Analytics in Raiser's Edge NXT: Export With ProspectPoint Models 7352

Analytics in Raiser's Edge NXT: Export With ProspectPoint Models


You have the ProspectPoint predictive models in Raiser’s Edge NXT and you need to export the results. This blog will review tips for when you need to use Export rather than Query or Lists to analyze Ratings.

If you are new to ProspectPoint predictive models--including Annual Giving Likelihood (AGL), Major Giving Likelihood (MGL), Planned Giving Likelihood (PGL), and Target Gift Range (TGR)--I recommend Blackbaud University’s Target Analytics: Basics of Modeling training session and the Knowledgebase articles on “What is a Target Analytics Likelihood Score” and “What are the Target Gift Range values.”

A great rule to live by in Raiser’s Edge is that a user should use Query to group records and Export to extract data, however you may find that the options for configuring Ratings in Export are limited. You are not alone! I’ve worked with many other organizations that have come to this same conclusion. 

In the “Basic Lists With ProspectPoint Models” and “Basic Queries With ProspectPoint Models” blog posts in this series, I explain the benefits of using Lists and Queries—rather than Export—to view and analyze your model scores and ratings. The most significant benefit is that you can select a specific Rating to display in each column. The challenges with Lists and Query often point to the selection of fields to display. For instance, you may need to include summary totals of this year’s giving vs. last year’s giving, their top 3 constituent codes, or other one-to-many fields. There may be a good reason to go to Export but be wary—you may find yourself with more cleanup work in Excel. 

Check out the “The Best Reporting Tool” blog post to compare the functionality of Lists, Query, and Export to group and analyze by Ratings. I hope this will help you to determine the best tool to use for your analytics reporting.

If you conclude that you need to use Export, then here are some tips to reduce your spreadsheet cleanup efforts. First, let’s start by walking through how to include Ratings in your Export.
  • Create a New Export to export Constituents with the format of a CSV or XLSX file. 
  • On the General tab, include a query of constituents to export. For instance, constituents with Major Giving Likelihood (MGL) greater than or equal to 701 and Target Gift Range (TGR) equals $100,001. Select other applicable options. 
  • On the Output tab, add your desired fields. To add Ratings, navigate to Prospect (if you have the RE:Search module) > Ratings in the available fields section. Select or drag and drop the Category field into the Output section to the right.
  • You will be prompted to enter the Ratings group criteria—essentially configuring which Ratings you want to display. Below are examples for importing vs. syncing, respectively, the models from ResearchPoint to assist with the remaining steps.
    • Change the radio button selection to “Selected Records” and select only 1 Rating Source to the right.
    • Enter the maximum number of Ratings to display for that source. For instance, if you have up to 3 Ratings in the Blackbaud Analytics’ Custom Modeling Service Source for a constituent, then enter 3. Note: For organizations syncing models from ResearchPoint, you may have additional data appear in the results other than just the ProspectPoint model scores. You can always modify this number later if you have too many or too few columns to display the Ratings.
    • Optional: Enter a start date. This is important for organizations with multiple years of ProspectPoint models in the database. It is also a tip to help better sort the Ratings when you export the data.
    • Select OK to create the Ratings group.
  • ​​​​​​​​​​​​​​Add Description under the Ratings group header. Add additional fields as desired, for example Source and Date Added.
  • ​​​​​​​​​​​​​​Repeat the process above creating new group criteria for each Rating Source, as needed.
  • Right-click on each field, choose Custom Heading and type a logical name. For instance, Category becomes “ProspectPoint Model” and Description becomes “ProspectPoint Model Score.”
  • Preview the export and adjust the Ratings group criteria as needed. The screenshots below are sample previews for imported and synced Ratings, respectively. You can see how sometimes the different types of Ratings are in the same column when exported.
  • Export to a spreadsheet when ready.
Note: If you are looking to use Export for other Ratings, such as the Raiser’s Edge NXT Analytics, use the same process above but select the appropriate Rating Source and number of Ratings to extract.

Now that you’ve exported the results into a spreadsheet, let’s clean up the spreadsheet so it is ready to share to your team. When preparing a spreadsheet for my boss or a colleague, my goal was to make the data as clear and concise as possible. It took time, but it was worth it to get fewer questions coming back after I sent them the spreadsheet. 

Here are some cleanup tasks to consider for your analytics analysis:
  • Sort, copy, and paste the values in the ProspectPoint Model (Category) and PropectPoint Model Score (Description) so that each ProspectPoint Model Rating scores display in unique columns, for example so only Major Giving Likelihood scores will be in that column.
  • Rename the ProspectPoint Model Score (Description) columns with the name of the ProspectPoint Model, for example ProspectPoint Model Score_1 may become “Major Giving Likelihood” or “MGL.”
  • Delete the ProspectPoint Model (Category) columns as they are no longer necessary with new column headers.
After cleanup, the completed spreadsheet may look something like this:

Export is a great tool for extracting data from Raiser’s Edge, however it is not always the best tool to use when reporting on Ratings. If you find that Query and Lists do not quite meet your needs, try Export but keep in mind that you may have additional cleanup work to prepare the spreadsheet before it is ready to be shared with your team. Weigh the benefit of including more robust fields in the output with the challenge of increased manual cleanup in the exported spreadsheet.

I hope you found this blog post helpful in clarifying how to use Export to extract Ratings data, especially for the ProspectPoint models. I will post additional tips about using Export for other models, such as Affluence Insight and the Raiser’s Edge NXT Analytics in the coming weeks.

Do you have other Ratings Export tips you would like to share? Comment below to share with the Community!
Blog Raiser's Edge NXT Blog 12/30/2020 10:00am EST

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David Lee David Lee Jan '21
Thanks for this great writing up Shelley.