Product Analytics for Early-Stage Teams
Know what is breaking growth - and what to do next.
RevLoop brings funnels, retention, acquisition quality, churn risk, insights, and experiments into one decision layer for founders and product teams.
Built with Next.js, FastAPI, PostgreSQL, and scikit-learn.
The problem with early-stage analytics
Early-stage teams collect data, build dashboards, and still struggle to determine which action to take next.
Data is scattered
Product events, campaigns, revenue, and experiments live in separate systems with no shared context or consistent definitions.
Charts don't explain decisions
Teams can see what happened but not why it matters or which metric to fix first - so meetings end without a clear next action.
Vanity metrics hide product health
Traffic and signups can grow while activation, retention, and user quality quietly decline - invisible until it's too late.
RevLoop connects the dots
One system that takes product data from raw events to the next decision.
One product-health view
Connect acquisition, activation, retention, revenue, and churn into a single coherent picture in one schema-backed view.
Prioritized decision signals
Turn raw metrics into risks, opportunities, and recommended experiments ordered by impact, not by recency or chart position.
Closed growth loop
Move from insight to experiment, measure the result, and feed it into the next decision without losing context.
Everything needed to move from metrics to action
Six interconnected modules that form a complete product decision system.
Funnel Analysis
Track conversion between important user actions and identify the largest transition losses in your product flow.
Retention Cohorts
Understand whether users return after signup and how retention changes across acquisition cohorts over time.
Channel Performance
Compare acquisition quality using activation rate, retention, CAC, ROI, and a composite quality score per channel.
ML Churn Risk
Score users with a Logistic Regression model. Each prediction includes clear churn reasons and recommended actions.
Data-Driven Insights
Prioritize risks, opportunities, and next experiments using real product metrics combined with ML output.
Experiment Tracker
Create, run, complete, and evaluate growth experiments in one workflow - from hypothesis to measured result.
Built on a realistic product dataset
Campus Connect Demo dataset
All numbers below come from demo data - not commercial customers or live production traffic.
0
Users tracked
0
Events analyzed
0
Acquisition channels
0.0%
Activation rate
0
High-risk users identified
0
Growth experiments tracked
From product events to the next decision
Three steps, one system, zero guesswork.
Connect product data
The demo models users, events, campaigns, revenue, and experiment data in one PostgreSQL-backed data layer.
Analyze product health
RevLoop calculates funnels, cohorts, channel quality scores, churn probability via ML, and cross-module business signals automatically on each page load.
Act on prioritized insights
Teams receive specific risks, opportunities, and experiments ordered by impact - so the next action is clear without manual analysis.
The RevLoop
RevLoop doesn't stop at charts. It connects analytics to action and tracks whether the action worked.
See RevLoop turn product data into decisions.
Explore the complete dashboard, churn model, insight engine, and experiment tracker - all running on the Campus Connect demo dataset.