We’re doing work on using data better as part of FeverBee’s coaching program.
A big part of this is building out decision trees which shows what you will do with data before you collect it.
This removes the bias from you and your team. It guides you to the right answer instead of what you want to work on.
For example, if the level of participation drops, you can create a series of binary decisions to guide you to the answer.
Building a decision tree requires creating a series of decisions which relate to an internal or external cause.
If a metric has significantly changed, it’s typically because of an internal or external cause.
Either something internal to community has changed (new design, onboarding journey, community manager etc… ) or something external has changed (new competition, changing needs, decline in customers etc..).
The decision tree means creating a series of decisions to identify the precise problems to ensure you’re working on the right solution.
There’s no point working on a new gamification program to increase participation if the problem is external to the audience. For example, if most members have solved most of their problems, a gamification problem is a waste of time.
Without decision trees in place, you’re almost certainly:
- Working on the wrong things.
- Not benefitting at all from the data you collect.
- Failing to create a system your team/next community manager can use.
If you need help, join our FeverBee Coaching program.