test-analysis
Analyze creative test results using heatmaps and data visualization to identify statistical winners and recommend next steps (scale, iterate, or kill). Use when reviewing test performance, making optimization decisions, or planning next test phases.
npx skills add majiayu000/claude-skill-registry --skill test-analysis-walkerhi11-mediabuy-plugins-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Test Analysis Analyze test results and recommend actions. ## Process ### Step 1: Input Performance Data Gather metrics: - CPL (Cost Per Lead) - CPA (Cost Per Acquisition) - CTR (Click-Through Rate) - CVR (Conversion Rate) - Spend per creative - Initiate checkouts (leading indicator) - Time period data ### Step 2: Create Heatmap Visualization **For 2x2 or 2x2x3 Tests:** ``` | Ad Text 1 | Ad Text 2 | ---------|-----------|-----------| Headline1| CPA $X | CPA $X | Headline2| CPA $X | CPA $X | ``` **Color Coding:** - Green: Below target CPA - Yellow: At target CPA - Red: Above target CPA **For Avatar/Image Tests:** ``` | Image 1 | Image 2 | Image 3 | ... ---------|---------|---------|---------|---- Avatar 1 | $CPA | $CPA | $CPA | Avatar 2 | $CPA | $CPA | $CPA | ... ``` ### Step 3: Identify Statistical Winners **Winner Criteria (Jason K):** - Doesn't lose more than 1x in 3 days - Doesn't lose more than 2x in 7 days - Consistent performance over time **Statistical Confidence:** - Minimum spend: 1.5-2x target CPA - Minimum conversions: 10+ for confidence - Look at trends, not single days **Leading Indicators:** - Initiate checkout CPA = ~1/3 of purchase CPA - High CTR + low CVR = lander
- Process
- Step 1: Input Performance Data
- Step 2: Create Heatmap Visualization
- Step 3: Identify Statistical Winners
- Step 4: Categorize Results
- Step 5: Output Analysis Report
- Analysis Framework
What does the test-analysis skill do?
Analyze creative test results using heatmaps and data visualization to identify statistical winners and recommend next steps (scale, iterate, or kill). Use when reviewing test performance, making optimization decisions, or planning next test phases.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill test-analysis-walkerhi11-mediabuy-plugins-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.