Savvy Data Selection and Visualization Empowers You to Evaluate Donor Potentials

Track: Data Analytics Symposium

Session Number: 1039
Date: Thu, Aug 9th, 2018
Time: 2:00 PM - 3:00 PM

Description:

Session Attendees will learn how to wisely select, compare, and visualize two data points with the end of evaluating donors, portfolios, and pipelines. Advancement Research Analyst and former educator, Dr. Stephen Lambert, will gently guide Attendees through three scenarios, three calculations, and three visualizations. These three techniques come from Susquehanna University’s Data-Driven Portfolio Evaluation tools. Attendees will receive examples, guidance, formulas, and follow-up help. Attendees will learn how to empower Gift Officers and Relationship Managers. Focus will be on middle, large, and planned giving prospects. Attendees will understand how to rescale data to “compare apples to apples.” The Presenter will demonstrate manipulation of predictive models, capacity, affinity, and recency as few have seen before. The Presenter will demonstrate thresholds for Gift Officer portfolio inclusion/exclusion. Attendees will see these actions performed in both MS Excel and IBM SPSS Modeler (with easy reference to IBM SPSS Statistics if Attendees desire).
Sub-Categorization: Start-Up Track
Session Type: Breakout Session

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Tertiary Competency: DA:Competency 6: Communication
Intended Audience Level: Level I
Recommended Prerequisites: Basic familiarity with a spreadsheet program such as Excel or a statistics program such as SPSS or a data mining program such as Modeler.
Learning Objective #1: Attendees will learn three data pairings for improved prospect description and ranking.
Learning Objective #2: Attendees will learn three data visualization methods for improved prospect, portfolio, and pipeline evaluation.
Shop Size: All Shop Sizes
Sub-Categorization: Start-Up Track
Session Type: Breakout Session

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Tertiary Competency: DA:Competency 6: Communication
Intended Audience Level: Level I
Recommended Prerequisites: Basic familiarity with a spreadsheet program such as Excel or a statistics program such as SPSS or a data mining program such as Modeler.
Learning Objective #1: Attendees will learn three data pairings for improved prospect description and ranking.
Learning Objective #2: Attendees will learn three data visualization methods for improved prospect, portfolio, and pipeline evaluation.
Shop Size: All Shop Sizes