Better Together: Visualizing Annual Giving Efforts to Predict Donor Activity

Track: Data Analytics Symposium

Session Number: 2017
Date: Wed, Jul 31st, 2019
Time: 1:30 PM - 2:30 PM
Room: Grand Saguaro East

Description:

Using a combination of predictive data and descriptive data, the Office of Annual Giving (OAG) at Johns Hopkins University is developing a communication formula to determine when a constituent is most likely to make a gift to the institution. This formula will be used to tie the work of the marketing team, the data team, and the gift officer team together to provide a 360 degree view of a constituent and, using data visualizations, engage new users across the division in data analytics.
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Secondary Competency: DA:Competency 4: Statistical Techniques and Competencies
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level I, Level II
Recommended Prerequisites: Tableau, Excel, Fundraising, Databases
Learning Objective #1: Attendees will learn about products being developed using a large database and Tableau visualizations in the fundraising field at a higher education institution.
Learning Objective #2: Attendees will lean how they can implement a similar data-driven product at their organization.
Shop Size: Mid-Size/Large
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Secondary Competency: DA:Competency 4: Statistical Techniques and Competencies
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level I, Level II
Recommended Prerequisites: Tableau, Excel, Fundraising, Databases
Learning Objective #1: Attendees will learn about products being developed using a large database and Tableau visualizations in the fundraising field at a higher education institution.
Learning Objective #2: Attendees will lean how they can implement a similar data-driven product at their organization.
Shop Size: Mid-Size/Large