Using Recommender Systems to Identify Prospect Interests

Track: Data Science

Session Number: 2005
Date: Thu, Aug 1st, 2019
Time: 10:30 AM - 12:00 PM
Room: Grand Sonoran C-D

Description:

The University of Colorado is in the process of implementing a collaberative filtering based recommender system to assist in identifying what prospect's donation area(s) of interest are.

The presentation will go over why and how the system was developed, how the system was matched to fundraising business needs, and how the model is being evaluated for effectiveness.

Note: This is an advanced subject, and an understanding of programming fundamentals (eg: R or Python), as well as the basics of linear algebra are recommended (though not required) to get the most out of this presentation.
Session Type: Breakout Session (90min)

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 7: Fundraising Knowledge
Intended Audience Level: Level II
Recommended Prerequisites: Understanding of matrix multiplication. Data manipulation techniques. Programming (preferred R and/or Python experience).
Learning Objective #1: Attendees will understand how to build a collaborative filtering based recommender system to identify prospect's donation area of interest using programming languages such as Python and/or R.
Learning Objective #2: Attendees will learn how to implement a recommender system in an applied way to support fundraising business needs.
Shop Size: All Shop Sizes
Session Type: Breakout Session (90min)

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 7: Fundraising Knowledge
Intended Audience Level: Level II
Recommended Prerequisites: Understanding of matrix multiplication. Data manipulation techniques. Programming (preferred R and/or Python experience).
Learning Objective #1: Attendees will understand how to build a collaborative filtering based recommender system to identify prospect's donation area of interest using programming languages such as Python and/or R.
Learning Objective #2: Attendees will learn how to implement a recommender system in an applied way to support fundraising business needs.
Shop Size: All Shop Sizes