This is what AppScope told me about itself today.

No dashboard to configure. No funnel to build. Just an AI reading the behavioral data and telling me exactly where users are leaving and why.

"Users are bouncing fastest from your login page (avg 2 seconds), suggesting friction or confusion before they even get started. Audit the login flow for errors, unclear CTAs, or slow load times , even a minor fix here could unlock access to the rest of your funnel."

That's the kind of insight that used to require a data analyst, a BI tool, and a week of digging.

AppScope surfaces it automatically.

But an honest not is that this masks a hypothesis as a measured fact.
So today, I am ripping out the standard "AI Insight" text box and replacing it with a Scientific Method UI. Instead of letting the AI act like a know-it-all oracle, the output is being physically separated into three distinct blocks:

🔍 1. The Evidence
What the DOM/database actually saw. (e.g., "84 sessions idled on #password-input for >8 seconds before exiting.")

🧠 2. The Inference
What the AI suspects is the friction point. (e.g., "Hypothesis: Password requirements are hidden until validation fails.")

🧪 3. The Falsification Experiment
How to explicitly prove the AI wrong. (e.g., "Display password rules in plain text. If idle time does not drop below 3s for the next 50 users, this hypothesis is invalid.")

Still in beta. Still free. Looking for founders who want to know why their users are leaving.
try it out here : https://shiny-malasada-5a8b3a.netlify.app/