Sep 7, 2021

New: Improve Your Marketing With Customer Lifetime Value And Repeat Purchase Recommendations

Apteo's new customer lifetime value metrics and repeat purchase recommendations help ecommerce companies grow sales and improve marketing.

Shanif Dhanani

If you run an ecommerce store that sells consumer goods, consumable products, or any other type of product that can be purchased multiple times, chances are a good amount of your sales comes from repeat purchasers. You're likely seeing a small group of customers who are driving a big portion of your sales, and you probably want to get as many customers like them as you can. Since retaining an existing customer is cheaper than acquiring a new one, it makes sense to focus on getting someone who has already purchased from you before to make another purchase. But it's not always easy to know who your best customers are going to be, especially if they've only made one or two purchases before.

Today, we're announcing two new features that can help you manage and grow repeat sales: customer lifetime value tracking and repeat purchase recommendations. The first helps you measure and predict who your highest-value customers will be over the course of their relationship with your store, and the second helps you see who's most likely to make another purchase of a product that they've already bought before.

Measuring Customer Lifetime Value

Customer lifetime value (CLV)is a metric that tells you how much value a customer will bring to your store throughout the course of their relationship with you. By tracking CLV, you can hyper-target your marketing activities, investing in higher-cost ads and paid media to target high CLV customers, and using lower-cost email and similar media for low-CLV customers. Tracking CLV also allows you to measure the health of your store, and helps you better forecast financials. So while it's clear how knowing the CLV of a customer or group of customers can be helpful, it's not always clear how to calculate it. CLV not only takes into account historical spend, it also factors in future spend. While it's easy to see what a customer has done before, it's not always easy to know what they'll do in the future. But predicting future behavior is exactly what Apteo specializes in.

Using the data that you integrate with Apteo, we're able to train a custom A.I. model to learn how your customers behave and what they'll do in the future, which allows us to predict their future spend, even after just a single purchase. By combining these predictions with their historical spend, we're able to develop an estimate of the total value they'll bring to your store. Once we have the CLV of each of your individual customers, we can then provide a breakdown of average CLV across your store and across each customer segment, allowing you to get as detailed as you like when it comes to creating marketing campaigns based on the potential value of a customer. As your customers continue to make purchases and interact with your store, our A.I. gets smarter and continues to learn, allowing it to improve its predictions, giving you a continuously updated view of your customers' potential.

When you sign up for an account at Apteo, you'll now see your CLV on your Overview page, as well as within the Segments page, and it will be available for you to create new segments from.

Predicting Repeat Purchases

Customers that have bought from you multiple times are more likely to buy from you again. One study showed that after a single purchase, a customer has a 27% chance of returning to your store, but if you can get that customer to make a second or third purchase, that probability jumps above 54%. While it may seem obvious, incentivizing customers to make a repeat purchase is one of the best ways to grow sales. But like most everything else, that's a lot easier said than done.

Getting customers to subscribe to a product is a great way to get them to come back, but even stores that have a subscription tier find it hard to get customers to commit to buying a product repeatedly. That doesn't mean that customers don't want to buy a product a second (or third, or fourth...) time, it just means that customers are wary of signing up for something over the long run. It's not easy to know which customers are likely to come back and buy again, and which are likely to go dormant, but with Apteo, you can now start to estimate who's who.

Our new repeat purchase recommendations feature identifies customers that are likely to make another purchase (and which product they're likely to buy again) and surfaces that information to you so you can intelligently target customers with the right message at the right time. Just like how we predict CLV, we use A.I. and all the data we have about your customers, their behavior, trends in your store, your products, and we use it all to forecast what your customers will buy next. Once you have this information, you can even combine it with data about your customer's lifetime value to identify the highest-potential customers and the products they'll buy and target them with ads and messages that will inspire them to come back and buy your products.

Repeat purchases will be available on our new "Recommendations" page, which also provides recommendations about which customers are likely to buy another, different product, based on what they've purchased in the past.

Making Better Use Of Your Data

Predicting CLV and repeat purchases are just two ways that we help you use your data to grow sales and repeat purchases for your store. If you're already using Apteo, you'll see these two new features in your account when you log in. If you'd like to learn more about how we help ecommerce companies use data to improve their marketing, feel free to chat with us on our site or book some time to learn more.

About the author
Shanif Dhanani
Co-Founder and CEO, Apteo

Shanif Dhanani is the co-founder & CEO of Apteo. Prior to Apteo, Shanif was a data scientist and software engineer at Twitter, and prior to that he was the lead engineer and head of analytics at TapCommerce, a NYC-based ad tech startup acquired by Twitter. He has a passion for all things data and analytics, loves adventure traveling, and generally loves living in New York City.