The comfort of data-driven decisions

As the next generation begins making financial decisions, credit unions will be able to comfort them with data-driven product recommendations.

Recently, my wife and I were shopping for a mattress. We began the process by “trying out” mattresses by how they felt. My wife thought she preferred firm mattresses, while I thought I preferred soft ones. As we tried mattress after mattress, my wife would ask me, “what do you think about this one”, in which I would usually reply, “It feels pretty good to me”. We became frustrated by a complicated search for a large budget item until we found a mattress store that comforted us with data. The mattress store (Becker Furniture World) is locally owned with only 8 locations (does this sound familiar to your credit union?). They approached mattress shopping from a data-driven way. By using an analytic data model (developed by Sleep to Live Institute), they are using analytics to aid customers in their mattress investments through data sensors and user input. The data comforted us enough that we decided to purchase one of the mattresses it recommended.

Data Acquisition from Users

When we walked into the Becker Furniture World, it was different than all the other mattress stores. There was a futuristic-looking canopy near the front of the store. Curious to see what this machine was, we asked a store associate and were informed that it collected data from our bodies and sleeping patterns to recommend the best mattresses. Before entering the contraption, we entered in personal data about ourselves using ranges for age, weight and height, along with other qualitative data including where we currently have pain and our sleeping preferences. After entering in our personal data, we both laid down on the bed (hooked up to data sensors).

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