The bar chart below illustrates the breakdown of Intents users by sectors based on their last 10 transactions.
It is evident that over 80% of users interact with DEXs and DeFi platforms, while only around 5% of their activities are in the NFT space.

The accompanying heatmap provides a comprehensive view of user activities across origin networks.
As the data reveals, NEAR users are predominantly DeFi enthusiasts, whereas EVM chain users are primarily focused on DEX activities.

This time, we’ll filter for specific users to distinguish between power users and normies. Then, we’ll conduct individual Intents interaction studies on them.

Pareto Charts

We’ll keep the segmentation simple by applying the 80-20 Pareto Rule. This approach identifies the users generating 80% of the total fee amount, labeling them as power users, while the remaining addresses are categorized as normies. This method is particularly useful when we expect a heavy skew in transaction distribution.

With this segmentation, we can study their usage patterns. For instance:

• Do power users interact with Intents more frequently?

• Are normies more active overall than power users?

Let’s dive in and find out.

Pareto Charts Are Not the Only Segmentation Technique!

While the Pareto Chart is a useful tool, it’s not the only segmentation technique available—this is just one example! Can you think of other ways to slice up your user base? For example:

• Users farming for airdrops

• Heavy DEX users

• Users with specific transaction patterns

It’s important to note that this analysis looks at addresses retrospectively and is not designed to predict user behavior in advance.

The analysis is conducted using queries from the near.defi.fact_intents table and other sources referenced in the credits. The filter syntax includes log_event = 'mt_transfer' to evaluate cross-chain transfer metrics.

Once the transferrer wallet addresses are identified, we track their activity on origin chains to determine their sector preferences. This is achieved by analyzing their last 10 transactions.

Finally, we categorize these users into power users (the most active participants in the NEAR ecosystem) and normies based on their activity levels.

This dashboard provides a comprehensive view of cross-chain transfer metrics, user activity, and sector preferences, offering valuable insights into the behavior of power users and normies within the NEAR ecosystem.

Credits

My dashboard was inspired by Flipside Team, from whom I forked some queries to use as a basis for my analysis!

Orig. dashboards:

1. NEAR Intents | Insights

2. Retention Metrics Workout