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Product managementintermediate

21. Help workshop visitors find a reason to return

Investigate a drop in repeat visits and choose one test without assuming reminders are the answer.

The brief

A neighborhood arts center wants more people to return after a first free workshop. Develop a focused product proposal: decide what to learn, which change to test and what evidence would justify a next step. Explain why your proposal addresses a visitor need rather than only improving a dashboard.

  • Of 80 first-time visitors last month, 12 attended again within four weeks. No reasons for leaving were recorded.
  • Workshops have 20 seats; popular evening sessions fill while weekday sessions often have empty seats.
  • A coordinator can support a four-week test with $600 and no added classes. Visitors may decline follow-up messages.

Constraints

Test budget≤ 600 dollars
Declare test spending and account for each planned expense.
Existing class capacity
Work within the current classes and 20-seat limit; avoid improving repeat visits by displacing everyone new.
Voluntary contact
Keep participation and any follow-up contact optional.
Honest interpretation
Separate observed behavior from a claim that the proposed change caused it; name an important uncertainty.

What to cover

  1. 01

    Problem hypotheses

    Offer at least two plausible reasons for low return visits and choose a small discovery activity that could distinguish them.

  2. 02

    One testable change

    Describe the audience, benefit, smallest change, non-goals and why it follows from your evidence or stated assumptions.

  3. 03

    Measures and decision

    Define who counts in the comparison, how you will observe returns, a guardrail for new visitors and a continue/change/stop rule.

  4. 04

    Delivery and tradeoff

    Allocate the budget and coordinator’s work; explain one rejected alternative and what you would do if popular sessions fill sooner.

Worked designs

No worked design has been published for this brief yet. You can start an attempt and share your approach in the discussion.

Review rubric

AI feedback uses these criteria. Scores are practice feedback.

Diagnosis before solution

Uses competing hypotheses and a useful discovery activity without inventing findings.

30points

Focused visitor value

A feasible change addresses the chosen need and makes exclusions explicit.

25points

Evidence and decision rules

The comparison, return measure, access guardrail and uncertainty support an honest decision.

30points

Feasible delivery and tradeoffs

Budget, limited class capacity, voluntary contact and the rejected alternative are considered.

15points

Discussion

Share an approach, ask a question, or tag @Coach.

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