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market-research

Skill9 starsChanged 5 months agoMITView on GitHub

Analyzes a dataset of companies or profiles to identify market patterns. Use when the user provides a larger dataset and wants segments, dominant categories, gaps, and emerging patterns.

113 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 99 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not over-generalize beyond what the data supports.

    line 47

“Common” is measured: kept by at least 6 in 10 of the 99 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Market Research

Purpose

Analyze a dataset of companies or profiles to identify market segments and patterns.

When to use this skill

  • Understanding a scraped market dataset
  • Finding natural segments in a large list
  • Spotting dominant and underserved categories
  • Sizing where the opportunity concentrates

When not to use this skill

  • The dataset is too small to show patterns
  • You need statistically rigorous market sizing
  • You want per-record actions (use Lead List Analysis)

Required inputs

  • A dataset of companies or profiles

Optional inputs

  • Dimensions of interest (industry, size, geography)
  • A hypothesis to test

Rules

  1. Analyze the whole dataset, not a convenient subset.
  2. Report counts and proportions where possible.
  3. Do not over-generalize beyond what the data supports.
  4. State source skew and limitations.
  5. Separate observed patterns from speculation.

Process

  1. Profile the dataset structure and fields.
  2. Identify recurring characteristics and categories.
  3. Derive natural segments.
  4. Identify gaps and emerging patterns.
  5. State limitations.

Output format

Return a market analysis with the following fields:

  • market_segments
  • recurring_characteristics
  • dominant_categories
  • gaps
  • emerging_patterns
  • research_limitations

Validation

  • Confirm segment claims reflect the data distribution.
  • Confirm limitations note any sampling skew.
  • Confirm no invented statistics.

Limitations

  • Findings describe the supplied dataset, not the whole market.
  • Source bias in collection carries into the analysis.

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