Revenue analytics is the practice of analyzing revenue data (where it comes from, how it trends over time, and what drives it) to inform business and product decisions. For onchain products, this extends to protocol revenue like fees, spreads, or yield, broken down by user segment or acquisition source.

Examples

• A dashboard breaks down protocol revenue by wallet cohort to see which users generate the most fees.

• A team uses revenue analytics to compare monthly recurring revenue trends across pricing tiers.

• Revenue analytics reveals that a small segment of whale wallets drives a disproportionate share of protocol revenue.

FAQs

How does revenue analytics differ from revenue attribution?

Revenue analytics focuses on understanding revenue trends and drivers broadly; revenue attribution specifically ties revenue back to acquisition touchpoints.

What onchain data feeds into revenue analytics?

Fee events, swap spreads, protocol yield, and other value-generating transactions recorded onchain.

Why combine revenue analytics with wallet analytics?

It shows not just how much revenue is generated, but which types of wallets and behaviors drive it.