Customer Data: A Holiday Gift for Retailers

Two hands holding a rectangular holiday gift wrapped in red and white striped wrapping paper and a gold bow.

With ongoing economic uncertainty, this holiday season may look a little bit different for retailers. That doesn’t mean consumers aren’t shopping, but their habits are changing, and retailers must understand how to adapt. The best way to do that is through data. 

Shopping Habits Are Changing

Retailers are already navigating persistent consumer shifts and a preference for digital engagement as a consequence of the COVID-19 pandemic. Add inflation and rising costs, and it’s easy to worry about how this holiday season will fare.

But there is good news. According to eMarketer, 2022 holiday retail sales are expected to increase, with brick-and-mortar increasing 0.9 percent to $1.026 trillion, and e-commerce growing 15.5 percent, to $235.86 billion.

It’s how that shopping will happen that retailers need to focus on. 

A PWC study found that 74 percent of consumers plan to spend the same or more this holiday season compared to last year. Of those, 57 percent will shop online, with the rest shopping in stores. However, we will see fewer trips to the store as consumers attempt to get more done in fewer trips. 

We’ll also see a lot more early holiday shopping as shoppers become more price conscious. As a result, they are looking for online information that helps them make the right decisions (including online reviews), and find the best deals.

What does all this mean for retailers? The holiday season holds great opportunities – especially for those who take the time to analyze their customer data and make data-driven decisions that improve experiences, build loyalty, and provide customers with the information and products they need when they want them. 

How Customer Data Can Help Retailers Be More Efficient This Holiday Season

Let’s look at five ways retailers can use customer data to make smarter marketing decisions and provide great customer experiences.

1. Improve the Targeting of Discounts and Promotions

As a consumer, you know this scenario well: you purchase a product, and then, you start seeing ads for the same exact product the very next day. As a marketer, it’s one of your worst nightmares: you’re continuing to spend precious advertising budget on customers you’ve already won. 

This is one example where marketing often wastes spend on mismatched retargeting. But there are others, like sending an email that offers a product discount to a customer with a warranty claim or a support ticket on the same product. 

To improve ad spend, you have to know who the right audiences are, with the right propensity to buy. And to build the right audiences, you must have a complete view of your customers and prospective customers across all interactions with your company. The key to having that complete view is connecting the data from all your systems, and then analyzing that data to find the best segments to reach.

One approach is to focus on look-alike audiences that match key micro-audiences you define (e.g., high-profit customers, customers who purchased a specific product, customers who spent over $500 last holiday season). The more narrow you can define your seed audience, the better you can narrow down the right target look-alike audience. 

Another way to improve targeting is to use next-best-action recommendations that consider an individual’s interactions with your company to date. Suppose you’re using a customer data platform (CDP) that provides this capability. In that case, there is a constant feedback loop that ingests customer interactions, allowing artificial intelligence and machine learning to recommend the next-best promotion or discount based on what a customer has done to date. For example, a customer visits a product page for a sound system three times, spending an average of five minutes on each visit, and then adds the sound system to a wish list. A next-best action recommendation might be to show that customer a discount ad for 15 percent off.  

2. Get Clear on Customer Preferences

Many studies discuss the benefits of personalization in marketing, including reduced acquisition costs, increased ad spend efficiency, reduced churn, and improved customer retention.

The better you know and understand your customers, the easier it is to deliver the right messages through the right channels that drives them toward conversion. Again, the key is having that single view of the customer and using that information to personalize messages, offers, and experiences.

Retailers capture a lot of first-party customer data that can help them understand how a customer wants to be communicated with and what their interests are, including the communication channels they prefer, the products or services they are interested in, the best time of day to engage with them, and so on. With this information, you can map out the customer journey, and identify critical stages where you can trigger messages and offers that will help move customers along the path to purchase.. 

3. Improve Demand Planning

Demand planning is the process of forecasting demand for your products based on several factors, including past sales history (both online and in-store), upcoming promotions, and any trends or recent events.

By pulling together data from your CRM, ERP, product information systems, and supply chain systems, you can understand which products are in high demand and where that demand is highest (e. g. your e-commerce site, your physical stores, specific locations, or geographies). 

Armed with this information, you can plan for strategic restocking, ensuring that the right products are available where there is high demand. At the same time, supplying your customer service team with information on where to find products if they are out of stock at a particular location can help reduce friction at the checkout. 

A great example is when a customer enters a store to purchase a pair of jeans, only to find that size isn’t available. A sales associate can quickly check their system to find that size available at another store nearby and place it on hold, or place an order for them for delivery.

4. Offer White Glove Customer Services

It’s rare that a repeat customer can go into a physical store and have the salespeople know them and their purchase history. But it’s a great way to build loyalty and retention when it does happen. By equipping your sales associates with clienteling tools, they can pull up a customer profile and have the information they need at hand to assist the customer better.

Just as customers expect a personalized digital experience, many are now expecting their in-store experiences to be equally personalized. Information such as past purchase history, current engagement on websites, or customer support inquiries can provide a sales associate with a better understanding of a customer’s needs.

5. Cultivate Loyalty

The key to a successful business is building a loyal customer base that is willing to advocate on the brand’s behalf. According to PWC, 88 percent of consumers say that when a brand earns their trust, they will recommend that brand to friends and family. You can cultivate loyalty and increase retention through subscription services, rewards programs, or direct-to-consumer (DTC) services.

For example, U.S. supermarket Kroger offers loyalty cards to its shoppers. Ninety-six percent of transactions on its retail site use the loyalty card, enabling Krogers to improve its messages and offers to those shoppers. 

Amazon provides the ability for consumers to “subscribe and save,” where a customer can receive a 5 percent discount for setting up a monthly subscription and have recurring purchases delivered automatically. 

Many clothing stores also offer rewards programs that enable customers to sign up in the store to receive an initial amount off their purchase and start to collect points that will give them further discounts on future purchases. CPG brands are extending their traditional business models to include direct-to-consumer programs that get the right products to consumers when they want them.

How Are You Using Your Customer Data?

We may not be at pre-pandemic levels for shopping yet, but we are on our way. However, how people shop has changed, and will continue to change as the economy shifts.

Customer data is the key that retailers need to better understand those shopping habits and how they are changing. This data gives retailers an improved understanding of customers, and helps them design and deliver the best experiences, including the right products, messages, and offers.

Learn more about how to deliver exceptional omnichannel customer experiences. Staff Staff
The staff has collaborated to deliver the latest information and insights on the customer data platform industry.