PREDICTIVE ANALYTICS: NO CRYSTAL BALL REQUIRED
October 13, 2017
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.”
Anyone who’s been online lately knows that the tidal wave of data pushed out by consumers and pulled in by Google, Facebook, Amazon and others has essentially created a new world order in how we do everything from ordering a sandwich to buying a car. The world of data management and dissemination is the world in which we live now, and it’s fueled by predictive analytics.
Predictive analytics are the reason Facebook knows which sponsored content you’re most likely to want to see (and eventually click on) and how Amazon knows which product suggestions to pop up. The good news for credit unions is that the power of predictive analytics is right here and right now, ready to decipher and deploy.
An article by Jim Marous in The Financial Brand highlights three primary reasons credit unions must embrace predictive analytics as a primary tool for connection, relationship building and growth:
- Consumer expectations. Predictive analytics have changed what consumers expect from brands and how they ultimately make decisions. They are becoming trained to not have to look too far or try too hard to find what they want. If credit unions can’t keep up with these expectations, members have someone waiting in the wings who will: the banking industry invested nearly $17 billion in predictive analytics last year1, a number that is expected to grow to $22.1 billion within the next three years2.
- The all-important mobile device. How many Uber trips have members taken in the past year? Have they texted donations with the touch of a button? Where and when do they work out? Like it or not, mobile devices log and track all these actions and behaviors. All these actions and behaviors add up to insights which can be distributed in real-time to help credit unions meet members where they already are.
- Data accessibility. Gone are the days of big data being difficult to collect and even harder to store. The abundance of data collected and the ability to store it at a much lower cost than in the past make key insights and information widely available. It’s there for the taking, and companies that don’t leverage it will soon find themselves at a significant competitive disadvantage.
Predictive analytics have allowed businesses to shift from educated gambles to statistically proven successes across basically every industry. Read our whitepaper, Predictive Analytics for Credit Unions and learn more about how credit unions can harness the power of predictive analytics to drive member engagement and transform their business.
1. “6 Predictions for the $203 Billion Big Data Analytics Market” Gil Press. Jan 20, 2017. https://www.forbes.com/sites/gilpress/2017/01/20/6-predictions-for-the-203-billion-big-data-analytics-market/#6957656f2083
2 “Big Data and Analytics Spending to Hit $187 Billion” Thor Olavsrud. May 24, 2016. http://www.cio.com/article/3074238/analytics/big-data-and-analytics-spending-to-hit-187-billion.html