STAUPELL ANALYTICS GROUP - ANALYTICS EXPERTS FOR NONPROFITS, IMPROVING FUNDRAISING
  • Home
  • About
    • Staupell Team
    • Testimonials
    • Partnerships >
      • Prospect Research Institute
      • Lityx
      • TouchPoints
      • Gravyty
  • Services
    • Fundraising Analytics
    • Prospect Development
    • Business Intelligence
    • Database Administration
    • Fundraising Optimization Solution
  • Training
    • Analytics Machine Learning Artificial Intelligence
    • Business Intelligence Visualization Reporting
    • Prospect Research and Management
    • Webinars
    • Classes >
      • Beginner Analytics Using R
      • Analytics Classes
      • Skill Builder Series
    • Workbooks
  • Blog
  • Events
    • Water Cooler Chats
    • Video Replays
  • Contact
  • Product

Driven by Data Blog

Lifetime Value, Single Gift, and Movement: A Review of Dependent Variables in Giving

4/20/2016

1 Comment

 
Picture
Most data mining and donor modeling projects include one dependent variable compared to several independent variables. Let’s review these concepts briefly before we get into the meat of this article.

The dependent variable represents the question that needs to be answered. Think of it as filling in this sentence: “[What you need to know] depends upon….” The “depends upon” are the independent variables, which we explain next. Examples include a donor’s next gift amount, acceptance or rejection to a request, or relative level of engagement (however you define engagement).
 
Dependent variables can be categories (usually two, such as “yes” or “no”) or continuous values (such as gift size).
 
The independent variables are those that demonstrate a relationship with the dependent variable. They answer the remainder of the sentence above. For instance, if the dependent variable is the donor’s next gift, then the sentence would read, “The donor’s next gift is dependent upon [a set of independent variables].”
 
Very few events or people can be described by one characteristic, and so independent variables tend to number more than one. Some of the models I’ve used have over a dozen.
 
A sample of independent variables interplaying with the dependent variable looks like this:
 
“The donor’s next gift is dependent upon the donor’s last gift plus the donor’s age plus whether the donor lives in the same geography as our organization.” In programming terms, the result is actually an equation, since the independent variables are also a assigned a weight to describe their relationship to the dependent variable, and our example would look like this after the equation is determined:
 
Next gift = (last gift * 1.05) + (age * 507) +(if donor’s geography = our geography then .453 else 0)
 
Dependent Giving Variables - In data mining, we frequently choose the dependent variable that is easiest to acquire from our primary databases. Most often, we start with the prospect’s lifetime giving. However, we want to be careful when thinking about which giving variable is measuring what we want to see. Here is a smattering of giving variables and their uses.
 
Lifetime Giving measures only lifetime customer value. In addition, it is often directly related to the length of time a prospect has been involved with your organization, especially for consistent givers. So, lifetime giving values tend to favor older donors.
 
Giving per Year in System reduces the effect of length of time by dividing lifetime giving by number of years in your system. For instance, a prospect became a member of your organization in 1999 and her giving is $10,000. So, her giving is an average of $1,000 per year for her lifetime ($10,000/10 years). You are still measuring lifetime customer value, but removing the effect of age/length of involvement.
 
Highest Gift/Pledge measures a donor’s single highest gift or pledge. Note that major gifts tend to be pledges, so it is best to measure pledges for this variable. This is my favorite variable for looking for major gifts prospects.
 
Velocity or Consistency measures a donor’s recent behavior, whether she is escalating her giving or whether she is giving consistently. I use these variables for annual giving studies. Velocity is calculated as (last full year’s giving/average(previous 3 years giving)).
 
Distances help measure the amount of required cultivation for different level gifts. Measure the distance from first to first major gift (major gifts), from entry date to first gift (annual giving), or from lowest gift to highest gift (major gifts or high-end annual giving) –hoping that the lowest gift came first.
 
Which are you interested in? Let us know. Tweet us - @Staupell
1 Comment
kate goldberg
4/20/2016 02:19:51 pm

In the recent neural network models that I have been building, I have seen success with using the "first gift" amount along with other non-giving characteristics to determine if they will be major or minor donors.

Reply



Leave a Reply.

    Keep Informed
    Sign up for
    notifications when a
    new post comes out

    Sign Up Now


    Authors

    Marianne Pelletier has more than 30 years of experience in fundraising, with the majority in prospect research and prospecting.

    Greg Duke helps Raiser’s Edge clients to optimize their database by implementing data clean-up techniques and creating reporting structures, including dashboards and SQL queries.  He also facilitates data imports into Raiser’s Edge and database administration.

    Categories

    All
    Advancement Svcs
    Annual Giving
    Artificial Intelligence
    Assessment
    Big Data
    Blackbaud
    Branding
    Dashboards
    Databases
    Data Management
    Data Mining
    Data Prep
    Dependent Variables
    Donor Modeling
    Efficiency
    Engagement
    GDPR
    Giving Variables
    Linear Regression
    Machine Learning
    Major Gifts
    NFT
    Participation
    Productivity
    Project Planning
    Prospecting
    Prospect Research
    Push Technology
    Raiser's Edge
    RE NXT
    Reporting
    Research Pride
    RFM
    Statistics

    Archives

    March 2023
    February 2023
    January 2023
    December 2022
    October 2022
    September 2022
    August 2022
    July 2022
    June 2022
    May 2022
    April 2022
    March 2022
    February 2022
    January 2022
    March 2021
    September 2020
    June 2020
    May 2020
    March 2020
    February 2020
    July 2019
    May 2019
    March 2019
    December 2018
    September 2018
    May 2018
    March 2018
    September 2017
    June 2017
    March 2017
    January 2017
    December 2016
    September 2016
    June 2016
    April 2016
    March 2016
    February 2016
    January 2016
    December 2015

    View my profile on LinkedIn
Picture
© COPYRIGHT 2023 Staupell Analytics Group. ALL RIGHTS RESERVED.
  • Home
  • About
    • Staupell Team
    • Testimonials
    • Partnerships >
      • Prospect Research Institute
      • Lityx
      • TouchPoints
      • Gravyty
  • Services
    • Fundraising Analytics
    • Prospect Development
    • Business Intelligence
    • Database Administration
    • Fundraising Optimization Solution
  • Training
    • Analytics Machine Learning Artificial Intelligence
    • Business Intelligence Visualization Reporting
    • Prospect Research and Management
    • Webinars
    • Classes >
      • Beginner Analytics Using R
      • Analytics Classes
      • Skill Builder Series
    • Workbooks
  • Blog
  • Events
    • Water Cooler Chats
    • Video Replays
  • Contact
  • Product