it). Ask how spoofed bots are filtered out. Ask whether it ingests Google Search Console and Bing Webmaster data, so you can find pages that rank in search but never get cited by AI.
Most lightweight trackers have none of this. That is fine if you only want a score, but you should know what you are buying.
7. How do you tie AI visibility to traffic and revenue?
Seer's point about GEO ROI being hard is valid, which is exactly why you should ask how the vendor handles it. Look for visitor analytics that attribute sessions from ChatGPT, Perplexity, Gemini, Claude and Copilot, and ask how they handle referrer loss. ChatGPT stopped sending a referrer on October 8, 2026, so a good platform needs a documented workaround such as counting visits tagged with a UTM parameter. If the answer is "we show visibility, you connect it to revenue," you are doing the hard part yourself.
8. Which sources does AI cite, and do you cover Reddit, YouTube and LinkedIn?
Citation behaviour differs sharply by engine. Promptwatch Data shows ChatGPT drew just 0.46% of its citations from social platforms between Sep 28 and Oct 4, 2026, while Google AI Overviews drew 12.2% (social media citations by AI model, October 2026). Reddit's share of ChatGPT citations also fell from roughly 4% to 0.5% on August 14, 2026 (Reddit citations are dropping in ChatGPT).
So ask: does the platform show which third-party pages and channels each engine cites, and can it find pages that mention your brand without linking to you? A platform built on last year's assumptions about Reddit will send you in the wrong direction.
9. What exactly is limited, and what does it cost after the intro period?
Ask for the pricing page and then ask what the page does not say. Limits that matter:
- number of prompts and monthly responses
- projects or brands
- tracking frequency (daily vs hourly)
- crawler log volume and visitor events
- content or article credits
- seats
- API and MCP request limits
Also ask about overage charges, whether annual billing changes the price, and whether a trial exists before you commit. Launchmind's warning is worth repeating: monthly billing does not automatically mean you can cancel month to month. Get the notice period and minimum term in writing.
10. Who are your customers like me, and can I talk to one?
Ask for a case study in your size and industry, with what changed over 30, 60 and 90 days. Seer suggests the same idea for agency pitches: ask about a win they are proud of and what happened afterward. Specific numbers beat adjectives. For reference, Crisp reported 2x higher conversion rates from AI traffic compared with traditional channels, and TreeHouse grew AI search to about 25% of its organic conversions. Those are the kind of claims you should expect, with names attached.
If you are comparing agencies instead of software, that is a different conversation, though several questions above carry over. Agencies such as 1001 SEO Media handle GEO as a service, and the tool they use is worth asking about too.
How the question categories map to platform types
Not every platform is trying to do everything, and that is okay. What matters is that the demo matches your need.
| Capability to probe | Basic trackers | Monitoring-focused platforms | End-to-end platforms |
|---|---|---|---|
| Real-interface data per engine | Sometimes | Usually | Yes |
| Query fan-outs | Rare | Sometimes | Yes |
| AI crawler logs | No | Rare | Yes |
| Traffic and conversion attribution | No | Rare | Yes |
| Content creation and CMS publishing | No | No | Yes |
| Measuring whether a fix worked | No | No | Yes |
Where common tools sit
Treat this as a starting shortlist, not a verdict. Always check current features on each vendor's site.
Promptwatch is the one I would put through the full ten questions first, because it covers the whole loop: tracking from the real interfaces of ChatGPT, Gemini, Perplexity, Google AI Overviews, AI Mode, Copilot and others, IP-verified crawler logs, visitor analytics, content gap analysis, a Content Agent that publishes to WordPress, Webflow or Framer, and page-level tracking afterward. Plans start at $95/mo with a 7-day free trial on monthly billing; confirm current numbers at promptwatch.com/pricing. You can also run the free AI visibility report before booking anything.
Profound is a strong monitoring product aimed at larger budgets. Ask it about Reddit coverage, shopping and agentic execution. There is a head-to-head at Promptwatch vs Profound.
Peec AI and Otterly.AI sit on the more affordable tracker end. They are good at answering "was my brand mentioned?" and weaker on crawler logs, attribution and content generation.
Semrush and Ahrefs Brand Radar add AI tracking to SEO suites you may already pay for. Ask about fixed prompt sets and how deep the AI-specific data goes.
AthenaHQ is another monitoring-led option worth pressure-testing on the content and publishing questions.
For a wider browse, the GEO software directory at bestgeosoftware.com lists many more options.
How to run the call itself
Send your questions in advance
Vendors prepare differently when they know what is coming. Send the ten questions a few days earlier and ask which ones they would rather answer live with the product open.
Ask them to use your brand
A canned demo with a fictional company hides gaps. Ask the rep to load your domain, three competitors and a dozen real prompts. Even a rough run shows how the platform handles brand-name collisions, local queries and your language markets.
Avoid agreement-bait
Sales teams are trained to ask "does this make sense?" and "would this be helpful?" Those questions invite a polite yes. Answer with specifics instead: "Show me how I would find the page AI learned the wrong claim from."
Score the answers
After the call, rate each question from 0 to 2: no answer, partial answer, shown live. A tool that scores high on tracking but zero on fixing and attribution is a dashboard. That may be all you need, but now you know.
Red flags to watch for
- The demo shows a score but never opens a single response or citation.
- "All AI engines" with no list, or blended results across engines.
- No way to verify what the score means.
- Pricing that is only revealed after a second call, with a 12-month minimum.
- Content features described as "coming soon" while you are asked to sign now.
- No explanation of how the data was collected.
Final checklist
Before you book, write down your top three outcomes: more citations, more AI-referred conversions, or better brand sentiment. Then make sure at least five of the ten questions map to those outcomes. If a vendor cannot show the path from a gap in the data to a published, measured page, keep looking. And if you want to see a full loop before taking a call, the 7-day trial and the free visibility report cost nothing to try.