Afraid to call your A/B test? Only copying RFM templates?
From A/B sample size and significance calls, to RFM user segmentation, to hands-on pandas cleaning: with Jueji installed, your Agent finds the Skill, runs the test and ships the segments — 3 scenarios covered.
By Jueji
How hard is real-world data analysis?
The experiment ran two weeks and the variant is up 2%. You stare at the p-value: is this significant? Is the sample size enough? Do you dare tell your boss 'ship it'? It's not that you can't compute — nobody ever taught you what steps an A/B test should follow and which traps to rule out first.
Xiaohongshu · A/B testing
You hold transactions for ten thousand users and want to know who to retain and who is about to churn — yet all you do is sort a spreadsheet by spend. The RFM model sounds fancy but it's just three dimensions: recency, frequency, monetary. When it comes to actually coding it, you don't know where to start.
Xiaohongshu · RFM analysis
The interviewer asks 'the result was statistically significant but the business saw no lift — why?' and your mind goes blank. You've bookmarked dozens of GitHub data-analysis repos and read Pandas tutorials three times, yet when it's time to clean data, run tests and plot charts, you still search line by line.
Xiaohongshu · data interviews
Real voices scattered across Reddit / Hacker News / X / dev forums — stitched together, this is what people go through when doing "python data analysis".
Lazy path · recommended
Install deep-skill-finder once — let your Agent find Skills for you
Whatever "python data analysis" task you have, MEYO already has the matching Skills. You don't need to hunt one by one — install deep-skill-finder and your Agent will auto-search MEYO's 50,000+ Skill library on every task, recommending the best match. You just say what you want to do — matching Skills is the Agent's job.
Copy → paste into Claude Code / Codex / Cursor / WorkBuddy / CatPaw · Agent installs automatically:
Please install the deep-skill-finder skill: download the archive from https://www.meyo.life/skill-finder, extract it into your local skill directory and enable it.
Or browse common-scene Skills below. Learn more about deep-skill-finder → meyo.life/skill
3 scenarios · 2 verified Skills each
Install them all, or just pick 1–2 by name. Don't worry about picking wrong — they're free, uninstall anytime.
A/B design & significance
From sample size to p-value, without guessing
For teams making data-backed calls
ab-test-analysis
TOP 1
Six-step flow · significance & ship advice
A six-step A/B result analysis pipeline: statistical significance, sample-size verification, confidence intervals, and a direct ship/scale/stop recommendation. Generates a Python script on the fly when you provide raw data — no hand computation. 23,858 verified installs via DSF; security-reviewed.
23858 users
Real hypothesis testing · power & effect size
Three scripts that actually compute: hypothesis_tester runs Z/t/chi-square tests for p-values and effect sizes; sample_size_calculator derives required samples from power/MDE; results are explained with confidence. 22,631 verified installs via DSF; security-reviewed.
22631 users
💬 Join the Deep Skill Finder Community
Trade "python data analysis" workflows with other Deep Skill Finder users and get install help
FAQ
Q: My A/B test is not significant — now what?
A: Don't jump to 'not enough sample'. Use statistical-analyst's power analysis to check whether the sample size was sufficient, then look at confidence intervals to understand the possible effect range. ab-test-analysis runs a six-step audit covering SRM checks, novelty effects and multiple-testing traps. Finally, combine with business judgment — statistical insignificance doesn't mean zero business value.
Q: How large a sample do I actually need?
A: Compute it before launching. Key parameters: significance level α (commonly 0.05), statistical power (commonly 0.8), expected lift and baseline conversion rate. statistical-analyst's sample_size_calculator derives the required sample from power/MDE; ab-test-analysis re-verifies sample adequacy during result analysis. Double insurance on both ends.
Q: How does RFM segmentation work in practice?
A: Prepare transactions as user ID + R (recency) + F (frequency) + M (monetary) and you're ready. ecom-rfm-analysis computes R/F/M scores and clusters users (Champions, At Risk, etc.), then generates a report with segment distribution and action recommendations for budget allocation. rfm classifies users into the classic 8 tiers (Champions, Need Attention, etc.) and outputs an interactive ECharts bubble chart so the value distribution is visible at a glance.
Q: Does statistical significance equal business significance?
A: No — that's the most common A/B trap. A p-value below 0.05 only says the difference is unlikely to be random noise; you still need effect size. Conversion moving from 3.2% to 4.1% is a real business lift, while 32.0% to 32.1% can be significant yet not worth shipping. statistical-analyst interprets results with effect size and confidence together — check both before deciding.
Q: Are these Skills real and safe?
A: All 6 Skills come from the Meyo community and passed security review. Install counts are measured via Deep Skill Finder: ab-test-analysis 23,858, statistical-analyst 22,631, pandasdataanalysis 6,534, pandas-data-wrangling 2,862, ecom-rfm-analysis 230, rfm 135. Click any card to open its download page.
Q: With Jueji installed, how do I trigger these Skills?
A: Just talk to your Agent in plain language — e.g. 'is this A/B result significant?', 'segment these users by RFM', or 'clean this dataset with pandas'. Jueji matches and invokes the right Skill automatically; no need to memorize Skill names.