Looking Past Average Numbers Can Pay Big Dividends

The following case study from Marketing Sherpa demonstrates the power of looking at segment metrics and performance vs. just looking at averages. It also demonstrates the impact of reducing churn and turning new customers into frequent customers.

SoftwarePundit had calculated customer lifetime value (CLTV) to be around $200. This figure was calculated as an average of the entire customer base. Major inputs into the calculation were average order value (AOV), order frequency, gross margin, and churn.

When they dug into their churn data, they discovered that a large number of their customers were one-time purchasers. They also discover that if a customer purchased a few times in the first few months, they basically never churned.

“Given that churn is a major input, we decided to segment and recalculate our CLTV,” said Bruce Hogan, CEO, SoftwarePundit.

They found that many of their customers had a CLTV around $20, but a significant percentage had a CLTV closer to $1,000.

Seeing this data impacted their marketing in two meaningful ways:

  1. They realized they could increase the amount of money spent on acquisition, provided the team could determine the customers weren’t one-time purchasers.
  2. They focused on converting one-time purchasers into repeat purchasers at the early stages of their lifecycles. Through A/B testing, they developed tactics that stimulated repeat purchases that increased CLTV.

For example, they sent coupons offering a 10 to 20% discount on subsequent purchases to entice customers to establish a buying pattern. This resulted in the biggest increase in repeat purchases, however, it should be noted that these people remained habitual shoppers only as long as they received the coupons.

Sending product recommendations was also effective. They identified products that were most often purchased on customers’ second and third orders. This tactic had a higher ROI than coupons, but did not have as large of an overall impact.

“It’s critical to segment CLTV. You’re better off having an accurate average CLTV than not having a trustworthy figure. However, there’s a good chance that this figure doesn’t actually describe the CLTV of any individual segment in an accurate way. By segmenting your CLTV, you can unlock more dollars for acquisition marketing, and uncover experiments that will increase CLTV,” Hogan said.

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