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Mining volumes of customer data can pose a significant challenge for any loyalty marketer. Finding the true connection between customer data and impactful loyalty programs is not an exact science.
John Geiger, director, client services, Baesman Insights & Marketing, talked to Loyalty360 about this alluring topic.
There has been so much talk about data in recent years and how it relates to impactful customer loyalty programs. What is your assessment of this connection?
Geiger: Marketers often think of data in abstract terms—as a statistic or an action driven by a lever the marketer pulled. While it is to a degree, it’s much more than that.
Data is the customer talking directly to us. It’s their unfiltered feedback, a daily report card on how the brand is doing. With focus groups and surveys, the answers are often too conscious, whereas the customer’s interaction with the brand has a deeper level of truth we can assess.
How can data be leveraged to improve and enhance the customer experience?
Geiger: Today, data is mostly utilized reactively at the end of execution, but analysis needs to be used to drive strategy, not just hindsight. It’s used on a micro level instead of assessing the macro approach to strategies that can make experiences better at the seasonal level.
We often hear about siloed data, but the bigger silo is teams and departments. Marketers need to think bigger, not just the analysts. Email, e-commerce, stores, and digital—they all want their own assessments focused on their sphere, but nobody is looking at the broader cues that can truly impact a seasonal strategy.
Before seasonal planning even begins, the data needs to be analyzed proactively. That’s how great brands truly enhance the customer experience—it’s the only way to make major strides based on what the customer is telling you through their interactions.
Can you talk about Big Data vs. Little Data and how they should be viewed by loyalty marketers?
Geiger: We don’t think there’s really a distinction between big data and little data. Data is neutral—it’s how you think about it, analyze it, and use it that makes it big or small—micro or macro.
The term big data makes people hyperventilate, but really the amount shouldn’t change your approach—only KPIs should alter your approach.
The biggest challenge we hear is that loyalty marketers have too much data and don’t know how to fully leverage it to make it actionable. What is your advice?
Geiger: Marketers get caught up in the amount of data at their fingertips—it causes data paralysis and it’s the wrong focal point. Start with your objectives—what are you trying to accomplish, what are your goals, what can you measure to impact those? Objectives are the foundation of everything. Define them, optimize them, and focus.
But there’s a bigger issue for marketers than just the amount of data. As marketers, we often think we understand the brand, or what works and what doesn’t. We implement our own bias and try to analyze it and prove it out later. Or we say that’s what works for the brand, or that’s what leadership wants this season.
But numbers don’t have an agenda. They aren’t there to hurt your feelings—they’re telling you a story of where you need to be. Be open to that—you don’t know better than the numbers. Brands that are successful within loyalty are using data to drive where they’re going, not where they’ve been.
Various companies use data differently as it relates to customer loyalty. How does Baesman believe data should be used in this regard?
Geiger: Most loyalty providers measure it as a redemption of rewards. It’s important, but what’s the program really doing? What’s the customer migration, what’s the journey, and what would it have been without it—in other words, what’s the incrementality?
We’re going beyond the surface value to find a deeper connection to the customer. We want to make them a better customer while making our clients a better retailer to them.
It’s all relationship marketing. We want to build a relationship with each member. It’s profitable to the business, but the customer needs to love it just as much as we do.
You need to see that story through the data and filter it through your own brand identity and figure out what customers really want.
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