AI agent for market and competitor research
A decision about a market rarely stalls on thinking — it stalls on gathering. You need what competitors publish, how demand is behaving, what customers say in their own words, and what you already tried here and how it went. That takes days, and you walk into the conversation tired from searching. The agent brings the material, with a source on every claim and an honest mark where it could not confirm something. The conclusion is yours to draw.
What a market research agent does
- Works through competitors' public surfaces — site, pricing, releases, ads, job postings — and sets out how they differ from each other, not just where they overlap.
- Tracks how demand behaves: what gets searched, what gets asked, how it shifts by season.
- Collects the words customers use for their own problem, quoted from reviews and public threads rather than paraphrased.
- Pulls up your own history: what you already tried in this market and how it ended.
- Attaches a source and a date to every claim, and marks separately anything it could not confirm.
Processes that run themselves
A playbook isn't a button — it's a process with a condition that starts it. These three get set up most often.
A new client or product gets scoped
A new client or a new product comes into the pipeline
- Work through the competitors' public surfaces: site, pricing, releases, ads, hiring
- Set out how they differ from each other, not only where they look alike
- Collect the words customers in this market use for their own problem
- Attach what you already tried here and how it ended
A competitor changes something in public
Something visible changes at a competitor — pricing, landing page, a release
- Record exactly what changed, with the before and after attached
- Check whether it's a one-off or a continuation of what they were already doing
- Send a short note — with no theory about what it means for you
A decision is on the calendar
A meeting is scheduled where the decision gets made
- Check with you which question the material is actually for
- Gather against that question rather than against the market in general
- Separate the confirmed from the unconfirmed inside the text itself
- Hand it over early enough to be read before the meeting
Where the agent stops
- It collects, it doesn't conclude: what follows from the material and what to do about it is your call — and that call is the part the client is paying for.
- Every claim carries its source and its date, and anything it could not verify is marked unverified rather than smoothed into a confident sentence.
- It works only with publicly available information: closed databases, paywalled content and other companies' internal data are off limits.
- On similar input it produces similar output. A research summary is a starting point, not the thing that makes you different from a competitor running the same agent.
FAQ
Can it just propose the strategy from the material it gathered?
Technically yes, and that's exactly where this breaks. In the agency this role is drawn from, an agent was writing the strategy — and three of six came out close enough that a client recognised their competitor's positioning in their own. On similar material and a similar prompt, a model gives a similar answer, and in strategy that's precisely what nobody pays for. So the agent stops at the material.
Where does it get the information?
Public sources: competitor sites and pricing, their releases and job postings, reviews and public discussion, search demand, and your own past campaigns. Closed databases, paywalled content and other companies' internal data are not collected. The reason isn't only legal — material you can't put on the table is useless in a conversation where someone asks you to back a number up.
How do I know what in the summary to trust?
By the source and date sitting next to each claim. A figure from a competitor's annual report and a figure from a blog post carry different weight, and you need to see which one you're looking at. Anything it couldn't confirm stays in the text marked unverified — and those lines are often the most interesting ones to talk about.
How is this different from what a competitor running the same agent would get?
In the gathering itself, barely at all, and it's worth accepting that up front. The difference is what you do with the material: which questions you put to it, what you judge important, which decision you make and where you put the money. The agent levels the starting point and saves you the days of searching; the advantage comes after that, and it comes to you rather than to the agent.
Where this shows up
Walkthroughs where this role carries part of the work.
An agency run on AI agents: where strategy has to go back to a human
Agents carry production well. The problem is elsewhere: strategy starts looking the same across every client, and clients notice before you do.
Read the walkthrough →Enterprise & productGetting through quarterly review without the 1 a.m. spreadsheet session
No team under you, no headcount coming, and you're held to a department's output. Here's which parts of that load are mechanical enough to hand off — and which have to stay yours, especially in the room.
Read the walkthrough →