I’m a fan of loyalty programs – the proof is to the right – most of my collection of loyalty cards. But just because I have the card doesn’t mean that I’m a loyal customer to each business. Of the ones featured I’m only a good customer to 3 or 4 of the businesses. And I’d say even fewer of those companies use data analytics effectively to market to me and send me enticing promotions – my loyalty steams from proximity to my house. The businesses I’m most loyal to track me by my phone number, or credit card/debit card, or have created an app, making it zero hassle for me to be a part of their program. And of those almost all use analytics to market to me and retain me as a customer by sending me personalized promotions. They have figured out that loyal customers are the best customers and bring in the most revenue and by using data analytics to enhance their loyalty program will result in even higher revenue. The challenge to most retailers is how to use customer data effectively and improve the customer experience and increase loyalty. Below are examples of how some companies are using big data to improve customer loyalty.
1. Implement analytics throughout the organization
Big data is often looked at and used at a strategic marketing level, to determine what location gets what stock at what price, and to send personalized automated emails and promotions. The people who are looking at and using the data are usually sitting at a desk far removed from the customer. One company, DSW Inc. used data strategically throughout the entire business to enhance their current loyalty program and had a lot of success with it. They realized in order to be successful they had to champion the strategy from the top and have complete buy-in at the store level. Employees at store level were able to provide more insight into problems and how to fix them, and provide more stellar customer service. One idea and strategy that came from store level that helped to retain customers is managers at each store personally wrote thank-you notes to their stores top 25 customers. By giving their employees data DSW Inc. was not only able to improve customer loyalty, they were able to use data to help their front line employees get excited about strategy and feel more empowered. The result has been a leap from being 5th in market share to 2nd in the span of 2 years.
2. Get to know your customer
Super Retail Company used big data to create a loyalty program for their Supercheaps Auto Stores. They used big data to know their customer better and built a loyalty program based on their customer knowledge. By leveraging their customer knowledge they were able to identify a customer service issue, and improve the customer experience by implementing it into their loyalty program. Through analysis they were able to identify the problem of when they had a sale or promotion customers would return items they had previously purchased. When building their loyalty program they spun this into the program – members would automatically receive a store credit on items they bought that go on sale within a specific time period after buying them. They were not only able to improve their customers experience they increased sales because customers would spend more to use the credit.
3. Use individual customer data to provide better customer service
Personally one of my pet peeves is providing the same information more than once during a customer service call. I can never understand why I have to type my phone number into my phone when the customer service rep always asks for it anyway. Nearly all calls to customer service are to issue a complaint, customers expect the call to be a bad experience, but companies can turn this negative call into a positive customer experience by using data effectively. Amazon is one company that has done this well and has implemented it across channels. In one example a customer issues a complaint on the amazon website. Within minutes he receives a call from a customer service rep, through the information he already provided the rep solves his problem within 2 minutes – he doesn’t have to give any more information, she already has everything in front of her.
4. Personalize the customer experience
Sears Holding used customer activity at the individual level to provide differential and personal attention to their best customers. They also use data to provide more relevant and targeted communications through segmentation and personalization. Sears has found that loyalty members shop more often and spend more than their non-members. By using big data at an individual level in their loyalty program Sears Holding has been not only able to retain their best customers, but gain more of their best customers. Another example of a company using big data to improve loyalty through personalization is Macys. Macys has used big data to improve through providing customized incentives at check-out and send hyper-targeted direct email messages to their customers – they send 500,000 unique versions of a single email. By using big data Macys has been able to improve sales over the last few years by 10%.
For even more tips on how to improve your loyalty program download our Loyalty Program Cookbook.