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Research overview

Research overview

Section titled “Research overview”

Research is the evidence-gathering stage of the validation pipeline. It answers questions like: Is anyone searching for this? Is the market growing? Who are the competitors? Where do frustrated users complain? Instead of opening a dozen browser tabs, you run research runs inside an idea.

What a research run is

Section titled “What a research run is”

A research run is a single investigation of one topic for one idea. Each run uses one of the available research phases — for example, a Google Trends analysis, a market sizing estimate, or a competitor analysis — and produces a structured set of results that you can read, export, and reuse.

Runs are stored per idea and stay in the idea’s Research section. You can re-run any phase as often as you like, and past results remain available so you can see how the picture changes over time.

How a run is created

Section titled “How a run is created”

Each idea gets its own research workspace. To create a run:

  1. Open the idea you want to research.
  2. Go to the Research section.
  3. Pick a phase from the list — you’ll see a short description of what it investigates.
  4. Provide any inputs the phase needs (such as keywords for SEO analysis or a description for market sizing).
  5. Start the run.

The run is queued and executed in the background, so you can keep working while it completes. You’ll see its status update from pending, to running, to completed — or failed, with a clear reason you can act on.

How results flow into the rest of the pipeline

Section titled “How results flow into the rest of the pipeline”

Research isn’t a dead end — its results feed everything downstream:

  • Scores. Completed runs power the PMF score’s proxy signals: search demand, pain point density, market growth, competitive traction, and timing are computed from your research data.
  • Canvases. AI-generated canvases (business model, value proposition, lean canvas) use your research as context, so they reflect the market as it actually is.
  • Comparison. The comparison dashboard extracts normalized metrics from your research runs so ideas can be ranked against each other.
  • Validation. Research identifies the assumptions worth testing — point the validation tools at those next.

Live data vs. simulated data

Section titled “Live data vs. simulated data”

Some research phases rely on external data sources — search trends, community forums, app stores, and similar. When a data source isn’t configured for your workspace, the system falls back to simulated results so you can still explore the feature and understand how it works.

Simulated results are always clearly labeled — you’ll see a “simulated” marker on the results, and the data quality is reflected in the confidence of any scores derived from them.

Next steps

Section titled “Next steps”
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