Amperity Unifies Fleet Farm’s Loyalty Program

You might be forgiven if you’ve never heard of Fleet Farm as a destination for home-improvement, agricultural, and outdoorsy pursuits if you’re not from the Midwest.

Fleet Farm is a destination with a loyal customer base, and recently tapped Amperity to manage its customer-loyalty program. Amperity uses AI for identity resolution and to create customizable data models among other offerings.

Fleet Farm’s senior Director of Marketing and Commerce Jessica Gillett called the partnership an investment in her company’s future. In a statement, she said, “By establishing a clean, unified customer data foundation, we can now move at the speed our business demands. This technology will enable us to better understand and serve our customers through timely, relevant personalization, while setting us up for long-term growth and innovation in how we engage with our shoppers.”

Jason Perocho, SVP, head of marketing at Amperity, sat down with StreetFight to discuss how the partnership will help Fleet Farm.

Tell me a little bit about the working relationship with Fleet Farm.

We help Fleet Farm understand their customers better by bringing together all the different touch points into one unified profile. That sounds easy, but it’s much harder than it seems when you dig a little bit underneath the surface. When you have a loyalty program people could sign up or purchase in-store or they’re on your website when they’re interacting with different social channels.  The questions that a lot of our customers face, including Fleet Farm, is how do you bring all these different identifiers together to actually construct that customer journey when there’s never been more touch points or data out there?

How did Fleet Farm run its loyalty programs before Amperity came on the scene?

Fleet Farm is a Midwestern company that has a reputation for understanding local needs and seasonal patterns. The question that a business like that usually asks itself is how do we scale that personalization like that one-to-one relationship that we could have in person across all these different channels? We help them do that by piecing together those information streams by building a profile that shows that entire interaction history with that with their brand.

What are some of the variables involved in keeping this information straight?

Some people sign up for a loyalty program but don’t remember their lo loyalty ID when they’re purchasing online. I can’t tell you how many times that I have to apply that for Delta [Airlines]. I go to Expedia and they’re like, “What’s your Delta ID?” And I’m like, “I don’t know, skip.”

Which other retailers’ loyalty programs does Amperity run?

We talk to catalyst brands. So that’s mall brands such as Eric Pastel, Brooks Brothers, Eddie Bauer, Forever 21, Lucky Brand, Nautica, and others.

We also work with mainly the biggest of the retailers out there. The Home Depot, Macy’s and a bunch of others. And a lot of all these retail similar to Fleet Farm have the same struggle and they have instore and then they have digital and how do we bring those two channels together? Because they’re both inherently extremely complex, and there’s a lot of data behind it.

We believe that the best asset a brand has is their own customer data. They could just take advantage of it because in that side of that data is the patterns that they need to understand to better utilize their business or to better profit their business.

Can you take me through an example of how Amperity helped a brand create a hyper-personalized local customer experience?

How many email addresses do you have? Have you ever gone to a brand and used a different email address to get the same coupon? [A brand may] think [it has a certain] amount of loyalty customers but when we add that up that’s more than the entire number of people in the country. A Canadian grocery that we work with said they have 95 million customers. The problem is there’s not 95 million people in Canada. When you think about serving the hyper-personalized experiences it’s the ability to then connect those dots with loyalty information.

For Brooks running, we united a bunch of their data. They had one person that purchased religiously every six months, and it was always a specific type of running shoe. Then they had a “second” person that had lumpy purchases. In the fall and spring it was very unpredictable. [This person had] two other profiles which never made a purchase but were definitely browsing on the website for kids shoes and stuff. And when we looked at it, and our algorithm brought it together, we said, “This is all the same person.”

How did you connect the patterns?

Our AI algorithm says with a high degree of certainty that these people are associated together. The reason why these profiles are even separate is because somebody might register as Jane D. Another one could be registered as Jane Doe. And another profile could just have a misspelling on it.

We have fuzzy matching that looks at not just the names but the addresses, the email, the location of where the device was being sign signed on. We try to triangulate and say wait this is all the same person. And that’s how we start bringing the data together to assemble one unified profile.