Here is what I found.
A consumer platform.
200M+ users.
The numbers told a different story.
200M+ registered users. 17M monthly active. Over 90% of the headline user base is not active monthly. The acquisition-to-retention gap is severe.
Revenue per active user is ~$6.94 per MAU. The category leader generates ~$14.75 per MAU from a smaller active base. More than 2× the monetisation efficiency.
Revenue is concentrated in a single source. The main monetised behaviour is declining. The core revenue engine is softening at the same time it dominates the books.
The constraint is not user acquisition. The platform has distribution. The constraint is converting that distribution into retained, repeat, revenue-generating behaviour.
Peer Benchmark
| Platform | MAU | Revenue | Rev / MAU |
|---|---|---|---|
| Consumer Platform ▲ SUBJECT | 17M | $118M | $6.94 |
| Category Leader | 15M | $221M | $14.75 |
This took
30 minutes.
I built an AI diagnostic tool that runs on any company.
Public data only.
30 minutes.
Imagine what I find if you give me internal data.
Revenue doesn't move in departments.
It leaks through the gaps between them.
Departments defend their own KPIs. Revenue falls through the handoffs. That is where we look first.
How it works
A public diagnostic before the first meeting. You see the gap before you commit to anything.
With internal data, we confirm the real constraint. Not the visible one. Not the loudest complaint.
90 days, embedded inside your business. One constraint. One goal. Option to extend.