The Next Level of Personalized Shopping

The following is a post written by Erik Severinghaus, Founder & CEO over at KoalaDeal. KoalaDeal integrated with Rapleaf and has been using our data to build analysis and correlations associated with online shopping habits. Check out what they have been up to:

A few weeks ago, Rapleaf was kind enough to invite KoalaDeal to blog about some of the trends we were beginning to see with personalizing online shopping. Since then, we decided to go deeper with Rapleaf’s data, analyzing the thousands of customers in the KoalaDeal platform to start to see what conclusions we could draw. Needless to say, there are some very interesting nuggets of information within the data.

The first thing we wanted to look at was categorization breakdown for different genders. The oft-quoted example is that of men being tired of getting deals for spas and we were interested in seeing how that held up. The following is a prioritized list of categories for shopping behaviors, by gender, based on purchases, “likes”, and expressed interest:

Then we took breakdowns of three different income brackets to see what would come out of it. Here is what we found, again in order of interest

We kept going and found some very interesting incidental correlations as well. Believe it or not, for our sample size, the top category for the state of Minnesota (“the land of 1000 lakes”) was actually lakes & boating. For England, it was soccer (not surprising) and for users identified as executives, the top two categories were watches and jewelry.

We found that by simply using Rapleaf data, we can provide a personalized user experience before we learn anything about our customer – and then gather additional data to further refine those models. What surprised you most about the data?

Needless to say – a huge win for KoalaDeal and an awesome example of the power of personalization in action.

Thanks to Erik for his insight! Stay tuned for more to come with the partnership.