Metadata
- Author: Ergest Xheblati
- Full Title:: Using Data to Find Growth Levers
- Category:: 🗞️Articles
- Document Tags:: Data Analysis,
- URL:: https://sqlpatterns.com/p/using-data-to-find-growth-levers
- Finished date:: 2024-01-14
Highlights
Since the company is still a startup, sustained user growth (preferably exponential) is a key indicator of its success (View Highlight)
I’ve learned the hard way that only when you really understand why something happens can you not only solve the problem but also explain it in simple terms. (View Highlight)
they built a model of how retention actually worked. They segmented users based on their engagement level into buckets and build a retention model. (View Highlight)
With the model created, we started taking daily snapshots of data to create a history of how all of these user buckets and retention rates had evolved on a day-by-day basis over the past several years. With this data, we could create a forward-looking model and then perform a sensitivity analysis to predict which levers would have the biggest impact on DAU growth. We ran a simulation for each rate, where we moved a single rate 2% every quarter for three years, holding all the other rates constant. (View Highlight)
This model allowed them to narrow down their focus on the blue box above (Current Users) which conveniently has an arrow looping back into itself creating a compounding effect. Current Users thus became their goal metric. (View Highlight)