WhailyWhaily

Market Intelligence

Know what AI tells your buyers — before you do

AI search reshapes buying behaviour before a prospect ever contacts you. Whaily captures the prompts, the framings, and the purchase criteria AI surfaces in your category, so you can respond to the real market, not the one in your decks.

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ChatGPTChatGPT
ClaudeClaude
GeminiGemini
PerplexityPerplexity
DeepSeekDeepSeek

The problem

Buyers form opinions with AI first. You are not in the room.

By the time a prospect books a demo, they have already compared five alternatives with ChatGPT, asked Gemini about evaluation criteria, and let Perplexity summarise the reviews. Their shortlist, the adjectives they use, the objections they raise — all of it is shaped by answers you never saw. Without market intelligence from the AI layer, you are responding to a pre-filtered version of your own market.

How it works

From sign-up to signal in minutes.

1

Define the prompts your buyers actually use

Evaluation queries, comparison queries, category-of-need queries. Whaily suggests prompts from your industry and product. Tag them by persona, funnel stage and market so analysis stays actionable.

2

Capture what AI says across every model

Whaily runs your prompts across ChatGPT, Gemini, Claude, Perplexity and DeepSeek on a schedule. Every response is stored, parsed and structured — brands named, criteria surfaced, framing captured verbatim.

3

Watch your market evolve in real time

See the top recommended brands, the most commonly surfaced purchase criteria, and the framing shifts that happen week to week. Spot new competitors rising, new criteria emerging, and new language AI uses about your category.

What you get

Everything you need, in one place.

Prompt library with smart suggestions

Start with suggested prompts for your industry. Expand as you learn what your buyers are really asking.

Purchase criteria extraction

Whaily extracts the buying criteria AI surfaces most often. See what is winning the argument right now.

Brand mention analysis

Every brand AI names in your category, with frequency, position and sentiment. Find rising challengers early.

Multi-market coverage

Run the same prompts in different countries and languages. The US answer is not the German answer.

Evolution over time

Track how category framing, preferred brands and criteria shift. Messaging that resonated last quarter may not this one.

Model-by-model comparison

See where models agree and where they diverge. Sometimes ChatGPT and Perplexity disagree in revealing ways.

The purchase criteria your buyers really weigh.

Whaily extracts every criterion AI surfaces across your prompts — pricing, integrations, onboarding, support — and ranks them by how often they win the argument.

Screenshot slot

Purchase Criteria grid — criteria AI surfaces, ranked by frequency, with competitor coverage columns.

/app/competitors (Purchase Criteria grid)

Why it matters

The AI answer is the new first impression.

A category conversation used to happen across trade press, analyst reports and peer conversations. It still does — but increasingly, it happens inside a single AI response that summarises all of that in one paragraph. The framing of that paragraph decides whether you are in consideration or not.

Market intelligence in the AI era is about capturing that paragraph — how it is phrased, which brands it contains, which criteria it foregrounds — and watching it evolve. That is what Whaily does. Every prompt run is a data point. Stitched together, they form the clearest view of the market a modern team can have.

The teams that win here use this intelligence to sharpen positioning, refine messaging, and spot competitive moves early. "Three of our prospects this month brought up integration depth. Gemini now leads with integration depth in the category prompt. We should re-sequence our homepage." That is the loop market intelligence should enable. Whaily makes it practical.

Every prompt. Every model. One matrix.

The prompt × model matrix shows who AI recommends for each query and each engine. Spot the prompts where ChatGPT loves you and Perplexity does not, and why.

Screenshot slot

Prompt × model matrix — rows of prompts, columns of AI engines, cells showing recommendations.

/app/competitors (prompt matrix)

Questions

The short answers.

How is this different from traditional market research?+
Traditional market research is survey-based, slow and expensive. AI market intelligence is continuous, model-based and captures the messaging your buyers actually receive. The two complement each other.
What counts as a "purchase criterion"?+
Any evaluation dimension AI surfaces when answering category prompts — pricing, integrations, onboarding, support, performance, compliance. Whaily extracts and normalises them automatically.
Can I see how AI's framing of my category changes over time?+
Yes. Whaily stores every response. You can diff any two time periods to see how language, criteria and brand preferences have shifted.
Do I need to write prompts from scratch?+
No. Whaily suggests prompts for your industry and product on setup, and you expand from there as you learn what your buyers ask.
How do different AI engines compare in their answers?+
Whaily shows you each engine's response side by side, so you can see where ChatGPT, Gemini, Claude, Perplexity and DeepSeek align and where they differ. The differences are often where the best insights live.
Does this work in non-English markets?+
Yes. Prompts carry a language and country code. Run the same query in German, Japanese or Portuguese and compare how the category is framed across markets.

Pairs well with

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