Fall 2019 - Inside Outdoor Magazine

Tech Savvy Inside Outdoor | FALL 2019 51 at past stimulus presented to custom- ers, as well as the response generated (converted or not) to predict the likelihood of a certain approach to get positive re- sponse. And “attrition rate” (or churn anal- ysis) provides a look at the percentage of customers lost during a certain period of time, as well as the opportunity cost/po- tential revenue lost with their departure. With the deliberate use of these predictive analytics tools (and oth- ers), a business can then predict the customer lifetime value (CLV). This measurement looks at several aspects of historical behavior to identify the most profitable customers over time, acquisition spending trends around which activities generate the best ROI and types of customers that are loyal (retention traits). This model then adds an estimate of expected retention to the equation as a means of estimating future value. Once you understand the CLV, you can right-size the cost of ac- quisition and your marketing budget to reach the desired ROI. One last note: When applying pre- dictive analytics, it’s critical to A/B test your approaches to inform your out- put. Known as “casual inference,” A/B testing of the same target audience allows us to infer the why behind the what customers are doing. With these steps and measurements in place, you have earned your role as fortune teller – overseeing a true “pre- dictive analytics organization.” This is a tight ship, where marketing, sales, op- erations and finance work hand in hand, constantly providing feedback into the “data-outcome-analysis” loop.  Finally, the future of predictive ana- lytics rests on ethics – yes, ethics. In- stead of “sneaking into” peoples’ tech- nology to follow their behaviors and disrupt their buying pattern to increase market share, the future of predictive analytics is to engage consumers, so they willingly share their prefer- ences. That is what led Nike to acquire Boston-based AI platform company Celect. By embedding predictive al- gorithms in its own website and apps, Nike will be able to better predict which models are getting traction, where consumers want to buy them and when shopper are likely to buy.   Remember, it all starts with the clear articulation of the business strat- egy.  With all parties in alignment, the chips should fall in place: Predictive modeling of customer behavior helps educate campaigns to drive loyalty or generate leads. Lead qualification modeling helps the sales team focus on the most prob- able customers to buy/close the deals. And both of these together help finance understand the CLV and edu- cate the whole organization on the ac- ceptable customer acquisition cost to drive the targeted ROI.  If you’re not predicting, you’re los- ing ground. m Adriana Lynch is CMO with Chief Outsiders, a CMO firm focused on mid- size company growth.