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Einstein for Nonprofits Managed Package
Predictive Insight Input Fields

Predictive Insight Input Fields

Learn more about data that is parsed to generate predictive insights.

Einstein for Nonprofits parses and analyzes data from Nonprofit Success Pack (NPSP). Depending on jobs that are initiated by admins, bulk data is analyzed by using Einstein Prediction Builder or Backup Models to generate predictions about constituents.

Insights and scores from Einstein Prediction Builder or Backup Models can be used to segment or target specific constituents to further refine the prediction output.

First-Time Donor

Predictive insights about constituents becoming first-time donors provides fundraising employees with an understanding about which supporters, with no previous donations, can be converted to donors. However, there are no guarantees about who becomes a first-time donor. The tool predicts future donors based on on past giving and similarities with other donors.

This table shows Einstein Prediction Builder input fields.

Standard Contact FieldsNonprofit Success Pack Contact Fields
Birthdate npe01__PreferredPhone__c
Email npe01__Preferred_Email__c
Title npe01__Work_Address__c
Description npe01__Primary_Address_Type__c
  npe01__Other_Address__c
  npe01__Secondary_Address_Type__c

This table shows Backup Models input fields:

Standard Contact FieldsNonprofit Success Pack Contact Fields
Birthdate npe01__Primary_Address_Type__c
HomePhone npsp__Current_Address__c
MailingCity  
MailingCountry  
MailingPostalCode  
MailingState  
MobilePhone  
Phone  

Recurring Donor

Predictive insights about constituents becoming recurring donors provide nonprofit fundraising staff with an understanding about supporters who can be converted to repeat donors. However, there are no guarantees as to who becomes a recurring donor or about the ability to predict future revenue from recurring donations.

This table shows Einstein Prediction Builder input fields.

Standard Contact FieldsNonprofit Success Pack Contact Fields
Title npe01__AlternateEmail__c
Birthdate npo02__AverageAmount__c
  npo02__Best_Gift_Year_Total__c
  npo02__FirstCloseDate__c
  npe01__Home_Address__c
  npsp__Largest_Soft_Credit_Amount__c
  npsp__Number_of_Soft_Credits__c
  npsp__Number_of_Soft_Credits_Last_N_Days__c
  npsp__Number_of_Soft_Credits_Last_Year__c
  npsp__Number_of_Soft_Credits_This_Year__c
  npe01__Other_Address__c
  npe01__Preferred_Email__c
  npe01__PreferredPhone__c
  npe01__Primary_Address_Type__c
  npo02__SmallestAmount__c
  npo02__Soft_Credit_Last_Year__c
  npo02__Soft_Credit_This_Year__c
  npo02__Soft_Credit_Total__c
  npo02__Soft_Credit_Two_Years_Ago__c
  npe01__Work_Address__c

This table shows Backup Models input fields:

Standard Contact FieldsNonprofit Success Pack Contact Fields
MailingPostalCode npe01__WorkEmail__c
MailingState npe01__HomeEmail__c
MailingCity npe01__AlternateEmail__c
Email npe01__WorkPhone__c
Phone npsp__Do_Not_Contact__c
HomePhone  
MobilePhone  
IsEmailBounced  

Top Donor

Top donors are constituents whose donation amounts fall within the top 25% of all contributions over the last 36 months. Predictive insights about constituents becoming top donors provides nonprofit fundraising staff with an understanding about constituents who donate enough to move them past the top-donor threshold. However, there are no guarantees as to who donates in the future or about future revenue amounts from donors.

This table shows Einstein Prediction Builder input fields:

Nonprofit Success Pack Contact Fields 
npo02__OppsClosedLastNDays__c  
npo02__OppsClosedLastYear__c  
npo02__OppsClosedThisYear__c  
npo02__OppsClosed2YearsAgo__c  
npe01__Primary_Address_Type__c  
npo02__SmallestAmount__c  
npo02__NumberOfClosedOpps__c  

This table shows Backup Models input fields:

NPSP Contact Fields 
npo02__OppsClosedLastNDays__c  
npo02__OppsClosedLastYear__c  
npo02__OppsClosedThisYear__c  
npo02__OppsClosed2YearsAgo__c  
npe01__Primary_Address_Type__c  
npo02__SmallestAmount__c  
npo02__NumberOfClosedOpps__c  
 
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