Time to Activate: How to Leverage Your Customer Data

By: Max Kenkel
warehouse team analyzing customer data
In a previous post about leveraging customer data, we talked about starting with the end in mind. How do you plan on using the data you’ve collected? Below, I've listed just a few of the ways you could start to leverage data to amplify your bottom-line results (but as mentioned in the previous post this list is by no means exhaustive). Keep in mind—each new data type can accomplish all the uses of the data type above it.

Sell-In Data

How You Can Use It: Inventory planning, customer demand modeling, market share, goal setting

Sell-Out Data (Claims, Disparate POS)

How You Can Use It: Basic audience segmentation, upsell opportunities, geographic mapping, customer identification, customer product loyalty, product launches, targeted promotions to both customer and channel, brand advancement (plus above)

POS Data (Market Basket)

How You Can Use It: Advanced audience segmentation, product grouping, profitability modeling, value add promotions, product targeting, experiential marketing, targeted offers, loyalty programs, retention and reactivation campaigns (plus above)

Survey Data

How You Can Use It: NPS and invitations into an advocacy program, customer service and retention strategies, customer experience tracking, areas to focus training (plus above)

Geographical or Demographic Data

How You Can Use It: Heat maps, seasonal targeting, cultural targeting, interest-based targeting, product promotions (plus above)

Behavioral Data

How You Can Use It: Cloning ideal behaviors, training, all of the above
Those are just a few ways you can use data you’ve collected. But let’s take it a step further. I’ll walk through how your company might use some of the data above to execute a targeted customer activation strategy. 

Sell-In Data

If you have sell-in by geography, you can get ahead of your competition by identifying where specific products are selling vs. where they aren’t—and match against any public data sources that make sense. Segment these groups and plan for increased inventory in locations with high customer demand. Seems simple, but you can bet that somewhere there is a store that has an entire pallet of obsolete product in the back, because someone lacked this data which would have shown no one is buying that product any more. This can also help ensure your customers have the product they need and can get it quickly.

Sell-Out Data (Claims, Disparate POS)

If you don’t have consistent POS, you likely need some way to collect sell-out data. If you collect product purchases, name and address, you can use this data to graduate your customers to your higher margin brands by sending them an exclusive offer. “We see you like X. If you jump up to Y, we’ll give you something really neat.”
You can also match this to your sell-in data to help plan for inventory.

POS (Market Basket)

This is where the fun begins. If you have transactional sales data, you can do just about anything. First, segment your audiences AND products into key groups. In other words, sift through the data to find out if people who typically buy a hammer also buy nails. Even better, find out if one group buys nails but another group buys gloves. Then, analyze and track other behavior factors to see if you can even identify what led to the hammer purchase. Now you can target customers based on your segmentation to get them to buy the hammer and nail combo, or the hammer and glove combo, or hammer and higher margin glove, etc. Critics will tell me this is way too cavalier an explanation of what is meant by market basket analysis. While that may be, at a high level, it’s identifying trends in your audience and exploiting those trends with like-customers who have yet to purchase the same products, where data tells us it’s a good match. Or, there’s an opportunity to push a higher margin item to specific demographics based on like-customer behaviors.

Survey Data

In my opinion, survey data is some of the most powerful and useful data you can leverage, yet . If you ask enough smart questions, you can provide your segmented customer groups with highly personalized offers motivating them to grow their purchase volume or change their behavior in your favor. Leveraging a flexible survey tool is worth the investment if you can ask dynamic questions.
  • Do they have a second vehicle? Target them to bring in their second vehicle for tires.
  • Do they have your cable but no security system? Target them to upgrade to a bundled package.
  • Are they a rabid promotor of your brand? Invite them to be a referral partner.
Surveys are the voice of your customer and, if you do it right, you can learn everything you need to know. It also allows you to collect some deeply personal information, which, depending on how you use it, is either very meaningful or super creepy. Usually I’d roll the dice because a personal and emotional connection to your brand is what wins. But make sure your strategy aligns who you are as a brand so as not to have a disjointed experience for your customers.

Adobe Improvements from Personalization Chart

Geographic or Demographic Data

Let’s say you sell a seasonal product. Do you want to launch your mosquito solution to residents in Montana in February? No, they might still be under a foot (or feet) of snow. What about southern Texas or Florida? Maybe. Conversely, you probably won’t sell many parkas in Southern California in November. Matching geographic sales history to your audience segmentations can tell you when to target a regional customer, when to go big in a region, and it helps make sure you are targeting the right customer with the right offer at the right time.
A lot of these ideas, especially targeting geographically, are not new, and probably are already anecdotal truths in your company. Leveraging the data helps in two ways. First, it confirms this is actually a truth, and not just a fun story the old timers tell by the water cooler, and second, data can specifically identify when you need to pull the trigger. It helps takes the guesswork out of your decisions.

Behavioral Data

One of our clients changed the day they send out their weekly newsletter because we were able to track open rates by day and the data told us Wednesday had more opens than Thursday. Obviously that’s not the sexiest example, but more people are reading their newsletter than ever before, and loyalty is built on repeated, positive brand interactions. Small shifts in behavior, over time, lead to big changes and can even shift a customer from one tier or product to the next, or from one segment to another, leading to more sales and more emotional connections with your brand.

You Need to Start Somewhere

To the advanced data analyst, this might seem insultingly basic. Not everyone is a Facebook, Amazon, Google or Ulta. Those companies have either reinvented themselves or built their entire existence by leveraging data. But to those hundreds of companies who do a decent job of using data, and those thousands of companies who are just scratching the surface, it can be done and it can be powerful. Don’t be afraid of failure, just do it fast, learn from it and do better on the next test. Leveraging data doesn’t replace a great product or great customer service, but it can sure amplify your results (and, it actually can help design a better product or place focus on the customer experience).
By understanding your customers’ passions and what drives them you can meet them where they are, show them you know what they want and connect on a personal level.
Want to learn more about how we help our clients meet customers where they are? Check out this post, Mapping the Customer Experience: Answers to 7 Common CX Questions.
Max Kenkel
Max Kenkel

Max’s favorite work pastime is looking at data and figuring out how companies can monetize it. He even does it with his band, by looking at Spotify heat maps and targeting shows in cities with higher volumes of streaming. He firmly believes that you can make a decision based on intuition, but it’s a lot easier to justify it to the shareholders when you can back it up with data. He really does like talking about leveraging data, and quoting Star Wars.