Search Data Is Free Market Research. Most Companies Never Read It.
Companies pay handsomely for market research — surveys, focus groups, consultants — while ignoring the largest honest dataset about their market that has ever existed: what people type into search engines, and increasingly, what they ask AI assistants. Search data isn’t marketing trivia. It’s demand, described by the demander, in their own words, at scale, with intent attached. Most companies use it to pick keywords. The smarter use is to read it as strategy.
Intent is the signal, volume is the distraction
Every query carries intent, and the intent tells you where that person stands. “Best running shoes for long distances” is someone learning — informational. A specific brand and model name is someone navigating toward a choice they’ve half-made. “Buy” plus the product is a wallet already open — transactional. Sort your market’s queries by intent and you get a live map of the funnel: how many people are problem-aware versus solution-aware versus ready, what language they use at each stage, and what questions stand between stages.
The strategic reads come from the details. Long-tail queries — specific, multi-word, low-volume — are underpriced precisely because volume-chasers ignore them; they describe niche needs with high conversion and low competition. Rising queries flag where the market is moving before your competitors’ products do. And the questions people ask — the “how do I,” “why does,” “what’s the difference between” — are a content strategy written for you by your future customers.
The new layer: your buyers are asking machines now
Here’s what’s changed, and it changes the payoff structure. A growing share of these same questions never reach a results page — they’re asked to ChatGPT, Claude, Perplexity, and Google’s AI answers, which respond with a synthesized answer and a handful of cited sources. The question data still tells you what the market wants to know. But the prize is different: instead of ranking third and getting a click, you’re either the source the AI cites or you’re absent from the conversation entirely.
That reframes content strategy in one specific way: the winning move is to be the clearest, most citable answer to the questions your market actually asks. Structured pages that answer one question thoroughly. Real data and specifics — AI systems preferentially cite sources that say something concrete. Machine-readable, crawlable sites that don’t hide content behind scripts. The companies doing this now are compounding a position in AI answers the way early SEO adopters compounded rankings — quietly, before it was obvious, at pre-competitive prices.
The practical loop stays the same as it always was, with one addition: pull the query data (Search Console, SEMrush, Ahrefs), sort by intent, build the content that answers the highest-value questions — then periodically ask the AI assistants your market’s top questions and see who gets cited. If it isn’t you, you now know exactly what to write.
The owner’s version
You don’t need the tooling; you need one artifact. Ask your team for a one-page summary, quarterly: the top questions our market is asking, what’s growing, what stage of intent dominates, and who the AI assistants currently cite when asked those questions. That page is market research your competitors paid five figures to approximate — and a scoreboard for whether your expertise is visible where buying decisions increasingly start.
Baron Belalov is a fractional CMO working with growth-stage and established companies globally.