Facebook Ads and Instagram Ads make it easy to reach lots of potential customers, but how do you target those who are more likely to make big purchases over time?
One way to do this is to create lookalike audiences based on spending behavior. These audiences allow brands to reach their ideal buyer personas automatically, including the types of potential customers you might not reach with email marketing or other channels. Lookalike audiences are a proven route to growth for e-commerce brands, as they allow you to expand your audience while maintaining high ROAS.
This recipe will help you avoid building audiences manually, which is time-consuming and often inaccurate, as “likes” and interests are not a great predictor of spending behavior. Instead, we will show you how to continuously target a similar audience to your highest-spending customers -- the types of customers who have proven to be loyal to your brand and more likely to maintain a higher AOV (average order value).
We’ll show you how to build a group of customers in Personas filtered by `customerLifetimeValue` and sync this as a custom audience with Facebook. We will focus on Shopify stores but you can apply the same principle to any e-commerce site, as long as you can capture customer lifetime value as a custom trait.
For this recipe we need to capture the lifetime value of the customer; the sum of all the customer’s orders, less any refunds or cancellations.
Every time a customer purchases on your Shopify store, the Shopify source sends an Identify event to Segment. One of the customer traits sent with that event is `customerLifetimeValue`, which is the customer’s lifetime value on Shopify. This is not only the sum of the orders sent since you connected Segment, but the total orders they have made on your Shopify store over time.
Littledata’s Shopify source captures this value automatically -- no further setup is needed.