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Market Matching: Results and Interpretation

What results you get

A typical Market Matching run provides:

  • overall quality score,
  • ranked controls for each test market,
  • per-control similarity scores,
  • balance statistics,
  • and report artifacts for review.

Read results in this order

  1. Overall quality assessment
  2. Test market -> control ranking
  3. Similarity levels
  4. Balance diagnostics
  5. Warnings/comments

This order helps prevent selecting controls based only on one metric.


Key output sections

Primary results

  • One row per test market
  • Lists selected control markets
  • Includes similarity and balance summary

Quality assessment

  • Overall quality score
  • Per-test-market quality signals
  • Balance audit details

Similarity chart

  • Visual ranking of candidate controls
  • Helps detect sharp quality drop-offs

Treatment drilldown

  • Detailed per-control statistics for a specific test market
  • Useful for final control acceptance decisions

How to interpret quality levels

High quality

Meaning:

  • selected controls are close and stable enough for reliable downstream analysis.

Action:

  • proceed with confidence to causal measurement.

Medium quality

Meaning:

  • usable controls exist, but match quality is mixed.

Action:

  • consider sensitivity rerun (different method/thresholds) before finalizing.

Low quality

Meaning:

  • controls are weak or poorly balanced.

Action:

  • revise test markets, improve data quality, and rerun.

Common diagnostic comments (important)

When quality is weak, read comments before deciding.

Where to read:

  • run summary comments in result details
  • narrative lines in the generated PDF summary

Comments you may see:

  • No similar markets found for selected test market(s)
  • Meaning: candidate controls do not match pre-period behavior closely enough.
  • Weak similarity / poor balance
  • Meaning: controls were found, but comparability is low.
  • Insufficient history for stable matching
  • Meaning: the pre-period window is too short/noisy for reliable pairing.
  • Quality gate fallback applied
  • Meaning: strict filters removed all candidates, so best-available fallback pair was kept.

Recommended follow-up:

  1. Revisit test market selection
  2. Increase historical window
  3. Tighten data quality checks
  4. Rerun with alternate matching method and compare results

Key terms

Similarity score

  • Numeric measure of closeness between test and control markets.
  • Higher is generally better.

Balance

  • How comparable test and control markets are on key behavior features.

SMD (Standardized Mean Difference)

  • Scale-free balance diagnostic.
  • Lower absolute values indicate better balance.

Quality score

  • Composite indicator summarizing match reliability.
  • Should be read with warnings/comments, not alone.

Decision matrix

Result patternInterpretationRecommended move
High quality + strong balanceReliable control setAccept and proceed
Medium quality + mixed balanceUsable but uncertainRun sensitivity checks
Low quality + weak balanceUnreliable controlsRedesign and rerun
No similar markets foundNo credible controlsRe-scope test markets

Reporting recommendations

Use this format in reviews:

  1. Objective and selected test markets
  2. Quality score and key warnings
  3. Final control selection rationale
  4. Risks and assumptions
  5. Next step (accept/refine/rerun)

Avoid:

  • selecting controls from similarity alone,
  • skipping balance diagnostics,
  • ignoring warning comments in low-quality runs.

Output surfaces

Typical output surfaces:

  • job details summary
  • primary results table
  • quality assessment panel
  • similarity chart and drilldown
  • PDF report and downloadable artifacts