I’ve been involved with loyalty programs for over twenty-five years. Much of my work is with restaurant chains (17 of them). I’ve also helped several retailers, travel companies (airline + hotel) and some B2B firms. I focus on analyzing the performance data to determine the impact the program has on the business. It’s common for companies to launch a program and leave it on auto-pilot, assuming that it’s having a positive impact. I focus on finding the answers to some simple but important questions. Do customers stay with your brand longer because of your program? Do customers visit/spend more? Check out my Linkedin Profile.
Understanding the performance of your loyalty programs requires getting into the weeds with the data. You can’t determine what’s really going on by using information that has already been aggregated. I work with clients and their loyalty software provider to get the granular data. With that I can derive useful and meaningful insights.
I’m a data scientist, software developer and marketing guy. I do science and art. I do left brain and right brain. Because I’ve worked with so many loyalty programs over the years, I know what to expect and what to look for. I cut to the chase and get high-caliber work done quickly. I’ve been with big firms and I find it’s not uncommon to have a lot of time and money wasted, and a mediocre product delivered. I’m a hired gun and I get things done well, quickly and at a fair price that’s based on value.
I’ve run into quite a few restaurant companies with loyalty programs that need periodic data analysis help and don’t have an internal data team, or their team doesn’t have the cycles to handle all the ad hoc requests that come up. These are companies on the Paytronix platform, and because I’ve worked on the Paytronix platform for nine years with about a dozen companies, they call me. I offer modest retainer relationships that make it easy for clients to get things done quickly with someone who knows loyalty, is a seasoned analyst, knows the data and how the system works. They can just shoot an email or pick up the phone to get things done.
A SAMPLE OF TYPICAL REQUESTS
- Segmentation of program members based on visit frequency with average visits, average check.
- Retention of existing members from period to period (3-month period, 6-month period, 12-month period). How many that were active in both periods spent, more, less, or about the same?
- Response to a specific offer, spending during a prior period and post period to identify lift.
- Segmentation by store (identifying similarities and differences from store to store).
- Performance of members by tier (for programs with tiers).
- Members visiting specific stores on specific dates during specific times (typically for tracking attendance at certain event or during certain sporting events).
- Cohort analysis: follow a group of members who joined in a given month to determine how many have one visit and don’t return. Create segmentation for those with more than one visit.
- Create a segmentation by daypart. Who are the lunch-only members, versus dinner-only members, versus both?
- Create weekday versus weekend segmentation.
- Segmentation of members by net value: how much do they contribute (spend) versus cost (reward redemption).
- Purchasing by item/plu – where check details are available.
- Loyalty penetration overall and by store.
I won’t waste your time. Let’s discuss your situation. That’s a good starting point. I guarantee that you’ll find it time well-spent.