Win Back Lapsing Customers

A win-back campaign uses a series of personalized email messages that are sent to customers who have stopped engaging with your brand to attempt to get them to re-engage with your brand.

An email-based win-back campaign should be built around a series of personalized messages that are designed to encourage your customers to re-engage with your brand before they become lost customers.

A win-back campaign for lapsing customers will typically include:

  • Incentives and offers, such as a percentage discount or a promotion code

  • Product announcements and updates, such as a preview sale for new items

  • Other types of messaging, such as product suggestions that are based on previous purchases

Lapsing customers are not lost. They recently engaged with your brand and they often require a tailored series of personalized messages that are different from lost or active customers.

Track the win-back percentage for your win-back campaigns!

A win-back percentage represents the percentage of customers who were inactive, but returned and made a purchase within the measurement window.

The following sections describe using the Segment Editor to build a segment that returns a list of customers who have contactable email addresses and whose most recent order was at least 1 years ago, but less than 2 years ago.

USE EMAIL TO WIN BACK LAPSING CUSTOMERS

Open the Segment Editor.

Open the Segment Editor, look in the lower-right of the page and make sure your customer 360 database is selected.

Use your customer 360 database to build segments.
Return a list of customers for whom your brand has phone numbers.

To identify customers for whom your brand has complete and contactable email addresses in their customer profiles. Choose the Contactable Email attribute from the Customer Attributes table, and then select the “is true” operator:

Find customers for whom your brand has email addresses.

Click the Refresh button located on the right side of the Segment Editor to see how many customers are in your segment, how much they spent in the past year, how many are active, and how many of them should belong to a future campaign.
Find customers whose last purchase was over 2 years ago.

The first step is to identify customers whose most recent order was at least 1 year ago. Choose the Days Since Latest Order attribute from the Transaction Attributes Extended table, select the “is greater than or equal to” operator, and then configure the dates to be “365”:

Find customers whose last purchase was more than 1 year ago.

Click the Refresh button located on the right side of the Segment Editor to view updated values for the combination of customers who have a contactable email address and have made a purchase in the last 365 days.

Tip

You can also use the Historical Purchaser Lifecycle Status attribute in the Customer Attributes table to identify lapsed customers. Set the operator to “is in list”, and then choose “Lapsed”:

Find customers whose last purchase was over 1 year ago.
Find customers whose last purchase in the las two years.

The next step is to add a second attribute to your segment.

To identify customers whose most recent order was at least 1 year ago. Choose the Days Since Latest Order attribute from the Transaction Attributes Extended table, select the “is greater than or equal to” operator, and then configure the dates to be “732”:

Find customers whose last purchase was more than 1 year ago, but less than two years ago.

Keep the and/or slider set to AND.

Click the Refresh button located on the right side of the Segment Editor to refresh segment insights to view updated values for the combination of customers who have have a contactable email address, and have made a purchase in the last year or more, and have made a purchase in the last two years or more.

What about predicted customer lifetime value?

Tenants with Amperity predictive modeling can use predicted customer lifetime value (CLV) instead of the combination of Days Since Latest Order attributes. Choose the Predicted Customer Lifecycle Status attribute from the Predicted CLV Attributes table, set the operator to “is in list”, and then choose “Lost”:

Find customers whose predicted CLV is "Lost".
Send customer list to favorite email destination.

The last step is to configure Amperity to send these audiences downstream to the marketing application from which you manage your email campaigns. For example, Attentive.
Save your segment.

You’re done! Click the Save As button in the top right corner of the Segment Editor. Give your segment a name that clearly describes the purpose and audience type for the segment. For example: “Win-back: Lapsed Customers”.

Give your segment a name.

Tip

Use good naming patterns to ensure that you can always find your segments when you need them. Be sure to include the brand name and/or the region name if you have multiple brands or have multiple regions and want to build segments that are brand- and/or region-specific.
Segment insights page

After your segment is saved the Segment Overview page opens and shows additional details, such as historical and predicted revenue, the percentage of customers that are reachable by email, by phone, on Facebook, and customer trends, such as purchases by channel, revenue by lifetime spend.