![]() It gives the salesmen a ranking of which customers are their biggest opportunity on that day, and they just go down that list and call them. And then it scores the opportunity with that customer, based on how much money they spend with us. Each one is designed to do a customer recommendation, where it determines which customers should be ready to buy today, based on the recency of their last purchase, how frequently they purchase. We have separate models for our US call center and our UK call center. We're running batch, overnight, and I believe we have three machine-learning models in production at the moment. ![]() ![]() In a recent sample that I pulled, it successfully predicted two-thirds of our sales in a given week. The primary use case is to augment our sales processes, to help our call center determine which customers to call, which products to push to those customers.
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