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Data Analyst
DatamediumFree

Where the Funnel Springs a Leak

Conversion fell at one step. Find the step, then find the cause.

FFinderk Originals 4.7 (314) 1,256 taken 35m Data Analyst

The situation

Bookings are down 9% week-over-week and nobody knows where in the funnel it's bleeding. You have a five-step funnel — search, results, select, payment, confirm — and the aggregate number hides which step broke. The marketing team swears traffic quality is fine; engineering swears nothing shipped; the payments team is quietly aware of a new fraud rule that went live. Your job is to localize the break to a specific step and segment, separate 'fewer people arriving' from 'fewer people converting', and point to the most likely cause before the daily revenue meeting at 4 PM.

What you'll practice

Localizes the drop to a specific funnel step and segment instead of citing the aggregate.
Localizes the drop to a specific funnel step and segment instead of citing the aggregate.. Show it clearly — with evidence a reviewer can point to.
Separates a decline in volume from a decline in step conversion rate.
Separates a decline in volume from a decline in step conversion rate.. Show it clearly — with evidence a reviewer can point to.
Connects the broken step to a plausible cause (e.g., the new fraud rule) with supporting evidence.
Connects the broken step to a plausible cause (e.g., the new fraud rule) with supporting evidence.. Show it clearly — with evidence a reviewer can point to.
Delivers a clear pointer for the 4 PM meeting without prematurely blaming the wrong team.
Delivers a clear pointer for the 4 PM meeting without prematurely blaming the wrong team.. 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.

J
Jordan Pace
Growth Marketing Manager
Wants: Wants to prove the top of funnel is healthy so the blame doesn't land on his campaigns.
Style: Defensive, quick to point downstream.
P
Priscilla Tan
Payments Product Manager
Wants: Shipped a stricter fraud rule last week and hopes it isn't the culprit.
Style: Conscientious, will admit it if cornered with data.
B
Ben Alvarez
Engineering Lead
Wants: Insists there were no relevant deploys and resents being pulled into 'data problems'.
Style: Blunt, evidence-driven, short on patience.

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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