How to fix limitations of customer life stage groups
Customer life stage is a standard of segmentation. Customer stages like “new,” “active,” “lapsed,” and “lost” serve an important purpose by grouping customers into homogeneous, manageable clusters for marketing, value measurement, and investment decision-making. However, these definitions have limitations that you should consider and correct prior to sales applications.
Here are key limitations and how to overcome them.
Measurement windows are too broad
Most of these segments have a 6- or 12-month horizon for comparison. A “new” customer stays in that segment for 6 months, often regardless of spend or activity, whether based on total spend or number of orders. Similarly, a “lost” customer is usually defined as any spend in the past 13–24 months, but zero spend over the past 12 months. As you can see both the time and revenue windows are very large, and that dilutes usefulness. Regarding time, this can be a few weeks or up to 24 months, and regarding revenue, the measure can be a few hundred dollars to several thousand.
Corrections: Create smaller segments for sales applications with sub-definitions. These can be arbitrary to follow a business threshold (i.e., 6 months or $2,000) or they can segment eligible customers into equal percentages, like 50-50 or 33-33-33 percent.
Another option is to create “run-rates” based on a larger window, but track smaller increments. For example, if “lost” customers are tracking 30% over 12 months, use a rolling 3-month window and 7.5% as the expected rate for this time window. Over time, you will arrive at a number that works for you.
Lack of interactivity
Once you have defined customer segments, customers are targeted for campaigns based on the static view. However, from a sales perspective, many factors influence customers’ migration from one segment to another. The quality of the rep (overall experience including with company, performance level), quality and quantity of the interaction, and tenure of the rep with the customer are all critical to influencing customer behavior.
Plus social media plays an increasing role in gauging customer sentiment. Social media gives many options for an alert sales force to listen and reach out proactively to customer needs.
Corrections: Allow for scoring within each segment based on interactions, and then have reps follow-up with customers. In the catalog world, it has long been known that product returns are actually a top predictor of repeat purchase. That hardly deserves a sales call, but for an early-stage customer this could be a significant differentiator to accelerate them into an active buying cycle.
Also by creating sub-segments, sales reps can initiate conversation with smaller changes in customer behavior, which leads to a more timely conversation.
Bias towards past or present value
All these segment definitions are based on what is already known about customers, not what is expected. With new customers, attempting to estimate their next 6- or 12-month value will be very helpful so you can take immediate actions rather than wait for customers to “prove themselves.” A placebo effect might create a self-fulfilling prophecy and grow value among new customers, but this is not likely to be the norm.
In the case of lapsed customers, the reverse is true. The emphasis is on the current value and less emphasis (or none!) on where the customers were 12-24 months ago. Thus customers who peaked much higher tend to get treated similar to customers who may not have such potential or share of wallet.
By looking at the past – or a single point – of value, trends also can be missed.
Corrections: Create future value measure for each outcome. Identify early stage customer trends to track and nurture new customers. When looking at retention, add “weights” for peak spend to give former high-value customers more priority.
Using two points of customer value allows you to capture trending info, and this is another way to differentiate among customers with an eye towards future value.
Set up a method you’re comfortable with that produces a future value. This can be simple up/down metric or a more elaborate statistical model. Within each life cycle segment, make a two- or three-way split of customers based on estimated future value. Have sales reps suggest and contribute additional metrics tied to their performance. For example, deeper category penetration as a goal with the early-stage customers.
In closing, for customer segmentation to bring better ROI for sales, three elements must be in place:
- Actionability should be tactically focused with short windows
- Have a future value orientation
- Ensure that reps take responsibility for their customer interactions. Getting sale reps’ input, recognizing their workload/behaviors, and providing a long-term perspective can enhance the value of segmentation for the benefit of sales.