For product marketing AI engines now write the buyer's shortlist. Get your product on it.

Seerly for product marketing shows whether AI engines recommend a product when buyers ask category and comparison questions. Product marketers use it in five steps: build a fixed prompt set from buying questions and measure how often the product is named and where it ranks, compare the product with one competitor at a time on the same prompts and sources, list the topics and engines where the product is absent and the pages cited in its place, audit product and documentation pages for the issues that affect how AI systems interpret and cite them, and follow a launch over time with analytics on AI referrals and published pages.

When a buyer asks an AI engine which product to choose, it names a shortlist. Seerly shows whether yours is on it, who is recommended in your place and on what evidence, and which pages to fix so the next answer includes you.

  • No tracking code
  • No credit card
  • Edit the prompt set any time
One buying questionRunning shoe brand
The shortlist

Who the answer recommends

best running shoes for flat feet

RecommendedThree competing models
Your modelLeft out
Why it is left out

What the answer was built from

  • A rival's comparison pageCited
  • Your product pageAudit issues
  • A page on flat-foot supportMissing
On the list

Same question, after the fixes

At launchNot named
Now2nd of 5 brands
TrackedFrom launch day onward

How it works

From positioning to the shortlist. Five steps, one shortlist.

How a product marketer gets a product into the answer: set the questions, read the comparison, find the gaps, fix the pages, follow the launch.

Test your positioning on the questions buyers ask

Positioning is tested when a buyer asks an AI engine for a shortlist. Build a prompt set from your category questions, the comparisons buyers make and the objections sales keeps hearing, then measure how often the product is named and where it ranks. The set stays fixed, so a change in the answer reflects the market and not a change in the question.

  • A reusable prompt set for your category
  • Mention and rank on each prompt
  • The prompts that surface the product, and the ones that leave it out
Visibility · All Engines
Last 30d

All Engine Visibility

ChatGPT

78%

Rank #1

Perplexity

61%

Rank #3

Google AI

54%

Rank #2

TopicVisibilityPositionStatus
Running shoes84%#1Strong
Trail gear51%#3Monitor

Where to start

Six areas, in the order a product marketer opens them.

Set the questions first. Everything after that is read against the prompt set you built for the product.

Visibility

Open this first: where the product is named on your category prompts, and at what rank.

See Visibility

Primed Prompts

To test your messaging: the same question asked cold and with buyer context, side by side.

See Primed Prompts

Competitor Intelligence

For battlecards and comparison pages: you and one rival, on the same prompts.

See Competitor Intelligence

Gap Analysis

The buying questions that are answered without your product in them.

See Gap Analysis

Smart Audit

The fix list for product and documentation pages, ready to hand to web.

See Smart Audit

Analytics

After a launch: AI referrals and the performance of the pages you shipped for it.

See Analytics

Questions

Questions product marketers ask.

AI assistants build a recommendation by summarizing the public sources they can reach about a category, so the products that appear are the ones described clearly in the pages those engines cite.

For product marketing that reframes the problem. The question is not how you rank, but whether an engine can state what your product does without hedging.

  • Seerly tracks the recommendation prompts buyers actually ask in your category
  • Every appearance is recorded with rank, framing, and cited sources
  • Answers are scored per engine, since each reads a different source mix
  • Prompt coverage: 25 per month on Basic, up to 100 on Pro

The gap that shows up most often is a capability you market heavily that no cited source states plainly.

How recommendation tracking works

Yes. Seerly tracks feature-level and capability-level prompts separately from brand prompts, so you can see which parts of the product AI answers mention and which never come up.

This is usually where a positioning problem becomes concrete. The differentiator that leads every deck turns out to be absent from every answer an engine gives about the category.

  • Prompts written around specific capabilities, use cases, and buyer intents
  • Mention frequency per feature, broken out by engine rather than blended
  • Features competitors are credited with on the same questions
  • Movement per feature between scheduled runs, so a change is traceable

Underrepresented features are typically a content problem before they are a product problem, because no cited source states the capability plainly enough to be summarized.

How capability coverage is tracked

Seerly shows the prompts where a competitor is recommended and your product is absent, together with the exact sources the engine cited to reach that recommendation.

Displacement usually traces back to a specific comparison page, review, or reference entry doing the persuading, not to the engine holding an opinion.

  • Share of voice across your tracked prompt set, reported per engine
  • Question-level detail on exactly where the competitor wins
  • The citation sources behind each competitor recommendation
  • How the competitor is framed on the aspects buyers ask about
  • Movement between runs, so a newly surfacing rival is visible early

The practical response is generally publishing a clearer, better-sourced answer to the same question rather than arguing with the engine about its conclusion.

How competitor displacement is tracked

Yes. Seerly lets you edit the tracked prompt set, so launch questions, new category terms, and the objections your sales team hears can be added and measured from the launch date onward.

Adding the prompts before launch is what makes the comparison meaningful, because the pre-launch baseline is captured rather than reconstructed later.

  • Prompts are editable, so launch questions can be added and retired
  • Up to 100 tracked prompts per month on Pro, 25 on Basic
  • Runs every 4 days on Basic, more frequently on Pro
  • Rolling comparisons across 7 days, 30 days, and 3 months

Engines pick up new material at their own pace, so read the movement as measured rather than expected.

How prompt sets are built

Documentation is one of the public sources AI engines can read, so how plainly your pages state what the product does affects how accurately an assistant can describe it.

Seerly audits your public site so you can see which pages are legible to a machine reader before trying to explain a weak answer.

  • Site audit covering 800 pages on Basic, or all pages on Pro
  • Page-level issues affecting how content is parsed
  • Which of your own pages already earn citations, and on which prompts
  • Public pages only, with no CMS or code access required

The pages that get cited are usually the ones that answer a question directly, not the ones that read best as marketing copy.

What the site audit checks

Yes. Category and comparison questions are the core of what Seerly tracks, because those are the prompts where an assistant names a shortlist and your product either appears on it or does not.

Prompt sets are tuned toward recommendation, comparison, and experience phrasing rather than neutral definitional queries, because that phrasing is what makes an engine commit to naming products.

  • Recommendation prompts, comparison prompts, and objection prompts
  • Every brand named in the answer recorded alongside yours
  • Rank within the shortlist, not just presence on it
  • Editable prompts, so you can add the comparisons sales actually hears
  • 25 tracked prompts per month on Basic, up to 100 on Pro

The same prompt set feeds visibility and sentiment, so presence and framing are always measured on identical questions.

How prompt sets are built

Seerly keeps every scored run, so a messaging or documentation change can be checked against the same prompts and engines that exposed the problem, with the earlier runs still on record.

A fixed prompt set is what makes this credible. The comparison is not a fresh sample taken after the fact, and the questions do not quietly change between the two readings.

  • Baseline captured on the first run, then movement across rolling windows
  • Rolling comparisons across 7 days, 30 days, and 3 months
  • Feature-level and category-level trends reported separately
  • Per-engine movement, since one usually shifts before the others
  • The verbatim response behind any point on the trend

Seerly reports the measured before-and-after. It does not forecast where positioning will land, and engines pick up new material at their own pace.

How trend reporting works

Seerly checks product recommendations on ChatGPT, Perplexity, and Google AI Overview, plus your Google search footprint. How many of those three you see depends on your plan.

Engines are reported separately because a shortlist can include your product in one engine and omit it entirely in another, and a blended average would hide exactly that.

  • Basic: one engine of your choice, either Google AI Overview or ChatGPT
  • Pro: all three, ChatGPT, Perplexity, and Google AI Overview
  • Enterprise: additional engines on request, under a custom scope
  • Your Google search footprint tracked alongside the AI results

Product marketers working a contested category usually want all three, since displacement rarely happens everywhere at once and the first engine to drop you is the early warning.

Compare engine coverage by plan

See which shortlists your product is on.

Enter your domain. The first analysis shows the buying questions where AI engines name you, and the ones where they name someone else.

  • No tracking code
  • No credit card
  • Edit the prompt set any time