A growing number of specialty retailers are understanding the value of using data to improve customer segmentation. The goal is to create better targeted marketing programs via email, direct mail and SMS. Gathering and analyzing customer data is helping them build more detailed segments and become more strategic with the offers they choose to send to customers.
Customer segmentation is the practice of dividing a customer base into homogeneous groups that have similar traits, needs and behaviors. This allows companies to optimize their product offerings, marketing and sales strategies to meet the specific requirements of the segments better and more cost efficiently. This can be done based on demographics, the lifecycle of the customers, or on their behavioral attributes.
Historically, these programs have often been more heuristic or ad hoc in nature, and have failed to take into account the totality of a customer’s behavior. But as e-commerce has made new data sources available, segmentation efforts have taken those into account and have become more holistic. They are also building in other factors such as coupon usage habits, average shopping cart size and shopping frequency.
Here’s a look at how the key tactics specialty retailers can put in place.
Set Goals and Gather Data
One specialty retail chain we worked with recently decided to modernize and build up its analytics capabilities around three focus areas: its loyalty rewards program, its direct mailer targeting and its customer segments.
With the loyalty program, as is often typical of such programs, the primary objective was to collect more data about the shoppers and use that for future marketing efforts. For direct mail, the goal was to find a way to increase incremental sales and improve targeting strategies. The goal for customer segments was to better understand customers across various dimensions and to identify the preferences and traits of each segment and then adjust marketing efforts accordingly.
Sort the Groups
The five segments for this retailer included: coupon-savvy, sporadic buyers, profitables, big baskets and MVP customers. The sporadic buyers and the coupon-savvy were among the least profitable, with both groups making few transactions, shopping just a couple times per year. The coupon-savvy group exclusively bought with coupons, while the sporadic buyers were coupon-insensitive yet still didn’t spend very much.
The “big baskets,” on the other hand, tended to buy a considerable amount when they shopped, while the “profitables” would buy more expensive merchandise—both groups are also insensitive to coupons. Finally, the MVPs spent the most and shopped the most often.
A look at the coupon-savvy segment revealed that the average customer in this group shopped around twice a year and was more receptive to direct mail than email or SMS. The retailer’s subsequent marketing efforts should therefore use direct mail to boost the number of transactions and, where possible, to send coupons with slightly higher margin offers.
Good targeted marketing options for the other segments would include the use of loyalty programs to engage sporadic customers for better category penetration, as well as to engage the big baskets group for better frequency.
Mass marketing efforts can be used to attract and grow the number of customers in the profitables group. External demographic data can be used to identify look-alikes for this category—those you might be able to attract and expect to behave similarly.
Targeted marketing for MVP customers should seek to protect and retain, identifying and engaging high-value and potentially at-risk MVPs, while also reactivating lapsed customers. Outreach to this set can be triggered automatically if the customer hasn’t shopped for a certain period of time, such as six months or a year. Personalized offers can also be used to cross-sell shoppers in each of the big spending groups.
While the specific segments and their characteristics will vary, any specialty retailer making this type of effort will likely gain a heightened understanding of its customers and their purchase habits, along with the ability to better align marketing strategies and improve profitability.
Ugam provides data and analytics for retailers, brands, B2B manufacturers and market research firms.Favorite