As customer loyalty management continues to mature, loyalty gurus across industries continue to refine strategies to deliver increased relevance to their customers. This includes retailers, financial services, travel & entertainment and subscription services. Each industry shares the goal of winning customer loyalty for their brand. The execution of their loyalty efforts may vary but the objectives have much in common including:
- Creating top-of-mind customer connection with the brand
- Increasing customer share of wallet
- Developing more top-tier customers
- Reducing attrition and defection rates
- Improving loyalty program and campaign ROI
Loyalty practitioners are increasingly focused on evolving strategies to smaller segments of customers. Each customer can be treated uniquely by deploying the right mix of motivators by focusing on relevant indicators such as delivery channel, offer content, merchandise and timing. The most successful loyalty programs leverage technology, analytics, data and strategy to drive increased customer loyalty. The core of this process is the customer marketing database which drives these efforts by maintaining transactional, survey, attribute, custom metric and Web data to deliver more relevant offers and rewards.
Building a comprehensive customer loyalty program may require substantial lead time, but most database marketers can leverage their marketing database quickly to jumpstart the process. Developing custom metrics contributes to early wins.
These metrics are data fields derived from elements residing in your marketing database. This data is very attractive because they add significant meaning and value and can be deployed at low cost using existing resources. Examples of the most impactful custom metrics include:
- Discount sensitivity score – relative price sensitivity of a customer
- Profitability index – margin basis of product sales mix
- Promotional response score – type of promotion the customer prefers
- Cadence quotient – timing of transactions
For example, a profitability index computed for each customer reveals “truths” that are masked by conventional frequency and recency indicators and provide a guide for maximizing campaign and program ROI.
These custom metrics are calculated from more discrete variables in the marketing database for use in our loyalty marketing efforts. It is the utility of the metric in your loyalty efforts rather than the complexity which makes them so powerful. In this way, custom metrics can be an important contributor in building and maintaining loyalty and effective customer migration management programs.
Paul Weiss is an Epsilon VP in its strategic and analytic consulting group
