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Prospect Management in the Age of Analytics

Track: Data Science

Session Number: 3122
Date: Wed, Aug 26th, 2020
Time: 12:15 PM - 1:00 PM

Description:

In this session, we will explore how visual analytics can refine prospect management protocols so that they are tailor-made for any institution. We will discuss challenging questions that arise throughout the fundraising process and see how analytics can help answer them. As we take a tour of various fundraising dashboards, attendees will learn how to adapt prospect management policies and practices to help increase fundraising productivity.
Session Type: Breakout Session (45 Minutes)

Learning Objective #1: Attendees will identify opportunities at their own institutions to use analytics in a way that enhances current prospect management practices.
Learning Objective #2: Attendees will learn how to question assumptions and analyze how their institution may differ from what is “typical,” using visual analytics as a guide.
Software or Vendor Tools: No
Primary Competency: DS:Competency 2: Project Management
Secondary Competency: RM:Competency 1: Prospect Pool/Base Analysis
Tertiary Competency: RM:Competency 6: Prospect Strategy
Intended Audience Level: Level II
Recommended Prerequisites: Basic understanding of relationship management and experience with data analysis.
Shop Size: All Shop Sizes
Session Type: Breakout Session (45 Minutes)

Learning Objective #1: Attendees will identify opportunities at their own institutions to use analytics in a way that enhances current prospect management practices.
Learning Objective #2: Attendees will learn how to question assumptions and analyze how their institution may differ from what is “typical,” using visual analytics as a guide.
Software or Vendor Tools: No
Primary Competency: DS:Competency 2: Project Management
Secondary Competency: RM:Competency 1: Prospect Pool/Base Analysis
Tertiary Competency: RM:Competency 6: Prospect Strategy
Intended Audience Level: Level II
Recommended Prerequisites: Basic understanding of relationship management and experience with data analysis.
Shop Size: All Shop Sizes