What analytic techniques are you using to make data-driven product recommendations this holiday season? I just published this post on FPGrowth, or frequent pattern growth, on the Learn Aster blog. This is a technique retailers use to identify multi-item associations. Think, if I purchase Item A, then I may be most likely to purchase Item C. But if I purchase Items A and B, then I may have a higher likelihood of purchasing Item D. FPGrowth allows you to look at different basket sizes to identify these patterns.
We are increasingly seeing retailers use FPGrowth in Aster-based next-best-offers with great success, so we've incorporated this technique into our Product Recommender solution. I wanted to make sure I shared the post here. Feel free to email me at firstname.lastname@example.org if you'd like to learn more.