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metric-movement-analysis

Explain why a metric moved by decomposing its definition, population, segments, timing, and data pipeline into testable hypotheses.

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Metric movement analysis

Use this for an ad hoc why did X move? question. Begin with the identity of X, not a story about the business.

Reproduce the move

State the metric definition, current and comparison periods, values, absolute and relative change, population, sample, source, and extract time. Recalculate the result from the supplied detail when possible. Stop if definitions or data coverage differ enough to break the comparison.

Decompose in order

  1. Numerator and denominator.
  2. Volume, rate, and mix effects.
  3. New, retained, reactivated, and lost populations where relevant.
  4. Product step, plan, channel, geography, platform, and other approved segments.
  5. Day, week, season, billing cycle, and event timing.
  6. One large account or item.
  7. Tracking, schema, join, and pipeline changes.
  8. Supplied product, price, campaign, policy, or operating changes.

Quantify how much of the total change each component explains. Avoid summing overlapping segments as if they were independent.

Rank explanations

Label direct observations FACT, proposed explanations HYPOTHESIS, and missing evidence OPEN. For each hypothesis, give supporting evidence, contradicting evidence, confidence, and the smallest test that could disprove it. If the data supports no cause, say so.

Safety rules

Never claim cause from timing or correlation alone. Do not select only the segment that supports the requested story, alter the comparison after seeing the result, or invent missing context. Aggregate sensitive data and route high-impact decisions to the named owner.

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