We’ve talked before about how customer data plays into a targeted customer strategy. But now let’s get into the nuts and bolts of making your customer data work for you. Below I’ve listed a few ways you can start leveraging data right now to amplify your bottom-line results. I’ll also walk you through how each type of data can be utilized to execute a long-term targeted customer activation strategy that delivers on your objectives.
Types of Customer Data & How to Use Them
1. Sell-In Data
General Uses: Inventory planning, customer-demand modeling, market share, goal setting
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 for those products. It seems simple, but you can bet that somewhere there is a store that has an entire pallet of obsolete product in the back because a buyer lacked data showing customers aren’t interested that product anymore. Sell-in data ensures customers can get the products they need quickly when they stop into your stores.
2. Purchase Data (via Claims; Disparate POS)
General Uses: 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)
If you don’t have a unified POS (e.g., you sell through multiple independent store channels), you likely need some way to collect purchase data, which is sometimes called sell-out data. If you collect product purchases, names and addresses, you can use this data to move your customers to higher margin brands by sending them exclusive offers. For example, “We see you like X. If you bump up to Y, we’ll give you something really neat.”
You can also match this to your sell-in data to help plan inventory.
3. POS Data (Market Basket)
General Uses: Advanced audience segmentation, product grouping, profitability modeling, value-add promotions, product targeting, experiential marketing, targeted offers, loyalty programs, retention and reactivation campaigns (plus above)
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 customers 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 identify what led to the hammer purchase.
Now you can target customers based on segmentation to get them to buy the hammer and nail combo, or the hammer and glove combo, or the hammer and a higher-margin glove, etc. Critics may say this is a too cavalier explanation of “market basket analysis.” And they’re probably right. But at a high level, it’s about identifying audience trends and using them with like-customers who have yet to purchase the same products (but who would be a good match for the products based on what the data shows). That’s an opportunity to push a higher-margin item to specific demographics based on like-customer behaviors.
4. Survey Data
General Uses: Zero-party data, NPS and invitations into an advocacy program, customer service and retention strategies, customer experience tracking, areas to focus training (plus above)
Survey data is some of the most powerful and useful data you can leverage. If you ask smart questions, you can collect the right data to enable highly personalized offers that motivate customers in each segment, driving them to 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.
Here are a few examples of targeted 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 an ardent promotor of your brand?”
Invite them to be a referral partner.
- “Do you want to send them a special reward or experience as a thank you?”
Collect personal information like T-shirt size, favorite color or favorite team, and act on it immediately.
Surveys are the voice of your customer and, if you do them right, you can learn everything you need to know about your audience. Plus, considering growing customer concerns about privacy, surveys allow you to collect personal information in a meaningful way without coming across as super creepy.
Related: Collecting zero-party data is increasingly necessary as customers become more protective of their data. Learn how zero-party data can improve your customer experience.
A customer’s personal and emotional connection to your brand is what wins you business, so make sure your survey and data-collection strategy aligns with your brand messaging to ensure a seamless customer experience.
5. Geographical or Demographic Data
General Uses: Heat maps, seasonal targeting, cultural targeting, interest-based targeting, product promotions (plus above)
Let’s say you sell a seasonal product. Do you want to launch your mosquito solution to residents in Montana in February? No, not when they might still be under a foot (or feet) of snow. What about southern Texas or Florida? Maybe. Conversely, you won’t sell many parkas in Southern California in February. Matching geographic sales history to audience segmentation can tell you when to target a regional customer, when to go big in a specific region and when to make the right offer at the right time.
A lot of these ideas, especially geographic targeting, are not new, and probably are already anecdotal truths in your company. Leveraging data helps in two ways. First, it confirms the anecdotal evidence is an actual truth and not just a fun story told by the water cooler; and second, it can specifically identify when you need to ramp up inventory, and put offers and promotions in market to maximize seasonality. Data helps take the guesswork out of decisions.
6. Behavioral Data
General Uses: Cloning ideal behaviors, training & education, social, non-purchase events (plus above)
One ITA Group client reached out for help getting better open rates on their weekly newsletter. We tracked how their customers opened emails and found Wednesdays had more opens than Thursdays. We suggested they change the date. Obvious, right? It’s not an exciting example, but it’s resulted in more newsletter readers than ever before. Don’t underestimate the big impact of small changes.
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, product level or segment to the next, leading to more sales and stronger emotional connections with your brand.
Start Leveraging Your Customer Data Today
To the advanced data analyst, the list above might seem insultingly basic. But the list is by no means exhaustive and not every brand is a Facebook, Amazon, Google or Starbucks. Those companies have built their entire existence around leveraging data. To the hundreds of brands who do a decent job of using data, and to the thousands that are just scratching the surface, these tips show the foundational but powerful ways data can be used.
Don’t be afraid of failure: fail quickly, 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 (which can help improve your product and customer experience in the long term).
Discover examples of how top brands are using zero-party data throughout the customer journey to drive success.