Use research and funnel data before choosing a solution.
Defining the Growth Problem
Maya and Lena open the workshop by comparing twelve user interviews with the latest funnel data. Their goal is to define the most important problem without treating an early signal as a confirmed cause.
- Participants
- Maya - Growth Marketing Manager / Lena - Product Analytics Lead
Conversation
- Maya
Before we choose channels or tactics, what did we learn from the user interviews?
- Lena
Most users liked the idea of planning a week in ten minutes, but several expected a team project tool.
- Maya
So our promise attracts attention, but it may not set the right expectation.
- Lena
That is one possibility. The funnel also shows that only 46% of trial users complete their first weekly plan.
- Maya
Where is the biggest drop before that activation point?
- Lena
Many users create an account, open the blank planner, and leave before adding a priority.
- Maya
Can we say that the blank state causes the drop?
- Lena
Not yet. It is a strong signal, but we still need an experiment to isolate the effect.
- Maya
Then our working problem is weak expectation-setting plus friction before the first useful outcome.
- Lena
Agreed. We should measure message fit and first-plan completion separately.
Core expressions
- set the right expectation
- help people understand what a product will and will not do
- activation point
- the first action that shows a user has experienced useful value
- biggest drop
- the stage where the largest share of users leaves a funnel
- isolate the effect
- test one factor clearly enough to estimate its impact
- working problem
- a current problem definition that may change with new evidence
Your practice task
Give a 60-second problem statement. Include one user insight, one funnel signal, one uncertainty, and the metric you would investigate next.