---
schema_version: "1"
id: f8adf2c45e2bdf1ca60ef6f1df3c291fbf17def380bd7de6198909e24d689e60
title: Predictive Insight Input Fields
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/sfdo/264-0-0/efn_predictive_insight_input_fields.md
canonical_url: https://help.salesforce.com/s/articleView?id=sfdo.efn_predictive_insight_input_fields.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 9c01df5a3a44bf68cae5ab650ad7a2f45bcf1106bc3e70ab079f5c02397cfea3
description: Learn more about data that is parsed to generate predictive insights.
products:
  - Nonprofit
release: "264"
---
# 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)](https://help.salesforce.com/s/articleview?id=sfdo.nonprofit_success_pack.htm). Depending on jobs that are initiated by admins, bulk data is analyzed by using [Einstein Prediction Builder](https://help.salesforce.com/s/articleview?id=sales.custom_ai_prediction_builder.htm&type=5) 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 Fields | Nonprofit 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 Fields | Nonprofit 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 Fields | Nonprofit 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 Fields | Nonprofit 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 |   |