Live application
https://happyco.talapartners.com/
HappyCo Resident Retention is a public product case study that shows how AI signals and operational workflows can help property teams reduce resident turnover.
The product is designed to help teams spot resident risk earlier, coordinate interventions, and improve retention through service recovery, support workflows, and better visibility.
This repository is built to show product management ability, not just code.
Short demo showing the retention intelligence workflow and product thinking behind the system.
- How residents are prioritized by churn risk
- How operational drivers explain the risk signal
- How the system recommends intervention actions
- How projected savings and ROI guide decisions
Direct video link (opens in new tab)
Shows at risk residents, recommended retention actions, and projected financial impact.
Resident facing interface where interventions are delivered through service support and retention credits.
Residents can apply retention credits toward services that improve their experience.
The resident retention platform combines resident risk scoring, friction driver analysis, intervention workflows, and financial impact modeling.
Core flow
Resident Data → Risk Signals → Friction Drivers → Intervention Engine → Retention ROI Tracking
Resident Risk Signals
Identifies residents showing patterns associated with dissatisfaction or increased churn risk.
Friction Driver Analysis
Highlights the main operational or service issues contributing to retention risk.
Intervention Engine
Maps residents into recommended action tiers such as outreach, concierge support, or retention credits.
Retention ROI Tracking
Estimates projected savings, credit cost, and net return from intervention decisions.
Property teams often realize a resident is at risk too late.
Signals are scattered across service issues, complaints, leasing activity, and team notes.
Even when risk is noticed, the follow up process is often manual, inconsistent, and hard to track.
This creates real business problems:
- preventable resident turnover
- inconsistent retention actions
- weak visibility into what is working
- reactive instead of proactive operations
This platform brings together:
- resident risk visibility
- intervention workflows
- service booking
- retention credits
- manager dashboards
The goal is to give property teams one system for identifying risk and taking action early.
- identify an at risk resident
- review resident details and service history
- trigger an intervention
- offer support, booking, or credits
- track follow through and outcome
Uses the platform to review resident issues, trigger interventions, and improve resident experience.
Uses the platform to track team follow through and monitor retention activity.
Uses the platform to understand retention trends and intervention results.
This repository is meant to show:
- product problem framing
- user workflow design
- technical collaboration
- prioritization and tradeoffs
- roadmap thinking
- product communication
Planned product documents:
docs/problem-statement.mddocs/personas.mddocs/prd.mddocs/workflows.mddocs/metrics.mddocs/decision-log.mddocs/roadmap.md
The application includes a frontend, backend, database workflows, and a live deployment for demonstration.
A large share of my highest value product work cannot be shared publicly.
This repository is designed as a public case study to show how I think through a product problem, define the workflow, work across technical systems, and structure a product for delivery.
The platform is designed around three product principles.
Early Risk Detection
Surface churn signals before dissatisfaction becomes irreversible.
Operational Explainability
Show the drivers behind each risk score so property teams understand why residents are flagged.
Actionable Workflows
Prediction alone is not enough. The product integrates intervention decisions and financial impact modeling directly into the workflow.
Future iterations would focus on:
- stronger churn prediction
- better intervention recommendations
- clearer retention analytics
- deeper property system integrations
- improved manager reporting