What market research tools do product managers use?
TL;DR
- Analytics shows behavior, interviews explain it, surveys size it, usability tests check designs, simulated audiences screen ideas before they exist.
- Marty Cagan's Inspired frames product discovery around four risks: value, usability, feasibility and business viability. Most market research tools address the first two.
- The gap most PMs feel is testing value for things not yet built, at the speed of a sprint.
- Neon Blue gives PMs a simulated audience of their users for concept, pricing and feature questions, with interviews and live tests kept for the finalists. Run your first study free
Neon Blue builds simulations of human behavior. Product managers use five kinds of research tools, each for a different question: product analytics for what users do, interviews for why, surveys for how many people think something, usability tests for whether people can use a design, and simulated audiences for how a defined group would react to something that doesn't exist yet. The mistake is using one tool for every question, such as reading analytics to guess why people churn, or running a survey to judge a design. Matching the tool to the risk you're trying to reduce is most of the job.
Which risks does product research reduce?
In Inspired: How to Create Tech Products Customers Love (2008, second edition 2017), Marty Cagan argued that product discovery exists to tackle four risks before engineering builds anything: value risk (will customers buy or use it?), usability risk (can they figure out how to use it?), feasibility risk (can we build it?), and business viability risk (does it work for the business?). Feasibility belongs to engineering and viability to the wider business. Market research tools mostly reduce the first two, and value risk is where PMs usually have the least evidence.
Which research tool answers which product question?
| Tool type | Answers | Doesn't answer | Best moment |
|---|---|---|---|
| Product analytics | What users do, where they drop off | Why, or what non-users would do | After launch, ongoing |
| Customer interviews | Why people behave as they do, in their words | How many people share the view | Early discovery, after big changes |
| Surveys | How common a need, view or preference is | Why, in depth; reactions to unbuilt things are shaky | Sizing and ranking |
| Usability tests | Whether people can complete tasks on a design | Whether they want it | Prototype to pre-release |
| A/B tests | Which live variant performs better | Anything you can't ship to real traffic | Live product with enough traffic |
| Simulated audiences | How a defined group would react to concepts, prices and features | How people use a real interface over time | Before build, before a live test |
Use two or three together. Interviews find a problem, a simulated audience ranks the solutions, a usability test checks the winner's design, and an A/B test settles the live version. The live test step is covered in the growth team guide.
What research does a PM run each stage?
- Problem discovery: five to ten interviews in the target segment, then a quick read on a simulated audience of how widespread the problem is.
- Solution screening: three to six solution concepts ranked on a simulated audience, with reasons. The method is in concept testing.
- Feature scope: a forced-choice ranking of candidate features, as in feature prioritization.
- Pricing and packaging: a price range and plan test before the pricing page exists; see pricing research.
- Design check: usability sessions on the prototype with real users.
- Launch and learn: analytics and A/B tests once it ships.
What does a PM study look like on a simulated audience?
Hypothetical: a PM at a large home fitness equipment company is scoping a new subscription tier for its connected bike app and has four tier concepts.
- Audience: US adults who own a home exercise bike or treadmill, split by current app subscribers versus non-subscribers, workout frequency, and household members who share the equipment.
- Questions to field:
- Which of these four plans would you choose, if any? [Plans with features and prices, plus "none"]
- What would make you upgrade from what you have today?
- Which feature in this plan would you miss most if it were removed?
- How many people in your household would use this?
- What, if anything, would make you cancel?
- Design: each plan shown monadically, then all four side by side, on the simulated audience.
Example output layout (illustrative, not a real result)
| Plan concept | Would choose (subscribers) | Would choose (non-subscribers) | Most-missed feature (coded) | Cancel reason (coded) | Next step |
|---|---|---|---|---|---|
| Plan A: classes only | __% | __% | Coded | Coded | Drop / Refine / Build |
| Plan B: classes plus coaching | __% | __% | Coded | Coded | Drop / Refine / Build |
| Plan C: family sharing | __% | __% | Coded | Coded | Drop / Refine / Build |
| Plan D: annual premium | __% | __% | Coded | Coded | Drop / Refine / Build |
The PM brings the top plan and its most-missed feature to design and pricing. The paywall that sells it gets its own read through subscription app paywall research.
How do PMs work with marketing on research?
Product and product marketing often research the same buyers for different reasons. Share the audience definition and reuse studies: the concept read that scopes the product can also feed the product marketing team's positioning work. For the prototype stage, the trade-offs of AI-run usability reads are covered in testing a landing page before launch.
Questions about research tools for product managers
What is the best research tool for a product manager?
There isn't one. Match the tool to the question: analytics for behavior, interviews for reasons, surveys for scale, usability tests for designs, simulated audiences for unbuilt ideas.
How do product managers do market research without a research team?
Run small, frequent studies: a handful of interviews each month, simulated audience reads for concept and price questions, and analytics reviews. Save larger live studies for big bets.
Can a simulated audience replace user interviews?
No. Interviews find problems and language you didn't know to ask about. A simulated audience is strongest at ranking options you can already describe.
How does Neon Blue fit in a PM's toolkit?
Neon Blue gives PMs a simulated audience of their users for concept, feature and pricing questions, returns results by segment marked as simulated, and leaves interviews and live tests for the finalists. Start a free first study.