10 Ways to Improve Retail With Data

Retailers collecting data isn’t news. We all know that when a cashier asks for our email address or when we buy something online, the retailer will keep information about our purchases. It probably wouldn’t surprise most people to know retailers also collect data about our movements (whether within stores or on websites), our advertising and promotion preferences, what we’ve clicked on or picked up, what emails we’ve opened ... the list goes on.

A couple of data-related problems exist for retailers, though. First, it’s one thing to collect data, but it’s another to use that data to drive smart business decisions. Not all retailers use the data they collect. Second, there may be a disconnect between how retailers think they’re doing with data and what customers perceive. A recent Cognizant survey, for example, found that 85 percent of retailers in the U.K. believe they’re using data for personalization effectively, but 59 percent of customers don’t think those personalization efforts are effective. Personalization is only one-way data is used, but this suggests there’s plenty of work to be done for data use to reach its full potential.

Whether a retail business needs to begin using data or just wants to use data better, the following list of ways to improve retail experiences with data will help.

1. Predict the Future

Data isn’t a crystal ball, but it does allow businesses to predict customer behavior, which is one of the most important uses of data. Data analysis can reveal what seasonal products have done well in the past, identify characteristics of repeat customers, and highlight products whose success could grow. Armed with this information, retailers can make smart choices for the future and stock their shelves accordingly.

2. Plan Effective Communications

With data about which email subject lines have had the best open rates, which ads have driven the most sales, and which coupons have led to the newest customers, businesses can plan their marketing and advertising communications effectively. That means less money wasted on ineffective campaigns and more customers who feel the business knows what they want.

3. Track Behavioral Data to Improve Displays

When customers enter a store (or land on a web page for that matter), retailers can track what displays these shoppers gravitate toward and where they linger. This can inform decisions about future advertisement placement and featured products.

4. Create Better Store Layouts

In conjunction with improving displays, retailers can use behavioral customer data to design logical store layouts. The way customers move through stores influence their purchase decisions and tell companies a lot about their spaces and popular products. The same tactics can be used in e-commerce; a shopper’s journey through a website says a lot about ease of navigation.

5. Improve Inventory Accuracy

Inventory relies on much more than customer data. It includes data about vendors, the warehouse, and the sales floor, but accurate inventory data plays a big role in keeping customers happy. A system to manage all parts of your inventory will keep track of all this product data for you. Then customers can have the products they want as soon as possible.

6. Develop More Personalized Offers

Not all customers are interested in the same things. Data about past customer behavior can inform which customers will like discounts on a particular product line, free shipping, coupons, and more.

7. Build Better Loyalty Programs

Combining transaction data and behavioral data makes for a better, more personalized loyalty program. This personalization makes customers happier and more likely to keep shopping with a brand in the future.

8. Know How to Set Pricing

Many factors influence price. Customer transaction data helps businesses infer what pricing levels are acceptable to customers, and it’s used in conjunction with information from competitor and market research. Big data analytics help automate this process.

9. Manage Staffing Levels

When do customers shop? Which locations do they visit? What departments do they spend the most time in? Data collection can answer all of these questions, then help adjust staffing levels accordingly.

10. Go Omnichannel the Right Way

One last thing retailers should remember: The physical store’s data and the website’s data need to work together. Omnichannel is the way customers shop, and data about each customer spans multiple locations and platforms. That’s why it’s important to have systems in place that connect all this customer data, allowing retailers to make the most of it.

Customer Data Leads the Way

In a retail market growing continually more competitive, it’s time to start making data-based decisions. A 2015 report suggested businesses that use customer data well could outpace the competition by 2 to 3 times on sales, margins, and profits. To start outpacing your competition with data, I recommend exploring the strategies above.

For more insights into how data and technology are transforming retail, check out Intel’s retail solutions or visit the retail section of the IT Peer Network.

Published on Categories RetailTags , , , ,
Joe Jensen

About Joe Jensen

General Manager, Retail Solutions Division (RSD), Intel Corporation: RSD is bringing the Internet of Things to retail by developing the hardware, software and analytics technologies that will enable brands and retailers to deliver the perfect personalized shopping experience. RSD owns point-of-sale, ATM, Kiosks, Digital Signage, Intelligent Vending, and Micro Digital Signage for Intel. In prior roles Joe directed the Strategic Planning, Marketing, and Operations for Intel's Consumer Electronics Group. Before that he was the General Manager of the Embedded Intel Architecture Division within Intel Corporation. Intel’s Embedded Intel Architecture focus is the development of new market segments and applications for Intel core PC and Server technologies. These market segments include communications, point of sale, industrial computer, and educational computing. Joe has a BS in Electrical Engineering from South Dakota State University and an MBA from Arizona State University. He started with Intel in 1984 in engineering and has worked in all aspects of the semiconductor business from product design, through manufacturing and to marketing.