Pinecrest Grocers: The Test Says Ship. Should You?

Product Management
medium35 min0 submissions
Flipkart
Scenario

Pinecrest Grocers ran an experiment on its grocery product in US.

The new checkout flow was tested against control with 1,640 users per arm over 15 days. Control converted at 7.3%; the variant converted 13.4% relatively higher. The team reports the result as significant at p < 0.05.

Two details sit further down the document. The team tested 3 variants against the same control, and checked results daily, calling the test when it crossed the threshold. A guardrail metric — refund rate — rose by 2.2 percentage points, which was reported as "not significant".

The PM wants to ship on Monday.

Supporting data

design

run days
15
stopping rule
checked daily, stopped when p < 0.05
users per arm
1640
variants against one control
3

results

absolute lift pts
0.98
relative lift pct
13.4
control conversion pct
7.3

guardrails

reported as
not significant
refund rate change pts
2.2
Your task

Advise the PM. Your answer should provide:

  1. Analysis — whether this result supports the conclusion, given the sample and how the test was run.
  2. Risks — the specific ways this readout could be wrong.
  3. Recommendation — ship, iterate, or re-run, with what you would require.

State any assumptions you make.

Ready to move forward? Up next: Pallas Pharma: Plenty of Demand, Nothing to BuyNext question
How you'll be graded

80 points, 60% to pass.

  • recommendation15
  • market analysis15
  • risk assessment25
  • financial analysis25
Hint
Reveal suggested structure

Check power, then the stopping rule, then multiple comparisons, then guardrails. A p-value from a peeked test is not a p-value.