How to use customers’ life stage changes for deepening customer loyalty?

Lokendra Devangan
David is an investment banker based in New York. At least twice every month he visits Redwood hypermarket to shop for groceries and other personal needs. Three months ago, he married his girlfriend from China.

David was lounging around on a lazy Saturday when he received an SMS from Redwood. The message offered 40% discount on woman fashion brands at a partner retailer and 30% discount at famous Chinese restaurants in central New York.

After seeing the offer David was impressed with Redwood.  He was also surprised as most of their earlier offers were bundled for grocery items. Why did Redwood think that these offers were relevant for him?  He then smiled and thought that he will definitely avail both the offers next month on his wife’s birthday. He will gift his wife a lovely handbag and take her to one of the restaurants for dinner.

How did Redwood figure out this highly relevant offer for David?

David is a loyal customer of Redwood. Redwood Customer Loyalty team uses advanced analytics method to identify the customers’ life stage. They track the customers’ basket size, product mix and frequency of visit to segment customers into groups such as large family, family with kids, family without kids, Single, occasional visitor etc. Loyalty team observed that in recent months David’s monthly spend at Redwood store has increased and the basket composition has changed. They noticed that apart from larger baskets, transactions for his household now routinely include women’s beauty and hygiene products.

Redwood employs automated analytics where the system captures such changes in behavior, and identifies opportunities to enhance marketing around this life stage changes.

The change in the product-mix in David’s basket can be permanent or temporary (a friend or a relative visiting). Redwood loyalty team can test the hypothesis that this is infact a change in relationship status and that the partner likes Asian food. Redwood to test their hypothesis has created a special personalized offer for David and extended discounts at partner fashion retailer and restaurant chain. They also plan to send such multiple offers over the period of next two months. If David responds to offers regularly, Redwood will be able to conclude that David is married. This information can be used for more personalized offers.

Redwood has realized the power of data analytics and used it efficiently to enhance the relationship with the loyal customers.

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