We believe that anyone can learn to do predictive marketing with the right foundation. In our series, “Core Concepts of Predictive Marketing”, Acquia’s Chief Science Officer, Omer Artun shares excerpts from his book: “Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data.”
This series will be a guide to everything you need to know about relationship marketing and predictive analytics in marketing. Dive in to learn how to activate your customer data and tap into unlimited opportunity.
When a customer leaves you, not all is lost. Our data shows that it is on average 10 times cheaper to reactivate a lapsed customer than it is to acquire a new one. Reactivation programs for lapsed customers therefore are low-hanging fruit for marketers looking for new revenue streams.
Reactivation campaigns are for customers who have not purchased anything for an extended period of time. Typically, a customer is considered lapsed or lost after she has not spent money with you for twelve months. For subscription services, you can consider a customer lapsed or lost as soon as they let their subscription expire — whether after one month or three years. Lapsed customers can frequently be reactivated with the right offer or product recommendation. Since these customers have essentially been written off and are not expected to make any additional purchases, the most successful reactivation offers are typically fairly generous — such as a significant discount on a next purchase.
One company we work with noticed it had a large number of customers who once loved the brand but hadn’t engaged with the company for a while. It wanted to focus on customer loyalty and engagement by bringing enthusiastic customers back to the brand. The company used its knowledge of the type of products its customers enjoy to send smart product recommendations. These campaigns resulted in an eightfold increase in monthly revenue.
Reactivating customers builds on the investments you have already made and avoids the costs of trying to get new customers. These original customers are already aware of your brand and are more receptive so reengaging them can lead to gaining significant incremental revenue.
In many measurements we made, most reactivated customers behave like new customers, that is, they almost restart their lifecycle. This also means that the early periods after reactivation are when customers are most vulnerable to lapse again and require special attention.
Reactivation campaigns in four steps
So where do you start with reactivation? First, determine which customers you want to reactivate. Then determine the most receptive candidates, customize your message to this group and re-engage these customers using different channels.
- Determine which customers you want to reactivate.
Not all past customers may be worth bringing back. Marketers need to carefully determine which customers were profitable, interested in products they want to sell/grow and other strategic factors. For example, you may want to exclude customers who returned more than 5 percent or had more than 30 percent discounting on their previous orders.
- Determine the most receptive candidates.
You may only want to approach past clients who are most likely or ready to respond — especially if your reactivation campaign is expensive such as in the case of direct mail or targeted display advertising. Even if you are using email, you probably don’t want to send marketing messages to customers who are not ready — otherwise, you risk seeming overenthusiastic and driving customers away.
- Re-engage customers using different channels.
The shopping journey spans across many distribution channels. There is no reason your marketing message should not be omnichannel as well. After customizing a message using your customer’s past data, try to reach customers at as many points as possible. A greater number of contacts usually correlate to a higher response rate. So don’t forget to send that email, postcard or app notification with personalized offers.
- Customize marketing message using past data
Now that you know which lapsed customers are ready to respond, take a look at their purchase history. What have they responded to in the past? What type of products do they buy? What kind of brands do they like? Craft your messages according to their tastes and needs. By looking at past trends, you may be able to figure out why the customer lapsed and use this as an opportunity to address this reason. Perhaps the customer may give you a second chance.
To see other ways that marketers can use machine learning and predictive marketing to improve customer relationships, see the other instalments in our Core Concepts of Predictive Marketing series.