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Weekly orders on a food delivery app fell: find out why
You run the case. Read the prompt, answer questions from the notes below, and share data only when the candidate asks for it or gets stuck. Score at the end.
Case timer
00:00
1. Read the prompt aloud
Read it slowly, then pause. Let the candidate ask questions before they structure.
Fictional and illustrative. You are the product manager for a food delivery app in Bengaluru, India. Weekly orders fell from 500,000 to 460,000 in one week. Active users fell from 250,000 to 230,000. Android users fell from 150,000 to 130,000 while iPhone users stayed at 100,000. A new Android version was released that week. What happened, and what do you do?
2. Answers to clarifying questions
This case has no scripted clarifying answers. Answer from the prompt, and say "assume what you think is reasonable" if the prompt does not cover it.
3. A model structure
Compare the candidate's structure with this one. A different split can be just as good if it is clean and fits the problem.
- Weekly orders = active users x orders per user
- Active users
- By platform: Android and iPhone
- New and returning
- Orders per user
- Outside causes: holidays, weather, a rival's offer
4. The working, step by step
Each step shows how a strong candidate works it out. Share a new fact from it only when the candidate asks or is stuck, and let them do the math: the result in the dark box is what they should reach.
Step 1: Size the drop
What a strong candidate does: Weekly orders went from 500,000 to 460,000. Work out the fall as a percentage.
Fall in weekly orders (percent): (500,000 - 460,000) ÷ 500,000 × 100 = 8
Step 2: Orders per user before
What a strong candidate does: Orders divided by active users in the week before.
Orders per user before: 500,000 ÷ 250,000 = 2
Step 3: Orders per user after
What a strong candidate does: Orders divided by active users this week.
Orders per user after: 460,000 ÷ 230,000 = 2
Step 4: Where the lost users are
What a strong candidate does: Android lost users while iPhone did not. Work out what share of the users lost were on Android.
Share of lost users on Android (percent): (150,000 - 130,000) ÷ (250,000 - 230,000) × 100 = 100
The recommendation to listen for
At the end, say: "The CEO walks in. What is your recommendation?"
The whole 8 percent drop comes from fewer Android users opening the app. Orders per user held at 2, so the fall is not in how often people order. All of the 20,000 lost users, 100 percent, were on Android, in the same week as a new Android release. My hypothesis is that the release broke something, for example sign-in or the home screen on some phones. Today I would check crash and sign-in rates for the new version. If they confirm it, I would go back to the old version or fix the new one. Then I would watch Android users return to about 150,000. As a guardrail, I would check that the fix does not raise payment failures. I would pause the planned feature work for a day, because a broken app costs more orders than any new feature adds.
Risks a strong answer names: A rival's Android-only promotion could also explain the drop; Some users may not come back even after the fix.
Next steps: Compare crash and sign-in rates for the old and new Android versions; Add an alert on Android active users by app version.
Score the candidate
Score each criterion from 1 to 5. A 2 or a 4 sits between the descriptions.
This case has no exhibit. Score Exhibit reading on how the candidate used the data you gave them: did they pick out the number that matters and say what it means?
Total
0 out of 25
Score all five criteria to see the band and the feedback template.
Next: another case in Partner mode
Swap roles and run the next case, so you both practise answering and scoring.