Analyze data to figure out how to better engage customers with targeted content for products they need but purchase from competitors, and your salespeople and website can become more useful to your customers and grow revenue.

Justin Racine

I’ve come to understand that this B2B space we all live and breathe seems sometimes to be slow to change, and other times, I can’t believe where we are today vs. where we were a year ago. Once again, I’m reminded that like most things in life, the pace is moving pretty fast—specifically in e-commerce, and even more so in predictive- and trend-data analysis.

At Geriatric Medical, we work with data on a regular basis. We look at engagement and disengagement trends around our products and content, we look at revenue by channel, time of day, seasonality, etc. We look at email open rates based upon persona and content. You name it, we track it, and for a mid-sized distributor, the power of data can really move the needle when it comes to finding opportunities and eliminating negative situations with our customers.

Not only does this help us from a sales standpoint, but soon we hope to leverage this through our e-commerce solution. Let me explain.

One specific area we look at is how much and how frequently our customers buy from us. How much they are spending within a specific timeframe, and how that compares to previous periods. Pretty standard stuff, right? Every business needs to look at this; surely it is woven into the sales analysis roles within each organization.

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But what if we can push this further? Instead of looking at just the spend of a customer, we also look at the frequency of order and disengagement. Maybe ‘customer A’ hasn’t ordered with us outside a specific time frame that we set. We can then identify this as a customer who is either becoming or already disengaged, and find a way to re-engage them through various channels (website, sales, email, etc.). We actively do this today.

But what if we could go even further down this rabbit hole? The frequency of orders is important, but as an e-commerce administrator and marketing professional I’m looking for a holistic view of what this customer means to us. I call this the “Customer Category Saturation Score,” or CCSS. This score would tell us how saturated this specific customer is with us and the product mix that they purchase from us vs. the purchasing behavior of other customers that fall into the same cohort or segment.

For example, the long-term care facilities that buy from us typically all need the same eight or nine categories of product; whether or not they are purchasing them from us or not, they have to get them somewhere. If we could look at our customers’ CCSS and apply it to other data we’re viewing, we would have some fascinating insights.

Let’s say one of our best customers is showing a -5.5% trending decrease in spending with us this year compared to the same period the previous year. But if their CCSS was 99%, we could hypothesize that we likely lowered this customer’s pricing because of some other external reason, as we still have a bulk of the business.

On the other side of the coin, let’s say that this customer has a -16% trending decrease in revenue with a category saturation score of 70%; it’s likely that we are losing or already lost a part of this business. We would then be able to drill down and view what their customer category saturation score was during the same period of the previous year, compare the deltas, and give our salespeople the key information that was needed to correctly engage the customer and attempt to win business back.

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But what if we could go even further with this data? My vision for this doesn’t stop with the salespeople. I would take an omnichannel approach with this, and re-work these missing CCSS categories back into our website content for customers that didn’t have category saturation scores above certain thresholds. The content would also target the categories customers don’t purchase from us.

We have various customer personas and segments that we serve, and each purchase their own mix of products and categories. Everyone in the long-term care market orders gloves, incontinence products, nutritionals, etc. They need these products for the everyday care of their patients.

By tapping into this data and creating a score that we can assign to these customers, we can actualize and visualize the opportunity that may or may not be there—and provide our salespeople and even our customer service reps with useful data.

Salespeople don’t have time to pull over to the side of the road and sort reports. We as e-commerce and marketing professionals need to provide them with the data they need to target the root of the problem and better serve our customers.

Justin Racine is director of marketing and e-commerce at Geriatric Medical, a distributor of medical supplies. He will participate in two panel discussions—on recruiting e-commerce talent, and getting support from senior executives for e-commerce projects—at the B2B Next conference in Chicago in September. Follow him on Twitter @JustinPRacine.

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