What Does "Big Data" Mean for Fundraising Analytics?

Track: Data Science

Session Number: 2060
Date: Thu, Aug 1st, 2019
Time: 4:15 PM - 5:15 PM
Room: Grand Sonoran C-D

Description:

Fundraising analytics teams in 2019 look much like the fundraising analytics teams of 2009. Many have been dealing with similar budgets, staffing levels, responsibilities, and have even been solving the same problems for over a decade. In the meantime, data science has hugely transformed the for-profit customer service experience. Why is fundraising apparently lagging behind? How can we catch up? Should we even try?

For over two years, the University of Michigan has wrestled with these questions. Frustrated with our team’s stagnancy and lack of progress toward the "big data" panacea, we reached out to colleagues at several large and innovative data savvy companies to cut through the hype and discover what we can learn from their successes.

This presentation will share our findings around the surprising similarities and differences between analytics in the for-profit and non-profit sectors. We will also share our in-progress plan to evolve our fundraising analytics program and ensure that in 2029 it will not look anything like it does in 2019. This will include a review of the technological and staffing infrastructure our team is building, as well as the language we've used to make a case to leadership that the transformation is worthwhile.
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 6: Strategic Management & Communication
Secondary Competency: CA:Competency 6: Campaign Analytics, Reporting and Data Management
Tertiary Competency: DA:Competency 7: Fundraising Knowledge
Intended Audience Level: Level II
Recommended Prerequisites: The intended audience is organizations that have an established analytics team, though organizations hoping to add one may also benefit.
Learning Objective #1: Attendees will be equipped with benchmarks that compare the state of non-profit analytics to for-profit
Learning Objective #2: Attendees will learn about the technological and staff infrastructure needed to create a "big data" focused analytics team
Shop Size: Mid-Size/Large
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 6: Strategic Management & Communication
Secondary Competency: CA:Competency 6: Campaign Analytics, Reporting and Data Management
Tertiary Competency: DA:Competency 7: Fundraising Knowledge
Intended Audience Level: Level II
Recommended Prerequisites: The intended audience is organizations that have an established analytics team, though organizations hoping to add one may also benefit.
Learning Objective #1: Attendees will be equipped with benchmarks that compare the state of non-profit analytics to for-profit
Learning Objective #2: Attendees will learn about the technological and staff infrastructure needed to create a "big data" focused analytics team
Shop Size: Mid-Size/Large