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A Social Network: A Pipeline for Future Campaigns

Track: Data Science

Session Number: 3039
Date: Tue, Aug 25th, 2020
Time: 3:45 PM - 4:30 PM

Description:

Annual giving programs face the challenge of being effectively incorporated into a major gift pipeline. In particular, donors who do not qualify based on capacity are sent to stewardship or taken out of the pipeline altogether. This applies to a younger demographic (Millennials) of recent graduates who want to remain connected to their alma mater but are not identified as major giving prospects.

At Santa Clara University, we have created a Social Network to better engage our Young Alumni with the aim of increasing affinity and creating habit of investment in the institution. This Digital Space will provide a means of testing the effectiveness of university content, events and other offerings that resonate with a Millennial audience. This exchange will accomplish three objectives:
1. The creation of a machine learning algorithm to measure millennial engagement
2. Establishment of a protocols to better generate resonance between millennials and a brand (alma mater)
3. Identification of the varied personas represented within the millennial population, their role and network influence

Our findings will measure the interaction and engagement between our Leadership Annual Giving Team and a group of at least 200 young alumni through a member-only and advocate led alumni chapter. Eventually, this longer term pipeline could eventually fill major gift portfolios when the wealth capacity threshold has been met. Ultimately, we will be able to understand what brands are likely to resonate most with a Millennial population in general.
Session Type: Breakout Session (45 Minutes)

Learning Objective #1: Attendees will design programs to better engage a millennial prospect base
Learning Objective #2: Attendees will track engagement of donors and prospects via a dynamic affinity score
Software or Vendor Tools: Yes
Software or Vendor Tool Details: Python, Tablea/PowerBI
Primary Competency: DS:Competency 1: The Data Science Umbrella
Secondary Competency: RM:Competency 1: Prospect Pool/Base Analysis
Tertiary Competency: RM:Competency 2: Relationship Management Policy
Intended Audience Level: Level II
Recommended Prerequisites: Visualization platform and programming language understanding
Shop Size: Mid-Size/Large
Session Type: Breakout Session (45 Minutes)

Learning Objective #1: Attendees will design programs to better engage a millennial prospect base
Learning Objective #2: Attendees will track engagement of donors and prospects via a dynamic affinity score
Software or Vendor Tools: Yes
Software or Vendor Tool Details: Python, Tablea/PowerBI
Primary Competency: DS:Competency 1: The Data Science Umbrella
Secondary Competency: RM:Competency 1: Prospect Pool/Base Analysis
Tertiary Competency: RM:Competency 2: Relationship Management Policy
Intended Audience Level: Level II
Recommended Prerequisites: Visualization platform and programming language understanding
Shop Size: Mid-Size/Large