A recent Colloquy report showed that the number of loyalty programs in the U.S. continues to grow, while Whole Foods is currently testing one in our industry. Loyalty programs of course generate torrents of customer data, and I'm often asked how to get the most value from the data. I normally recommend three simple steps:
1. Get to know your best customers.
Using the amount they spend and the frequency they visit to understand their value to the brand is the standard approach. However, it's also essential to understand why they shop with you. For some of your best customers, you'll just be a convenient choice: Useful in their lives, but they feel no connection to you. For others, you'll be a positive choice: They feel an affinity towards you, and will seek you out.
2. Improve their experience.
Once you understand their motivation, use that knowledge to improve their experience of shopping with you. For the convenient customer, this could mean using their purchase history to make the experience as easy as possible, but not bombarding them with information about you that they're not interested in.
For those that feel an affinity, it also means involving them in the brand: Ask their opinion, look for opportunities to surprise and delight them, and work with them to find ways you can be more useful to them. Then enlist their help in spreading the word, making it easy for them to share content and offers with their own network.
3. Identify other customers that look like them.
Finally, profile your best customers, and search your data to find the next set of customers who are the most likely to become best customers. Then reach out to them, and improve their experience too.
It is of course possible to get much more sophisticated. However, in my experience, these three steps capture much of the value. What have you found? How else do you use data from loyalty programs?