PE portfolio SaaS optimization: funnel fixes, pricing clarity, and support automation that drove 7× revenue growth.
Find where users stalled
I started with session replays and funnel cuts on each product. Onboarding drop-off clustered in the same places: too many decisions before first value, pricing pages that listed features when buyers wanted outcomes, and activation steps that assumed power-user patience.
We wrote one paragraph per product before any roadmap: where users quit, what job they came for, and what proof we had that the fix would move revenue.
Fix the first ten minutes
The biggest lifts came from shortening paths to first value. We cut onboarding steps, prefilled defaults where data allowed, and rewrote pricing around the job the buyer already named in sales calls.
On one product, activation moved when we surfaced a sample output on first login. On another, pricing conversion moved when we dropped a tier nobody selected and named the middle plan after the buyer segment that actually closed.
Automate routine support tickets
For a marketing platform build, we routed tickets through intent classification and self-service flows before they hit humans. Response time dropped roughly 90%. Automated resolution cleared 80%+ of routine requests so the team could focus on billing edge cases and integration bugs.
We prototyped routing rules with real ticket samples, released weekly, and tracked deflection rate as the primary metric.
Measure what the firm funded
Every change linked to activation rate, pricing conversion, churn, or support cost. I built simple dashboards the partners could read without a product translator.
Portfolio revenue moved 7× over the engagement. Most of that traceable lift came from onboarding, pricing, and support cost moves.