Real-Time Analytics Dashboard
How we built a customer intelligence platform that reduced churn by 34% for a growth-stage SaaS company.
Project Overview
A growth-stage SaaS company needed to understand why customers were leaving. Their existing analytics were batch-processed overnight with no real-time visibility. By the time they identified at-risk accounts, it was too late.
They engaged Syslice to build a real-time customer intelligence platform that could ingest millions of events daily, surface actionable insights, and predict churn before it happened.
The Challenge
The client's data was scattered across multiple sources — product usage logs, support tickets, billing events, and CRM records. There was no unified view of customer health.
They needed a platform that could process 2M+ events daily in real time, run predictive models against that data, and present the results in an intuitive dashboard that non-technical team members could act on.
Our Solution
We designed and built a full-stack analytics platform with four core components.
Real-Time Data Pipeline
Event ingestion layer using Kafka and streaming processors that handle 2M+ events per day with sub-second latency.
Predictive Churn Models
ML models trained on historical data to identify at-risk accounts 30 days before churn, with 85%+ accuracy.
Interactive Dashboard
React-based analytics interface with drill-down capabilities, cohort analysis, and automated alerting for the customer success team.
API & Integrations
RESTful APIs connecting the platform to Salesforce, Intercom, and Stripe for a unified customer health view.
Technologies Used
“Syslice delivered what two previous agencies couldn't. Our customer success team now has real-time visibility into account health, and churn has dropped significantly.”
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