MADISON, Wis. (10/3/13)--More organizations across industries are using predictive analytics to determine consumer behavior and improve their success. Despite not having large analytic staffs, credit unions could benefit from using existing predictive analytics technologies to bolster their business and better serve members, a senior TruStage executive told an Online Discovery audience Tuesday.
The online conference was sponsored by CUNA Mutual Group. TruStage is CUNA Mutual Group's direct-to-consumer brand for insurance and investment products.
Simon Gao, vice president, TruStage consumer analytics, defined predictive analytics as a set of business intelligence technologies that uncover relationships and patterns within large volumes of data to predict future behavior and events.
"Do you ever wonder how Netflix has such great movie recommendations for you or how Target sends you just the right coupons? The answer is these companies, like many others, are predicting your behavior," Gao said.
Predictive analytics is forward-looking, using past events to anticipate the future. Existing data are modeled to help business leaders make decisions more accurately, objectively and economically. Although credit unions could potentially gather a plethora of member information, Gao suggested the following information might be useful for credit unions to initially collect and model:
Predictive analytics could help credit unions with marketing and risk management in particular, Gao said. "In marketing acquisition, targeted programs are still the best way to go," he added. "If your credit union is not doing individualized targeted marketing, you should investigate this approach."
Predictive analytics can help credit unions create targeted cross-sell and up-sell offers. "It helps identify the most effective contact strategy to reach members, and which products and services to offer to more effectively grow and retain members," Gao said.
The CUNA Mutual Group MemberCONNECT Program uses predictive analytics in the direct marketing of TruStage insurance to identify the best consumers to target. Factors built into its modeling include propensity to respond, likelihood of conversion, persistence and lifestyle factors. "We test various models to identify what message or combination of messages is the best for a particular segment of consumers, so the creative tests would identify winning approaches with the biggest impacts," Gao said.
Consumers also benefit from predictive analytics through the receipt of more relevant and targeted offers, better products and services, and cheaper prices through greater marketing efficiency.
Credit unions don't need large staffs to take advantage of existing predictive analytics technologies. "You may not be able to do the modeling in-house, but you can purchase vendor products, similar to those you use with FICO credit scores in loan underwriting," Gao said.
Most companies start by leveraging their existing analytics staff, who have the best knowledge of existing databases. Many predictive analytics consulting companies that can assist credit unions in getting set up.
Predictive analytics is not a fad, Gao said. "Organizations are already struggling with too much data. Predictive analytics is the most powerful solution to the 'too much data' problem, and it has proven to have an outstanding return on investment," he added.
Online Discovery is an annual virtual conference sponsored by CUNA Mutual Group that attracts a national and international credit union audience of more than 1,300.