skill

Market Research

Market Research is an ecommerce AI skill for Alireza Rezvani, built for teams working with Codex, Claude Code, OpenClaw. Use it to build a decision-ready market-size…

What this skill helps you do

Build a decision-ready market-size and segmentation analysis without relying on one unsupported TAM number.

Independent Store Operator

Build a decision-ready market-size and segmentation analysis without relying on one unsupported TAM number.

Before you start

  • Write the decision the research must support.
  • Define geography, customer, category, channel, time period, and currency.
  • Collect at least one top-down source and enough operating assumptions for a bottom-up model.

How to test it safely

  • Stress-test the three assumptions with the largest impact.
  • Have a second operator reproduce one result from the stated formula and inputs.
  • Present a range and decision threshold rather than one precise headline number.

Operator-ready setup plan

  1. Define the market boundary

    State exactly who buys what, where, through which channel, and during which period.

    Checkpoint: Two analysts would count the same customers and transactions.

  2. Run both sizing methods

    Calculate top-down and bottom-up estimates with visible formulas, units, assumptions, and source dates.

    Checkpoint: Every number has a source or a named assumption.

  3. Reconcile the gap

    Explain why the methods differ and revise scope or assumptions before presenting a headline range.

    Checkpoint: The remaining range is tied to known uncertainty.

  4. Score reachable segments

    Evaluate whether each segment is measurable, substantial, accessible, differentiable, and actionable for the store.

    Checkpoint: A segment can be reached with a plausible offer, channel, and budget.

  5. Connect analysis to a decision

    State what would make you proceed, test, delay, or reject the opportunity.

    Checkpoint: The report changes an actual product, market, or budget decision.

Limits to account for

  • The method cannot repair weak or incompatible source data.
  • Repository popularity is not evidence that a specific market estimate is correct.
  • A large market does not prove reachable demand, unit economics, or product-market fit.

Questions at this experience level

Why calculate TAM in two ways?

The disagreement exposes scope and assumption problems that a single impressive number can hide.

How precise should the result be?

Use a range that matches the quality of the inputs and the decision. Extra decimal places do not create certainty.

Can this choose a winning product for me?

No. It can structure market evidence, but product selection also needs unit economics, competition, compliance, supply, and validation with real customers.

License
MIT
Source & attribution

Creator, original source, and platform proof

Checked 2026-07-19
Author / maintainer

Alireza Rezvani

HealthTech CTO and open-source maintainer focused on applied AI, agentic coding, and practical skills for product, research, growth, and operations teams.