Start Small, Prove ROI, and Grow as You Go

Reef’s model stacking approach creates feedback loops that measure model accuracy and improve your data so that all models perform better. This enables you to get started quickly and add models as you prove value.

Big Deal Finder

Reef’s big deal finder is a machine learning model that generates big deal pipeline with customers by 1) identifying and analyzing your best large expansion from the last year and 2) scanning all of your current customers and scoring them to find the customers most likely to produce deals like your past big wins.

Targeted Cross-sell

Selling new products into existing customers is usually scatter-shot and unstructured resulting in poor conversion rates and wasted resources. Reef’s targeted cross-sell model scores and identifies customers most likely to convert.

Competitive Churn Blocker

Losing too many customers to a competitor? Stop getting surprised and score your customers for competitive churn risk with Reef’s Competitive Churn Blocker model.

Churn Predictor

The key to reducing churn is early warning and early action. Reef’s Churn Predictor model score’s customers based on churn risk at renewal, well in advance of the renewal date. This allows you to engage at-risk customers 6-9 months in advance to mitigate churn risk.

Healthscore 2.0

Do you have a healthscore that you find helpful but you can’t calculate how accurate it is? Plug your existing healthscore into Reef to calculate and visualize score performance over time so you can tune and improve it.