Amazon. Google. Netflix. We know these brands as the head honchos of data management and data analytics. In many ways, they’ve written the handbook for a game in which both the rules and the playing field change in the blink of an eye. If keeping up with that rapid evolution is can seem daunting, the good news is that data collection and analytics continues to become more accessible in a way that credit unions can utilize and maximize.
It goes without saying that credit unions want to keep their members, and keep them happy. As credit unions look to enhance offerings, ensure superior member service and stay competitive, alleviating member attrition is at the top of the priority list.
Good business relies on smart strategy, across industries and from top to bottom in organizations. Looking to increase employee engagement? Start with strategy. Working toward growth goals? Start with strategy. Trying to figure out how to use the ever-increasing amount of data available about credit unions and credit union members? Right again. Strategy. Without a solid data analytics strategy guiding the way, even the most compelling data can amount to nothing more than a missed opportunity.
A tool for getting to know your members on a deeper level. A window of insight into how those members make decisions. A predictor for potential member behaviors and actions. Predictive analytics can be all these things and more for credit unions today, ultimately delivering the information needed to best serve members and to make the best business decisions.
There used to be a standard protocol for connecting with consumers: conduct market research, use it to make educated guesses about what consumers want, build a campaign that reaches them and tells them you have what you think they want. It worked to varying degrees for a long time to convince people to buy Coca-Cola or remain loyal to their Toyota. But, reflecting back, that “educated guess” was in some ways nothing more than an “educated gamble.”