CDPa Founder Megan Kohout has built a career on building customer analytics practices in businesses that previously had trouble accessing and using their customer data to drive decision making. We spoke to Megan about some of the common challenges she’s seen in multiple organizations, as well the first steps she’d recommend to teams starting on their journey toward customer-centricity.
CDPa: What was the state of customer analytics at different companies when you started your journey? What were some of the first steps you took to build an organization?
Megan Kohout: I’ve tended to join businesses that haven’t spent a lot of time analyzing their customer data, so I’ve needed to determine the best ways to start using the data. One thing I find effective is to listen to how colleagues are talking about the customer and the assumptions they’re making. At a women’s fashion retailer, for example, the employees might assume that a person who buys a specific product is a new customer or from a younger demographic. I like to take those assumptions, look at the data, and share whether that’s really the case.
It’s also a matter of putting myself in the customer’s shoes and trying to understand why they are shopping. For example, are customers shopping for an outfit or for individual pieces? Are they stocking up or shopping for a specific occasion? Then, I use those questions to guide analysis.
There are also some standard customer metrics such as one-time shopper percentage, omni-channel shopping patterns, and behavior by LTV deciles that are a good place to start in any business.
CDPa: How do you go from simple questions and assumptions to ensuring your findings are used every time?
MK: I always tell team members, no matter what level they are, to propose recommendations based on their findings. It’s important to build strong partnerships with colleagues across the organization to get them on board with new and different ideas. You also need to think not just about numbers, but also about the “why” — making sure you have the capabilities within your organization to assess things more qualitatively.
"We may not have all the data we would like, but that shouldn’t stop us from learning what we can today."
CDPa: What are you looking for when hiring for a new customer analytics team, particularly those who don’t fit into the traditional “data scientist” role?
MK: When I hire for these types of positions, I care a lot about analytical curiosity. You have to be willing to learn about the customer, learn about the details of the data and learn how to write code to get data out of the systems. I hire team members who find joy in understanding consumer behavior.
CDPa: Given your current level of experience, is there anything you would go back and change about the way you’ve tackled this challenge in the past?
MK: It’s important to continue to push your thinking. There are certain metrics where the first time you hear them you think, “Wow, that’s really wild!” But, when you spend more time with it, you realize that you can add additional valuable nuance. That’s part of what keeps it fun.
CDPa: Do you have any other advice on first steps for organizations that are starting from scratch?
MK: Start simple and understand the basics of your customer. Also, be realistic about the resources you have as an organization. If you make 50 different customer segments and need 50 different creative assets to communicate to them, and your organization can’t support that, then you’re no further ahead than if you had three larger customer segments and really great creative that supports those segments.
Also, don’t underestimate the power of the data that you have! For example, you may not have a perfect methodology to establish customer ids, but if you do have email addresses, you can start to build a customer profile that includes purchases. We may not have all the data we would like, but that shouldn’t stop us from learning what we can today.
Want to learn more insights from CDPa Founders? Check out this recent interview with Sebastian DiGrande on first steps towards customer-centricity.