The Oracle Data Cloud blog highlights the latest data-driven insights and trends in digital marketing and ad tech.

How to re-engage lapsed customers with data-driven personalization

Tara Dezao
Director of Content and Creative Services, Oracle Data Cloud

Lapsed customers aren’t a new problem and brands have been devising win-back strategies since the early days of consumerism.

However, brands didn’t always have the insights or tools necessary to re-engage lapsed or lapsing customers.

Lapsed customers demonstrated a need for your product in the past, which means that they are likely a better place to put your resources than brand new prospects who have yet to reveal that need.

Also, they are already familiar with your brand, eliminating the potential of wasted dollars on brand awareness campaigns

Since the advent of CRM tools many have leveraged email hygiene or open/click information on existing customers, but lacked insights into their other engagement and purchase behaviors—which we know provides valuable context for delivering the right message to the right customer at the right time.

With third-party data, marketers now have the insights at their fingertips to create highly targeted and personalized win-back campaigns that speak directly to their lapsed customers. 

Using your own onboarded first-party data, layer on various third-party data types containing attributes such as age, gender, past purchase and interest variables to create personalized, versioned digital content that truly speaks to these lapsed customers.  

Here are some of the data types to utilize:

  • Demographic. Social and economic information about populations including age, gender, income, education, type of residence, etc.
  • Geographic. Insights in relation to the location and attributes of a designated area, which may consist of size, physical characteristics, population and other metrics.
  • Behavioral. Observable actions and patterns of a particular individual or group in response to stimulation or stimuli.
  • Purchase-based. Decision making influenced by the presence of previous transaction data. Past-purchase behavior is often an indicator of future buying decisions.
  • Psychographic. An aggregation of values, interests and lifestyle information to create a profile for an individual or group with similar traits and beliefs, determined through survey response or previously observed behavior.

In this case, you know they haven’t shopped with you lately, so combine that with other signals about their behavior to craft something truly tailored to this segment.

A partnership among the data, media and creative agencies is the key when trying to version content. Lapsed customers may fall into multiple interest and purchase categories, but it’s unnecessary or unadvisable to create a thousand different pieces of creative for a single campaign. It’s critical though to understand the main differences between audiences to increase relevance and drive conversion.

Here’s an example of the success you can achieve by adding personalization techniques to existing customer data: HauteLook, a Nordstrom company, leveraged custom scoring on their member file to personalize messaging and version creative offers. This effort drove 2x increase in opens, a 340 percent higher purchase rate and 14x higher revenue per-member rate.

This is just one of example of multiple data-driven strategies that marketers can use to re-engage lapsed customers. To learn more about using data to connect with inactive customers contact The Data Hotline today. 

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Image: Shutterstock


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