Case Study: a global consumer-networking company achieves 25% more renewals with Inferenz

Predictive Analytics for a Global Consumer-Networking Brand​

Inferenz partnered with a global consumer-networking company to address its significant data challenges. The client, which operates in over 150 markets, was struggling with disparate data formats that blocked campaign-to-sale links, stalled support updates, and left churn models outdated. This was compounded by tens of millions of unstructured JSON events daily, which slowed development cycles and drove up costs with separate data pipelines for each project.

The solution implemented by Inferenz involved unifying all event data under a common schema and applying a low-code rule engine for real-time predictive insight. This allowed the client to onboard new event types 80% faster and reduced processing costs by 40%. Most significantly, Inferenz's predictive models, which used gradient-boosted trees to flag churn risk, helped the company increase customer renewals by 25% by sending targeted offers when risk was highest.