Introduction to Simulation Analytics for Fundraising

Track: Data Analytics Symposium

Session Number: 1097
Date: Wed, Aug 8th, 2018
Time: 10:15 AM - 10:45 AM

Description:

Synopsis: Simulation analytics is one of the fastest-growing segments of data analysis. Companies like Amazon, Target, Wal*Mart, and even your favorite sports team use simulation analytics every day to identify potential client behavior and to maximize future results. Dr. Duke will show you how to harness the incredible power of simulation analytics, and demonstrate that you don’t need messily expensive software or a doctorate in statistics to start using it today!

Topics to be discussed will include:
--Examples of simulation
--Concepts of simulation analytics: Random number generation, algorithms, and model verification
--Problems in fundraising which can be addressed by simulation
--Technique #1: Using a Monte Carlo simulation to predict gift income
--Technique #2: Building a capacity algorithm by using trendlines
Sub-Categorization: Enterprise Track
Session Type: Breakout Session

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 7: Fund Raising Knowledge
Intended Audience Level: Level I, Level II
Recommended Prerequisites: Excel. Secondary (helpful but not required): SPSS, Tableau
Learning Objective #1: Attendees will be able to understand the concepts of simulation analytics
Learning Objective #2: Attendees will learn how to build a sample simulation and an algorithm for donor or event attendee behavior
Shop Size: All Shop Sizes
Sub-Categorization: Enterprise Track
Session Type: Breakout Session

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 7: Fund Raising Knowledge
Intended Audience Level: Level I, Level II
Recommended Prerequisites: Excel. Secondary (helpful but not required): SPSS, Tableau
Learning Objective #1: Attendees will be able to understand the concepts of simulation analytics
Learning Objective #2: Attendees will learn how to build a sample simulation and an algorithm for donor or event attendee behavior
Shop Size: All Shop Sizes