At its core, Customer Relationship Management (CRM) seeks to maximize value from past, present and potential future customers. Requirements for most CRM programs include the ability to target individuals on a one-to-one basis and measure campaign performance via relevant metrics for the brand. The playbook consists of a multitude of programs and strategies supporting acquisition, engagement & retention with a focus on lifecycle management of the customer.
I’d like to focus on one “play” in the CRM playbook that could use some refinement for many CRM marketers, win back.
Win back consists of a brand attempting, through one or more contacts, to reactivate lost customers or customers at risk of attrition. Offers and calls to action for these types of campaigns are usually very strong, costing the brand substantial markdown dollars and occasionally brand value. The price of the campaign may be measured in successfully reactivated customers.
For most brands win back is initiated when the target customer has not engaged within a designated period of time (example: six or twelve months of no trackable activity). Whereas this approach may be effective, additional opportunity exists to enhance the program with data and advanced analytics. The reward for investing business intelligence resources into win back programs is three-fold:
- Eliminate False Customers. Isolated transactions associated with gift purchases or program enrollment without engagement (no opens / clicks) are likely not customers requiring win back as they have never engaged with the brand in a meaningful way.
- Eliminate Highly Promotional / Low Frequency Customers. If the customer only shops when they’re being reactivated or responding to negative net margin offers it may be worth evaluating them for win back. These types of customers are often the driving force behind eroding top line sales, margin rate and equity for the brand. It may be best to part ways with these customers and reserve marketing dollars for higher value targets.
- Eliminate Engaged Customers. Sort of a misnomer given the nature of the program but there may likely be valuable, low frequency seasonal customers that are mistaken for inactive. A churn analysis assessing frequency and spend should be incorporated prior to engaging customers that may just be out of their usual buying cycle.
Now that we’ve discussed which customers to eliminate, we may begin to address techniques to identify which customers to include in program outreach. These techniques include:
- Churn Analysis. Look beyond general inactivity to better understand customer engagement patterns. This includes analyzing recency of last brand engagement, average frequency (number of visits) and spend over time for each customer. Attrition may be confused for seasonality and/or consolidated spend. Failure to accurately identify churn will result in an unproductive marketing investment.
- Third Party Life Events / Triggers. Look for relevant times within the customers’ lifecycle to re-engage. This is actually something that is effective with active customers as well as inactive. Monitor your CRM for life events with a program like DataWatch™ or similar to identify moments when the customer is more prone to engage with your brand vs competition.
- Predictive Analytics. Leverage first party transactional data & third-party demographic and psychographic data to optimize your win back efforts. Through machine learning, understanding which customers are more likely to re-engage, spend and return on investment may be maximized. Once the model has been built, determine which business rules should be applied to your universe of inactive customers (duration of inactivity, etc.) and optimize your targeting strategy and spend accordingly.
Through the investment of business intelligence resources and the optimizations outlined above, proactive and profitable re-engagement of lost customers without erosion of brand value is right around the corner.