What exactly is Dataro predicting when we say 'RG Churn' or 'DM Appeal'. This article will tell you the modeling objective for each model in your system.
Appeal Models
Dataro DM Appeal: How likely is a donor, who has made any financial contribution ever, to give to a Direct Mail appeal in the next 3 months?
Dataro DM Appeal >$500: How likely is a donor, who has made any financial contribution ever, to give $500 or more to a Direct Mail appeal in the next 3 months?
Dataro DM 24M Lapsed: How likely is a donor, who hasn't given anything in >= 24 Months, to give to a Direct Mail appeal in the next 3 months?
Recurring Giving Models
Dataro RG Churn: How likely is a donor, with an active recurring gift, to cease their commitment in the near future?
More technically the model is trained to predict a donor with an active RG at the reference date, who makes no successful >$0 RG transactions between 90 and 180 days after the reference date. This captures both ‘active’ and ‘passive’ churn and works across organisations with different churn definitions.
Dataro RG Reactivation: How likely is a donor, with a canceled recurring gift, to resume RG payments in the near future?
Dataro RG Upgrade: How likely is a donor, with an active RG, to increase their payment amount in the near future?
Conversion to RG Models
Convert to RG: How likely is a donor, who has made any single gift ever, to convert to Regular Giving in the near future?
Mid-Level Giving Models
Mid-Level Giving: How likely is a donor, who has made any financial contribution ever, to give between $500 and $5000 (mid-level giving range) cumulatively in the next 12 months. (Note: the thresholds for your mid-level program may be different and can be adjusted to $1000 - $10,000).
Stewardship Models
Major Giving: How likely is a donor, who has made any financial contribution ever, to give >$5000 (major giving range) cumulatively in the next 12 months. (Note: the threshold for your 'major' giving program may be different and can be adjusted to >$10,000 or >$25,000).
Gift in Will: How likely is a donor, who has made any financial contribution ever, to leave a gift in will.
And finally, a word about 'Scores' and 'Ranks'
You will have noticed that each Dataro model comes with two new fields in your CRM: the 'Score' field and the 'Rank' field.
Scores: Propensity scores are a number on a scale from 0-1, and approximate the probability of a person doing a particular thing. The higher the score, the higher the probability of an individual taking the associated action. So if we were trying to predict direct mail giving, a person with a score of 0.76 would have roughly a 76 percent chance of giving in the upcoming DM appeal.
Ranks: Ranks tell you how likely a donor is compared to everyone else in the database. So a person with Rank 1 is the most likely to take a particular action, and rank 10,000 is the 10,000th most likely.
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