Power Users vs Normies: Who's returning and driving substantial trade volume?

This time, let's filter for specific users—distinguishing between power users and normies.

We'll then conduct individual cohort retention studies on them.

The premise remains the same as before. Whether we study by user, metric, or event, the underlying query remains consistent.

The key difference is adding a label (when possible) to these addresses.

Creating a Pareto Chart

1. Group the data by the launch date, which is 2023-03, to calculate the total traded volume for each address.

2. Calculate the cumulative count of addresses, starting with the address having the highest volume.

3. Normalize the cumulative sum of each address by dividing it by the total volume of all addresses.

4. Apply labels: Addresses representing less than 0.8% of the total sum are labeled as "Power," while others are labeled as "Normie."

Optional: Utilize dense_rank() to rank addresses by total volume in descending order and generate a chart for validation.

For power users, observe the remarkable retention! This underscores the importance of segmentation, steering away from a single rate for analysis. Interestingly, normies significantly contribute to the overall blended retention rate.

Comparing volumes, normies fall behind power users. However, their volume retention is comparable, indicating their relative spending propensity despite lower wallet sizes.