Dont get lost in the hype focus on

































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Don’t get lost in the hype: focus on data that matter November 17, 2017 Copyright © 2016 Bentz Whaley Flessner Copyright © 2015 Bentz Whaley Flessner © Copyright 2013 Bentz Whaley Flessner 0
Remember…. Copyright © 2016 2015 Bentz Whaley Flessner 1
Introductions Copyright © 2015 Bentz Whaley Flessner 2
Agenda § Welcome and Introductions § Perspective: Where is analytics for fundraising heading? § Outcome focused W B n F ! h tc pi a t o N § Technique focused § Wrap up and Questions Copyright © 2016 2015 Bentz Whaley Flessner 3
About me aoftelie@bwf. com 651 -253 -6364 @aoftelie linkedin. com/in/alexoftelie Curren t Former Copyright © 2016 2015 Bentz Whaley Flessner 4
Where are we headed? Copyright © 2015 Bentz Whaley Flessner 5
Proper focus Data Technology / Technique Goals Outcome Copyright © 2016 2015 Bentz Whaley Flessner 6
Where are we headed? § Thinking about donors vs how we do business § Driving intent through behavioral understanding § Borrowing more technical approaches from business world § Limitations of ”latest trends” (ie Social Media) Copyright © 2016 2015 Bentz Whaley Flessner 7
Countless Non Profits are leveraging their data Descriptive Analytics Predictive Analytics Copyright © 2015 Bentz Whaley Flessner 8
Countless Non Profits are leveraging their data Copyright © 2015 Bentz Whaley Flessner 9
Lets focus on ourselves Copyright © 2015 Bentz Whaley Flessner 10
Countless Non Profits are leveraging their data Who Will Renew? Will Churn? Will Upgrade? Will Give for first time? When Will they give? Why Do they give? Do they lapse? How Much will they give? Copyright © 2015 Bentz Whaley Flessner 11
Emerging Approach: Leverage your potential by applying predictive analytics within, not just on Constituents Who will close largest gifts? will close highest volume of gifts? Why did we not meet our goal? did we exceed expectations? When will he hit our goal? How much will we raise? best case/worst case? Copyright © 2015 Bentz Whaley Flessner 12
Internal Focus in Action: Confronting Assumptions of performance Assumptions Performance § Not always “apples-to-apples” § GLM allows control for tenure, portfolio capacity, etc Business Understanding Communication Avg Gift 2014 -2016 Gift Officer 1 $22, 000 $24, 550 Gift Officer 2 $17, 500 $16, 550 Gift Officer 3 $45, 200 $23, 750 * Adjusted Bentz Whaley Flessner Copyright © 2015 Bentz Whaley Flessner 13
Internal Focus in Action: Prediction through rigorous Business Understanding $ 3, 000 $ 2, 500, 000 Assumptions $ 2, 000 $ 1, 500, 000 Business Understanding $ 1, 000 $ 500, 000 Communication $FY 11 FY 12 FY 13 FY 14 FY 15 PR 16 PR 17 PR 18 PR 19 PR 20 Giving Lower CI Upper CI Copyright © 2015 Bentz Whaley Flessner 14
Internal Focus in Action: Communication is the key to understanding not only behavior, but intent. Assumptions Business Understanding Communication Copyright © 2015 Bentz Whaley Flessner 15
Emerging technical frontiers Copyright © 2015 Bentz Whaley Flessner 16
Countless Non Profits are leveraging their data New techniques for Status Quo Choose Your Own Adventure Listen At Scale Leverage machine learning to sharpen insight quality Decision Optimization provides dynamic outlooks into success Understand: what is said, what matters, what doesn’t Copyright © 2015 Bentz Whaley Flessner 17
Countless Non Profits are leveraging their data New techniques for Status Quo Choose Your Own Adventure Listen At Scale Leverage machine learning to sharpen insight quality Decision Optimization provides dynamic outlooks into success Understand: what is said, what matters, what doesn’t Copyright © 2015 Bentz Whaley Flessner 18
Machine Learning “lite” § Currently popular ”iterative” algorithms § Random Forrest (Random Trees) § Known Nearest Neighbor § Support Vector Machines § Neural Networks § Used to address common fundraising analytics questions like § Likelihood of contribution § Gift amount § Segmentation of donors Bentz Whaley Flessner Copyright © 2016 2015 Bentz Whaley Flessner 19
Machine Learning “heavy” § “The science of getting computers to act without being explicitly programmed” § “Systems that can learn from data” Data Copyright © 2016 2015 Bentz Whaley Flessner 20
Machine Learning: Requirements Motion! 90% of the world’s data is in motion 90% of non profit communities data is at rest Copyright © 2016 2015 Bentz Whaley Flessner 21
Machine Learning: Requirements Machine Learning Considerations - Thoughtful about preparation Copyright © 2016 2015 Bentz Whaley Flessner 22
Choose your own adventure New techniques for Status Quo Choose Your Own Adventure Listen At Scale Leverage machine learning to sharpen insight quality Decision Optimization provides dynamic outlooks into success Understand: what is said, what matters, what doesn’t Copyright © 2015 Bentz Whaley Flessner 23
Choose your own adventure: optimization § Third branch of Analytics § Concept of constraints! § Think many moves ahead § Less guess work Applications -Resource Allocation § Portfolio Optimization - assignment § Prioritization of asks/messaging § Impact of resource changes on goals and timeline Copyright © 2016 2015 Bentz Whaley Flessner 24
Choose your own adventure: optimization Spray and Pray NO MORE! A translation of your business problem into math… Business goals / KPIs Increase Private Annual. Gift Support Levers / decisions affecting goals How to allocate channel, ask, and message Business “rules” constraining decisions Lean targeted outreach, goals, timeline Model objectives Maximize Private Gift Support Model variables Giving History Predictive Models Channel Preference Model constraints Response Rates Cost per ask Interest Areas Copyright © 2016 2015 Bentz Whaley Flessner 25
Listen at Scale New techniques for Status Quo Choose Your Own Adventure Listen At Scale Leverage machine learning to sharpen insight quality Decision Optimization provides dynamic outlooks into success Understand: what is said, what matters, what doesn’t Copyright © 2015 Bentz Whaley Flessner 26
Listen at Scale Because people communicate with words, not numbers, it has become critical to be able to mine text for its meaning and to sort, analyze, and understand it in the same way that data has been tamed. In fact, the two basic types of information complement each other, with data supplying the “what” and text supplying the “why”. Source IDC: “Text Analytics: Software’s Missing Piece? ” Copyright © 2016 2015 Bentz Whaley Flessner 27
Listen at scale § Natural language processing heuristic rules and statistical techniques to reveal conceptual meaning in text § Extracts concepts from text and categorizes them § Makes unstructured qualitative data more quantifiable, enabling the discovery of key insights from sources such as: -Visit documentation -Survey responses -Call center Notes -Social Media -Web Pages Bentz Whaley Flessner Copyright © 2016 2015 Bentz Whaley Flessner 28
Wrap up Copyright © 2015 Bentz Whaley Flessner 29
So where do we head from here? Start from the “goal up” § Let the outcome set your agenda § What do you want learn? § How will it be used? Look within our organizations § Focus analytics on internal processes § Support strategic business decisions with statistical outcomes Embrace new approaches, where they fit § Have an open mind to the “latest § Be mindful how it fits within your analytics maturity, and of course outcomes Copyright © 2016 2015 Bentz Whaley Flessner 30
Discussion Copyright © 2016 2015 Bentz Whaley Flessner 31
Copyright © 2016 2015 Bentz Whaley Flessner 32