But customer acquisition cost goes beyond cost of outreach and initial offer value. Once a customer has supposedly been “acquired” i.e. has signed up, there is a critical stage in which a customer will either become “engaged” i.e. return to make additional purchases, or… well, not return. Unlike service industries, which engage customers in long-term contracts, in retail, once a new customer has received the goods to her satisfaction, the contract is effectively concluded.
A typical example is offering customers 10 percent discount on their first purchase when signing up to a loyalty program. While such a benefit may help drive the first purchase, it doesn’t necessarily compel the customer to make a second purchase. In fact, 30-40% of new loyalty club members never return.
This is demonstrated in the following chart, tracking the average of the number of visits made by new loyalty club members of several groceries retailers during their first 8 membership weeks:
Among members who did not cancel their membership during the first 8 weeks, 5 percent visited the shop 7 times or more, 25 percent visited the shop 3-6 times, and 35 percent visited the shop 1-2 times. However, the most telling number is the one not presented at all in the bar chart (which sums to 65%) – the 35 percent who never made a purchase after their initial sign up.
Most groceries retailers agree that the first 8 weeks are critical in building relationships with customers. Many of them have identified that “loyalty” is typically achieved when the customer visits the store at least bi-weekly, i.e. at least thrice during the first eight weeks.
Aside from the missing 35 percent, our chart also shows another 35 percent of potential churners that did not reach the three-time visit loyalty milestone. We now realize that what we thought was an acquisition rate of 65 percent is more like 30 percent. This correlates well with consumer behavior reported by digital app vendors – 50-70% of people who download an app will never use it more than once.
How do we fix this?
Dating your customer
A good analogy for the first meeting between a retailer and a new loyalty member is dating.
At first, we know very little about each other. The selected venue will be something that appeals to most people’s tastes, such as a popular bar or a restaurant, in our case a general offer. During that first date, our date may share more personal information such as his or her history, passions, or values.
Unconscious sentiments like physical attraction and emotional appeal, often stronger than “objective facts”, will be forged during these initial encounters. And these factors will predict what happens next – will there be a second date?
In subsequent dates, both sides will fill in the “information gap” to help build the relationship. This new found knowledge will be entered into a more complex set of considerations such as understanding, empathy, mutual value generation, and teamwork among others.
In retail, “first dates” are just as crucial. It is during these initial dates that the retailer must pique the interest of new members and generate positive sentiment, by collecting the right information and sharing the right information, to build a long-term relationship.
Personalization is a winning strategy for long-term retailer-customer relationships, but not all personalization is created equal. Successful programs must understand the needs of new members and initiate a personal dialogue with those customers.
Tips and best practices on increasing acquisition success rates
The retailer can act on two fronts. Initially, the retailer should try to communicate the brand’s uniqueness, value, and differentiation to customers and try to tap into their emotions. A large retailer recently began sending membership confirmation e-mails with a personalized branding video that features the customer’s name in various parts, explaining how its corporate values relate to that customer. Not only that, the customer’s first three purchases were accompanied with personal outreach to identify any unfulfilled expectations. These straightforward nurturing activities decreased new members churn by as much as 50%. An amazing result on a large segment of customers!
Another Retailer interviewed new members regarding hurdles they had encountered in their first purchases and then surveyed veteran customers on how they overcame these shortcomings. The retailer then produced a series of communiques to new members regarding these hurdles and how to overcome them. These communiques showed that the retailer was listening to new members while having the sincerity to admit that “no one is perfect”. That way, even before it managed the necessary improvements, it helped new customers get the most from their membership. The retailer tested the impact of these communications against a control group that received attractive discount and rebate offers and saw that these personal care treatments were even more effective than monetary incentives. Here again, touching on the emotional aspect of early membership days created immense value in shrinking the “vanishing new members” segment.
The second front is crafting strategies that entice customers to visit stores more often and connect with them by learning more about their specific needs during each visit.
The typical marketing approach is to provide customers with attractive coupons that have broad perceived value, covering as many stores and departments as possible. Best seller coupons and high value non-specific category level coupons are typically chosen. But this action alone is not enough. Our first encounter with the customer gives us an opportunity to employ data science to do better. For example, we know what the customer has already purchased with us and probably more than one product. We can use a rewarding tactic to entice him to buy more of these products and other complementary products, while giving him substantial benefits, the same benefits that we provide our best customers. Another tactic is to combine demographic attributes with segmentations and offers that have been successful with similar customers in the past.
While using generalized coupons, it is likely that customers will pick more personally important products, and this can be very helpful in decoding the retail DNA of new members.
After a few visits the retailer will be able to fully decode the retail DNA of new members and can then consider long tail products offers to drive basket diversity and more visits.
The following chart shows a grocery chains’ progress while implementing the above tactics over a span of nine months:
The chart tracks the increase new customers visiting the shop more than 3 times during their 8 first weeks as well as the increase in the use of coupons during that period. We can see the learning curve of deploying attractive coupons – during this period the redemption by new customers increased 3.6X while attrition related to the 3+ visits milestone decreased by 18%.
The foundation of getting to know a customer lies in collecting and analyzing the data that she provides and responding to key findings in a timely manner. During the first 8 weeks, the retailer should engage members on at least a bi-weekly basis, with each message becoming more personalized than the previous. The current article is just one example of how data science automation can be applied at scale, in which the retailer analyzes the information provided by all new members during their first purchases and uses that information drive long-term engagement.
Happy and successful dating!