Who do AI assistants recommend in your market, and which topics are still open?
Keyword data shows what buyers search for. This check shows which brands leading AI models name when buyers ask for a recommendation, how you compare with the competitors you choose, and which buyer topics no brand owns yet.
Checks start at $1,890. The configurator shows the exact price for your scope before you pay. Your results stay private.
Your planning data stops where the AI answer starts
Next year's content and positioning plan usually starts from keyword volume, rankings, competitor pages, and last year's performance. Those inputs describe search demand and search results.
More buyers now ask an AI assistant directly. They ask which brand to choose for a specific job at a specific budget. The assistant names a few brands and gives reasons. For that buyer, the answer is the shortlist.
Your planning data doesn't show what happens inside that answer. It leaves questions like these open:
- Which competitor gets named when buyers ask about our category, and how often?
- Are we behind that competitor, or is the gap within the noise?
- Which buyer questions get an answer with no clear brand in it?
- Where are we strong on one buyer topic and missing from the next?
Your current tools measure something else
Keep your SEO partner and your tools. Keyword research, rank trackers, and SEO suites do the job they are built for: they tell you what people search for and where your pages rank. They are not built to measure which brand an AI model recommends.
Two things make AI answers hard to read from a quick test.
Answers vary. Ask an AI assistant the same question twice and the brands it names can change. One answer, or a handful, can't tell you whether a competitor's lead is real. Measuring that takes many answers per buyer need, each need asked in several phrasings, a re-asked sample, and statistics.
What a model has learned outlasts today's search results. AI models answer partly from what they learned in training and partly from live web search. The trained part carries over from day to day, and it shapes answers even when search is switched on. The check measures what the models themselves hold, separate from what a live web search returns on a given day. You see the position your content and positioning work has to move over time.
In our read, that trained knowledge draws on reviews, forum opinions, SEO-farm content, and outdated pages. The brand AI assistants name first may differ from the brand that leads your market by sales.
That makes AI's version of your market the one buyers are told. Where it differs from what is true, or from your own research, the AI version wins over time.
We built the check for our own platform, because no tool we tried showed what AI assistants tell buyers.
Been there, done that.
The check was built by a designer with two decades inside the SEO and content playbook for some of the biggest brands in the world. The playbook worked and still works. It also shaped the web AI learned from, and we now deal with its side effects.
Designed digital products for Allianz, MetLife, JPMorgan Chase, BlackRock, Nestlé and Porsche.
Two sections built for planning decisions
Competitive picture: who owns the answers you're missing?
For the buyer questions in your market, the report shows share of voice (how often each brand is named). It covers your brand and the competitors you add in the configurator. When a head-to-head difference between two brands is too small to be real, the report marks it "too close to call" rather than showing a lead. You see which gaps are real before you plan around them.
Use it to decide which competitor to plan against, and where to defend or challenge.
Whitespace: which buyer topics does no brand own yet?
Some buyer questions get answers where no brand holds a clear position. The report lists these open topics. In an open topic, your content has no established brand in the answer to compete with.
Use it to choose the themes for next year's content program.
Also in the report
The report also covers where you appear in AI answers, how results differ by model, and what AI says about your brand. A technical audit checks whether AI models can read your website and product information, with fix text for each failing check.
How it works
- Configure your scope. Describe your market and add the named competitors you want to measure against.
- See your price. Checks start at $1,890. The configurator calculates the exact price for your scope and shows it before you pay.
- The scan runs. A fixed panel of leading AI models is asked realistic buyer questions about your market, each need in several phrasings, with a sample re-asked. Statistics mark differences too small to be real as "too close to call", and the technical audit checks your website.
- Get the report and your Monday plan. Each section answers one buyer question. The Monday plan ranks what to do first.
A report your planning meeting can use
Your report is built on 7,000+ analyzed data points. Each section answers one question:
- Verdict: where do we stand, in one score and a plain verdict?
- Machine access: can AI models read our website, and what do we fix first?
- Visibility map: where do we show up in AI answers, and where don't we?
- Model split: does this differ model by model?
- Competitive picture: who owns the answers we're missing?
- Whitespace: which buyer topics does no brand own yet?
- Perception: what does AI say about us, laid out so we can hold it against reality?
- Monday plan: what do we do first?
- Methodology footprint: how was the scan run, and will a re-scan compare?
The Monday plan turns the competitive picture and the open topics into one ranked to-do list. Each task has an owner (whoever runs your website, owns your content, or owns your positioning) and a link to the evidence behind it. Hand it to your in-house team or your agency.
Questions
- We already track share of voice. How is this different?
- Share-of-voice reporting usually covers search results, ads, or social mentions. This check measures share of voice inside AI answers to buyer questions: how often each brand is named, with differences too small to be real marked "too close to call". Use both. They describe different channels.
- What if we and a competitor are close?
- If the difference is too small to be real, the report says "too close to call". It doesn't place you first or second when the data can't support it. That keeps you from moving budget over a gap that may not exist.
- How do you decide that a topic is whitespace?
- A topic is listed as whitespace when, across many answers per buyer need from every model in the panel, no brand holds a clear position. Each open topic is listed in the report, so your team can judge the opportunity for itself.
- The results don't match our own market research. Which one is right?
- Both can be. Your research measures what customers think. The check measures what AI tools believe your market looks like. Where the AI version differs, the AI version is what buyers are being told when they ask. That gap is a positioning finding in its own right.
- Will our results be published?
- No. Customer results are never published, and your results belong to your brand.
- Do you write the content for the open topics?
- No. Pure Neo measures. We don't sell articles, backlinks, or GEO content packages. The Monday plan is written so any team or agency can act on it, and agencies also buy the check for their clients.
Set next year's priorities on measured answers
Choose your competitors in the configurator. Checks start at $1,890. The configurator shows the exact price for that scope before you pay. The report shows who owns the answers in your market, which buyer topics are still open, and what to do first.
Questions before you buy? Email us