Can You Really Know What Your Customers Will Do Next?

On Tuesday, Total Retail hosted the webinar “Unlock the Secret to Knowing What Your Customers Are Going to Do Next,” featuring Todd Werden, vice president of Boston Retail Partners; and Arthur Viente, program director, e-commerce strategy at IBM Commerce. (If you missed this webinar, you can listen to it in its entirety on-demand.)

Before you can reasonably forecast what your customers are going to do next, you first need to understand them. For retailers, your customers are the center of the universe. For example, Werden shared that J.C. Penney is putting a priority on customer service. The department store chain is minimizing the tasks given to store managers in order to free them up to concentrate on providing customers with a better experience.

And J.C. Penney’s not alone. In a study conducted by Boston Retail Partners, 74 percent of retailers surveyed reported that their top customer relationship management priority is customer experience/engagement. Retailers are looking to make transactions easier and understand their individual customer better. That’s where data comes into play.

Werden said it best, “it’s all about the data.” Data is interactive and can work for both customers and retailers alike. Social media, advertising, company websites and employees all generate data, and buyers and sellers can use that data in real time.

With a seemingly infinite supply of data at their disposal, the challenge for retailers is getting all of it to make sense and, ultimately, actionable. Improving your analytics is key to this process. In the same Boston Retail Partners study mentioned above, 58 percent of participants said improving analytics is a top planning priority. All retailers surveyed plan to use analytics, dashboards or business intelligence within the next two years, and 91 percent aim to apply real-time analytics in that same time period.

However, the use of real-time analytics and reporting needs improvement. Only 14 percent of the companies surveyed said their real-time features are implemented and working well.

Werden summarized how analytics can help retailers make smarter and faster business decisions with the following four points:

• Ensure that your data is accurate. Only report data that's consistent and you know where it’s coming from.
• Start small. Since there's so much information to digest, take something that makes sense for your individual business and experiment.
• Organization is key. Match your data organization methods with your campaign or business goals. This takes time, training and experimentation to get it all working the right way.
• Make data actionable. Data can tell you many things, but can you do something about it? Be sure to pick questions that the data can answer and that you can act upon once given an answer.

There are still advances to be made when it comes to analytics, particularly around predicting future customer behavior. Viente noted that cognitive systems can help businesses understand their customers at a deeper level. Cognitive systems learn and reason through interactions with humans, so there's a shared learning environment between the system and the person using it.

For example, cognitive systems can use personality insights to connect personally with customers. This allows businesses to see who they're interacting with at the exact moment they're interacting. The cognitive system will already know details about that individual, and therefore can react with personalized products instead of a planned out promotion, for example.

In an IBM Commerce case study, the use of cognitive analytics improved the amount of products managed by a leading retailer by 400 percent. This increase was realized in not only the company’s best-selling products, but also brought needed attention to some of its slower-moving products as well. Cognitive analytics eliminate a time-consuming step that merchants experience on a daily basis.

Advanced analytics are still a work in progress, so start slow. Eventually, you'll be able to use the collected data to predict what you customers will do next.