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Data Analyst
Datamedium19 credits

Who's Leaving, and the One Thing That Would Stop Them

Churn is up. Don't just describe it — tell them what to do.

FNorthstar Academy 4.3 (571) 3,426 taken 40m Data Analyst

The situation

Net revenue retention slipped from 108% to 96% in two quarters and the leadership team is anxious. You've been handed the usage, billing, and support data and asked the dangerous open question: 'why are customers leaving, and what should we do about it?' It's tempting to deliver a beautiful cohort chart and stop there — but the VP wants a recommendation she can fund. You'll need to separate price-sensitive churn from product-failure churn from 'they were never a fit' churn, resist the seductive single-cause story, and land on one intervention worth the company's money next quarter.

What you'll practice

Segments churn by likely cause (price, product, fit, lifecycle) rather than reporting one aggregate rate.
Segments churn by likely cause (price, product, fit, lifecycle) rather than reporting one aggregate rate.. Show it clearly — with evidence a reviewer can point to.
Avoids a single-cause narrative when the data supports multiple drivers.
Avoids a single-cause narrative when the data supports multiple drivers.. Show it clearly — with evidence a reviewer can point to.
Lands on a specific, fundable recommendation tied to the segment with the most recoverable revenue.
Lands on a specific, fundable recommendation tied to the segment with the most recoverable revenue.. Show it clearly — with evidence a reviewer can point to.
Quantifies the expected impact and acknowledges what the data can't yet prove.
Quantifies the expected impact and acknowledges what the data can't yet prove.. Show it clearly — with evidence a reviewer can point to.

The room

3 autonomous AI coworkers, each with their own agenda. They won't all agree.

M
Maya Foster
VP Customer Success
Wants: Wants budget for more CSMs and hopes the data supports headcount, not a product fix.
Style: Warm, persuasive, has a preferred conclusion.
D
Derek Lin
Head of Product
Wants: Believes onboarding is the problem and wants the analysis to point at activation, not his roadmap gaps.
Style: Confident, a bit defensive about the product.
A
Aisha Bello
Pricing Manager
Wants: Suspects a recent price increase drove the best accounts away; nervous to be blamed.
Style: Analytical, cautious, conflict-averse.

Your workspace

Real tools, pre-seeded with context. You're not roleplaying, you're working.

Code / IDE Docs / wiki Team chat

Scored on

Analytical rigorValidityCommunicationActionability

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