Product Recommendations Overview

Apteo's goal is to help you automate your marketing using data and insights. We want to make it as easy as possible to identify opportunities where you can sell more to your customers, and one of the ways we do that is through our Product Recommendations feature.

By analyzing what your customers' behavior, including what products they buy together and how often they buy purchases, we're able to identify trends and patterns that you can take advantage of to sell more to your customers.

Specifically, we provide cross-sale and repeat-purchase recommendations that help you understand which of your customers are likely to buy which products and when.

Cross-sale recommendations

By analyzing your site's data, we can find products that tend to be purchased together. When a customer buys a product that is usually frequently bought with another product (but doesn't buy that other product), this presents an opportunity to send a marketing message to that customer to sell them the product they didn't buy.

Apteo refers to this as a cross-sale recommendation. The idea is that if someone purchased Product A, and Product A is usually bought with Product B, then that customer may also like Product B.

How do we identify products that are bought together?

For the data enthusiasts out there, we use a few A.I. algorithms that are designed to identify which products are bought together more often than expected by random chance. They are designed to identify a product (or group of products) that occur relatively more often with a primary product than they would if that primary product wasn't also purchased.

Repeat-Purchase Recommendations

In addition to identifying which new products a customer may purchase, we also identify which products that a user is likely to buy again. We refer to these as repeat-purchase recommendations.

By analyzing a variety of data, including every customer's purchase frequency, spend, and product preferences, we're able to make a prediction about which of your customers are likely to buy which products again. We'll then surface any customers that are likely to make a repeat purchase again within the next 30 days.

How do we identify products that are bought together?

Any time someone buys a product, we take a snapshot of everything we know about that customer at that point in time - how often they purchase, how many times they've purchased that specific product, even things like their zip code and state - and we use all this data across all your customers to train an A.I. algorithm to predict how many days it will take before that customer makes another purchase.

The algorithm will then be able to identify patterns across all customers in your store and predict which of them are likely to buy another product, and how long it will be before they do.

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