Event Propensity Scoring

Estimate the likelihood that a profile or subscription will perform a defined business event within a future window. Use the scores to prioritize eligible audiences for conversion, engagement, or retention.

Choose a scoring use case

Business need	Mode and scoring grain	Example target
Prioritize likely purchasers	Generic event propensity; one score per profile	order_completed
Identify registration or trial opportunities	Generic event propensity; one score per profile	registration_completed or trial_started
Prioritize content engagement	Generic event propensity; one score per profile	premium_content_viewed
Anticipate subscription cancellation	Subscription lifecycle propensity; one score per profile and subscription	cancellation_requested

Generic mode learns from the timing and mix of behavioral events. Subscription mode also reconstructs subscription state and history, with optional behavioral signals such as usage or content consumption.

For retention, choose a target that leaves time to act. A cancellation request can be more actionable than the effective subscription end. Subscription mode requires mappings for starts, cancellation requests, and ends even when only one movement is the prediction target.

How it works

Training uses historically observable subjects from the configured event streams. The current User model defines who can receive a score; it does not filter that historical training population.

When you create an Event Propensity intelligence, DinMo starts training on your event history. Once training succeeds, DinMo calculates the first scores for your selected population. You do not need to create a separate prediction. You can change how often scores are refreshed from the intelligence overview.

Outputs include a score, a training-reference percentile, a score band, up to three signed local reason families, and scoring history. Interpret a score as a probability only when its score semantics confirm calibration. Percentiles and reasons support prioritization and interpretation; they do not prove that a campaign will change the outcome.

If you need to choose which individual product or offer to show, use Product Recommendations. Event Propensity predicts an event, not an item ranking.

Documentation guide

Start here	What you will learn
Prepare your data	Technical prerequisites, raw event mappings, subscription history, input limits, and readiness thresholds.
Configure and refresh	Target and horizon choices, training, scoring populations, and refresh schedules.
Understand performance and scores	Temporal evaluation, probability, percentile, signed reasons, and warehouse outputs.
Use results and best practices	Actionable targets, leakage risks, audience selection, experiments, and monitoring.

Event Propensity Scoring must be enabled for your workspace. Confirm access with your DinMo administrator or customer success contact.