Case Study — The Relationship Psychics
Rebuild the product.
Connect the customer journey.
A founder using paid acquisition couldn't see what was happening inside his product. We made the invisible visible — and fixed what the data revealed.
The Relationship Psychics
Tom Cote, Founder
Tom Cote is the founder of The Relationship Psychics — a company dedicated to providing personalized relationship guidance. Paid acquisition on Meta. Revenue through Stripe.
The problem: Paid acquisition brought users into the product. But everything between the click and the charge was a black box.
A Disconnected
Black Box
Tom checked Stripe every morning. Revenue was up or down. He couldn't answer the most basic questions:
Why did revenue vary between days?
Which sessions were actually making money?
What did a user who renews look like vs. one who leaves after an early session?
Marketing data lived in Meta. Product data lived in the app. Revenue data lived in Stripe. None of them talked to each other.
Before we were working with them, we were just in a spot where so much technical debt, so many issues, our system was unscalable, relying on humans at every single element of the process.
— Tom Cote, Founder
Disconnected data
Marketing, product, and financial data in three separate silos. No unified view of the user lifecycle.
Crushing technical debt
Legacy code, manual processes at every step. The system couldn't scale without breaking.
Human bottlenecks
Every element of the process relied on manual intervention. Growth was capped by headcount.
Rebuild. Connect. Reveal.
Tom didn't need a consultant with a slide deck. He needed a team that could come in, rebuild the infrastructure, and make the invisible visible.
Phase 1
Rebuild the stack
Rapidly rebuilt the entire tech infrastructure — scalability at the core. Eliminated legacy code and human bottlenecks. Processes that required manual intervention became automated.
Phase 2
Connect the data
Connected the three layers that had never talked: acquisition (Meta), engagement (product), and revenue (Stripe). For the first time, Tom could see the full lifecycle — session by session, dollar by dollar.
Phase 3
Reveal the leaks
The Lifecycle Lens surfaced what had been invisible: Session-level revenue, differences between user segments, and returning-user flows that needed investigation.
Phase 4
Fix what the data showed
Armed with the diagnostics, we updated product flows: eliminated the dead-end flow, built personalized follow-ups for high-value users, and updated the returning-user experience.
They've come in and completely and very quickly re-energized our entire tech stack, rebuilt everything in a way that makes it so much more scalable.
— Tom Cote, Founder
A clearer view of the customer journey.
Sessions
connect engagement with revenue
Users were entering, hitting a dead-end flow, and leaving without completing a paid reading. Every one of those sessions cost ad spend to acquire.
Segments
inspect differences between users
The team examined user segments and personalized follow-ups. They were getting the same generic experience as everyone else.
Return visits
review returning-user flows
Returning-user flows became part of the product review and implementation work.
Before & After
Before Clarity
Check Stripe. Revenue is up or down. No idea why.
Marketing, product, and revenue data in three silos
Manual processes at every step — growth capped by headcount
Technical debt and legacy code blocking every improvement
Returning-user experience without a unified diagnosis
After Clarity
See exactly which campaigns drive high-value sessions
Full lifecycle view: acquisition → engagement → revenue
Automated processes with AI personalization at higher quality
Scalable tech stack rebuilt from the ground up
Personalized follow-ups and returning-user flows implemented
Implementation scope
The engagement combined a tech-stack rebuild, lifecycle-data integration, and personalized follow-ups. These changes describe the work delivered; they do not isolate the effect of any one API or product change on revenue.
Tom didn't need more ads. He didn't need a new product.
He needed to see what was happening inside — and a team that could fix what the data revealed.
Product infrastructure, lifecycle visibility, and personalized follow-ups.
Is your product
a black box?
Start with Sprint Zero. We connect your marketing, product, and revenue data into a single view — then scope the agent or workflow changes to evaluate. AI-native services start at $100k+.