Decision Science POV 6-26-13
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Decision Science uses data mining and predictive modeling algorithms to analyze constituent data and determine who organizations should target for communications, about what topics, and when. It includes response, upsell/cross-sell, risk, attrition, and lifetime value models. Decision Science sits between an organization's constituent data and communication channels to create models that segment constituents and are appended to the database to guide outreach. Practitioners are typically statisticians with an understanding of cognitive psychology.
Decision Science POV 6-26-13
- 1. Decision Science v.1.0 Nick Metcalfe Decision Science is the process of data mining your constituent data for insights and actions that will maximize the relationship with UCLA. This statistical function includes analytics, predictive modeling algorithms and propensity models that helps you decide who to talk to, about what and when. There are 5 types of models, Response, Upsell/Cross Sell, Risk, Attrition and LTV models. The two big vendors in the space for this analytics are SAS and SPSS (IBM). Challenge – A Business Intelligence team qualified to create and manage these models, and the technology required to run them. Decision Science in a nutshell 1. So Decision Science helps us determine who is more likely to engage in our communications? • Yes. The modeling enables us to segment our constituents into target groups that have a higher likelihood of engagement. • The models can distinguish those more interested in online giving vs. planned giving vs. volunteer events vs. On The Road events vs. Alumni news etc. 2. Can’t I make the decision? Why do we need a model? • Models are more effective, efficient and statistical. Individuals can be partial and biased. The data is impartial. • Humans do not have the ability to synthesize multiple variables or perform multivariate analysis. The technology is built to do this. 3. So, where does Decision Science fit within the CRM process? • Decision Science and the supporting technology sits between your constituent data repository and your communication channels (email, direct mail etc) • The tool creates models and database scripts that are appended back into the database and can be refreshed 4. Who is qualified to be in Decision Science? • Most Decision Science practitioners are statisticians who have cognitive psychology understanding 5. Who else uses Decision Science? • Many organizations use Decision Science for business decisions and campaign management • You may be familiar with NetFlix’s movie predictor algorithm or Amazon’s collaborative filtering algorithm 11/25/2014 Nobel prize for models