The Art of Refined Conjecture: Using Data Marts To Go Beyond the CRM

Track: Data Analytics Symposium

Session Number: 2068
Date: Thu, Aug 1st, 2019
Time: 1:15 PM - 2:15 PM
Room: Grand Saguaro East

Description:

The customer relationship manager (CRM) is intended to be the sole source of truth about an organization's constituents. But the work of fundraising analytics is to speculate beyond the factual. Without such conjecture, our work is confined to basic reporting. Of course, CRMs allow storage of inclination models and capacity ratings, but as we start tapping unstructured data that exists outside of the CRM, it is less clear where to put the flood of information that "might" be true.

In this presentation, we will discuss the importance of a separate analytics data mart to enable advanced predictive modeling and storage of speculative insights. We will discuss ways to estimate the accuracy of such conjecture and make it actionable. Finally, we will share the infrastructure needed to tie these insights back to the data in our CRMs, and avoid remaining a permanent "shadow" system.
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 3: Data Manipulation Skills
Secondary Competency: DA:Competency 7: Fundraising Knowledge
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level II
Recommended Prerequisites: Knowledge of CRMs
Knowledge of databases
Learning Objective #1: Attendees will learn about the importance of an analytics data mart in enabling advanced predictive modeling and storage of speculative insights.
Learning Objective #2: Attendees will learn ways of estimating the accuracy of the speculative insights in an analytics data mart.
Shop Size: Small
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 3: Data Manipulation Skills
Secondary Competency: DA:Competency 7: Fundraising Knowledge
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level II
Recommended Prerequisites: Knowledge of CRMs
Knowledge of databases
Learning Objective #1: Attendees will learn about the importance of an analytics data mart in enabling advanced predictive modeling and storage of speculative insights.
Learning Objective #2: Attendees will learn ways of estimating the accuracy of the speculative insights in an analytics data mart.
Shop Size: Small