From Manual Reports to Real-Time Creator Data
How HeroHero doubled subscriptions while replacing gut feel with daily data on 10,000+ creators.
2×
Subscription growth during cooperation
10,000+
Creator profiles unified
Seconds
To answer a business question (vs hours before)
The Challenge
Scaling at Speed: Building the Visibility to Match Growth
HeroHero is a creator economy platform connecting content creators with their subscribers. Subscription revenue flows through Stripe. Traffic data accumulates in Google Analytics. When the engagement began, 5,000+ active creators were generating data across both systems, and the platform had more raw information than most companies its size. What it did not have was a way to bring that information together.
Creator performance existed only as intuition. Getting answers to basic questions, which creators are growing, where subscribers are churning, which cohorts are strongest, required manual exports, spreadsheet work, and hours of effort. Time spent on reporting was time not spent on growth.
In short: the data existed. The infrastructure to use it did not.
The Solution
A Unified Data Model Built Around the Creator
Stratodata built a custom data pipeline connecting HeroHero's core data sources into a single, creator-level view, updated daily.
What Was Built
Stripe transaction data structured into a creator-level data warehouse
Google Analytics traffic data merged per creator, measuring volume and source alongside subscription metrics
Accounting and marketing data connected as the pipeline grew over time
Daily automated updates replacing manual reporting cycles entirely
Custom MCP built on top of selected BigQuery datasets
Client analyses data via Claude AI
Technology stack
The Breakthrough
For the first time, all 5,000+ creator profiles appeared in a single view with daily updates. What had previously required hours of manual assembly was now live and queryable. And as HeroHero grew, past 5,000 creators, then 10,000, the pipeline grew with it. Google Analytics, accounting, and marketing data followed, each connected to the same foundation.
The Results
Data as a Growth Condition
Subscription growth of 2× since the start of the engagement is the headline number. Stratodata may not have caused that growth, but we created the conditions for it: data accessible in seconds, decisions grounded in numbers, no manual reporting overhead. The time that used to go toward assembling reports went back to the team. HeroHero's team directed that freed capacity toward growth.
What changed
- Creator performance tracked by number, not instinct: identifying fastest-growing accounts and understanding what separates them
- Reporting time reduced from hours of manual work to seconds
- No dependency on the tech team for ad hoc analysis: business questions answered from dashboards or by asking Claude directly
- A clean, scalable data model as the foundation for AI-powered analytics
"Reporting used to be the slow, time-consuming task that repeatedly held us back. We decided that had to change. Stratodata proved to be a strong partner, they built and now manage a custom data solution for us. What started as connecting Stripe data has grown: today we have Google Analytics, accounting, and marketing all integrated. It saves us time, and with instant access to data through reports or AI, I get the answers I need. We can redirect our time and energy toward growth. I especially enjoy querying my data via Claude to get instant insights into our current business performance."
Vojtěch Knyttl
Co-founder, HeroHero
Beyond Retail
Custom Solutions for Non-Standard Problems
Stratodata's primary focus is retail and e-commerce. That is where our deepest expertise sits, and where we have delivered measurable results for clients across European markets.
The HeroHero engagement is a different kind of proof point. Creator economy is not retail. The data model looks different, the business questions are different, and the integration requirements are different. However, building it well required the same fundamentals: a coherent data architecture, reliable pipelines, and a clear understanding of what the business actually needs to see.
If your business generates data across multiple systems and the answers you need are not where you can reach them, the domain almost certainly does not matter. The problem is structural, and the solution is the same regardless of your industry: a data foundation built around how your business actually works.
If that sounds familiar, we are worth a conversation.