The page provides the default definitions of Predictable’s scoring populations for each model. Note: all historical and prediction windows are customizable to fit a particular need or use case.

Summary Table

MODEL TYPE HISTORICAL WINDOW PREDICTION WINDOW ADDITION CRITERIA
PURCHASE PROPENSITY 90 30 Must have made a purchase / clicked email / triggered web event within historical window
CHURN 365 180 Must have made a purchase within historical window
LTV 365 365 Must have made a purchase / clicked email / triggered web event within historical window
NEXT PURCHASE 180 90 Must have made first purchase within historical window
PRODUCT RECOMMENDATION 365 N/A Must have made two purchases within historical window
ENGAGEMENT INDEX 365 N/A Must have clicked an email or triggered a web event within historical window

Purchase Propensity

Scoring Criteria

In order to be scored by the Purchase Propensity model, a customer must have done one of the following actions within the last 90 days:

  • Made a purchase
  • Clicked an email
  • Triggered a web event

If a customer does not fit this criteria, they are dropped out of the scoreable population and will not receive updated scores.

Scoring Output

Predicted Score: represents the likelihood a customer will make a purchase in the next 30 days.



Churn

Scoring Criteria

In order to be scored by the Churn model, a customer must have made a purchase in the last 365 days.

If a customer does not fit this criteria, they are dropped out of the scoreable population and will not receive updated scores.

Scoring Output

Predicted Score: represents the likelihood a customer will not make a purchase in the next 180 days.



Lifetime Value (LTV)

Scoring Criteria

In order to be scored by the LTV model, a customer must have done one of the following actions within the last 365 days:

  • Made a purchase
  • Clicked an email
  • Triggered a web event

If a customer does not do this, they are dropped out of the scoreable population and will not receive updated scores.

Scoring Output

Predicted Score: represents the likely total amount a customer will spend in the next 365 days.



Next Purchase

Scoring Criteria

In order to be scored by the Next Purchase model, a customer must have made their first purchase in the last 180 days.

If a customer does not fit this criteria, they are dropped out of the scoreable population and will not receive updated scores.

Scoring Output

Predicted Score: represents the likelihood a customer will make their 2nd purchase in the next 90 days of the score date.



Product Recommendation

Scoring Criteria

A customer must have made two distinct purchases within a 365 day window for the transactions to be eligible for this model.

If a customer does not fit this criteria, they are dropped out of the scoreable population and will not receive updated scores.



Engagement Index

Scoring Criteria

In order to receive an Engagement Index value, a customer must have done one of the following actions within the last 365 days:

  • Clicked an email
  • Triggered a web event

If a customer does not fit this criteria, they are dropped out of the scoreable population and will not receive updated scores.