Finding WHY is a process of discovery, not invention.
The process of increasing in size, generally customers.
Growth features are generally experimental in nature and we don't have enough data points to support the success of the feature.
It is a hard problem.
As the data-based decision has more of a "fancy" keyword so to support these "intuition-based" features they put some biases in data.
As a leader - you might hear sentences like below when the product manager pitches you the gut or intuition-based features.
- I feel this would work ...
- I have seen it working for other players ...
- The XYZ reports state that ...
What do we need?
- Customer Interviews - To know the pain of the customers
- Early Adopters - To run experiments successfully
- Iterative feature release planning and measuring outcomes at every step.
How to Define a Good Growth Feature?
- Go through customer interviews, list down all the problems which customers talked about in the interview. Find the most common problems.
- Define the customer segment on which the experiment would be running.
- How would it impact the early adopter's life?
- How to track the impact - lagging and leading indicators?
- What are the success metrics of the feature with the given few early adopters?
- Start Small and define an iterative feature path.
- Put down the adverse impact of the growth features clearly.
- Never oversell a growth feature.