Your analytics and your revenue are two separate datasets. That gap is costing you decisions.

Every SaaS developer sets up analytics early. Plausible, GA4, something lightweight, doesn't matter which. Then Stripe goes in for payments. Both are running, both are collecting data, and they never talk to each other.

That gap seems harmless until you're three months into acquisition and trying to figure out where to double down. You can see traffic by source. You can see MRR. But connecting a specific source to a specific paying customer requires either a custom integration, a data warehouse, or a spreadsheet that breaks the moment someone switches devices between clicking a link and signing up.

The developer instinct is to build something internal. A script that pulls Stripe events, matches them against UTM parameters, dumps it into a dashboard. It works, takes a weekend, and then someone changes the UTM structure and the whole thing needs rewriting. It becomes a maintenance liability instead of a useful tool.

The cleaner approach is connecting a tool that already does this. Faurya sits between your traffic layer and Stripe, handles the attribution matching, and puts revenue by source in the same view as your visitor data. No custom code, no pipeline to maintain.

For developers building SaaS products the tradeoff is simple. You can spend a weekend building attribution infrastructure or you can spend that weekend on product. The attribution problem is already solved, use the time on something that actually differentiates what you're building.