By the time a customer cancels, the decision was made weeks ago. Traditional metrics tell you what happened. Labelf tells you what's about to happen.
We don't guess. We learn from experience.
Our models train on everything — conversations, agent behavior, products, segments, and cohort patterns. They learn continuously. Every save and every loss makes them sharper.
When a customer hits the risk list, we don't just flag it. We deliver a complete recovery plan — what went wrong, what to say, and what to offer.
Not a playbook. A personal recovery plan.
Generic retention scripts don't work. Labelf generates an individualized action plan for each at-risk customer — based on their specific history, the agent's behavior, and what's worked for similar situations before.
- Full context summary Previous interactions, unresolved issues, and sentiment history — all summarized for the agent.
- Recommended actions Specific offers, talking points, and escalation paths tailored to this customer's situation.
- Outcome tracking Every save attempt is tracked. The model learns what worked and gets smarter with every interaction.
Your at-risk customers, prioritized
Every customer scored. Every risk ranked. Every recovery action ready — before they even think about leaving.
| Customer | Risk |
|---|---|
| Jan Lindström | Critical (100) |
| Alma Lund | Critical (94) |
| Hugo Lindberg | Critical (92) |
| Alice Lindberg | Critical (89) |
| Elsa Axelsson | Critical (87) |
| Kristina Andersson | Critical (87) |
| Per Lundberg | Critical (79) |
| Alice Nordin | Critical (75) |
| Viktor Sandberg | Critical (72) |
Click any customer. Get the full picture.
Priority actions, churn signals, retention playbooks, full journey — all generated automatically. Here's a preview.
Escalate & stabilize before she switches to competitor
Alice has called 4 times in 30 days. Her last call mentioned a competitor offer. Service still unresolved. This is her last straw.
Precision in Every Signal.
Eliminate guesswork with a system that learns from every interaction. High-accuracy predictions delivered with minimal friction.
Preventable churn identified
Cost to acquire vs. retain
Average integration window
