We are undergoing a period of data transformation in retail. The retail landscape has changed dramatically in the past few years, and this evolution is not likely to stop any time soon. Consumers are simply changing the way in which they shop. For example, even though the majority of shopping still occurs in-store, 79% of US consumers now shop online in some form, and over half have purchased items using their mobile device. And even in-store, 90% of people use their smartphones while shopping to look up price comparisons, product information, and check reviews online.
Naturally, these altered shopping habits have huge implications for both traditional and digital retailers. So as a retailer, how do you make sure that you are not only keeping up with changing consumer demands, but anticipating future needs and developments? The good news is that this retail digital transformation is providing just as many exciting opportunities as it is new challenges. Let’s break down what it actually means for retail, and most importantly, how you can take advantage.
Data on Data
The biggest impact of all of this is the dramatic increase in data that is available — and consequently, what you can learn about your customers and potential customers. It is predicted that by the year 2020, there will be 35 zettabytes of data generated annually. That is a massive amount of data — which can be both a blessing and a curse. What does this data tell retailers about consumers?
To start, you can learn more about consumers. People are telling us more — both directly and indirectly — than they ever have before. With the right data, you can learn when, where, and how they like to shop. You can also listen to the conversation surrounding your products, service, and brand in a way that was never possible before. But the question remains: how do you empower this data, and make it useful?
Make It About The Customer
This is where retail transformation takes place — in utilizing all of the data available, to create a better, more rewarding experience for both the customer and the retailer. How? Let’s take the aforementioned examples to illustrate. First, knowing how your customers like to shop allows you to meet customers where they already are.
For example, imagine a potential customer who has little reason to regularly check their email — or who filters out all promotional offers without ever even seeing them. Instead of spamming their email inbox with offers and ads that they will likely never see, you can meet them where it is more convenient, where they are more likely to interact. In this case it might be on Instagram, with in-app purchases enabled so that they don’t even have to take a break in their browsing. With another customer it might be through a chat or promo code sent on Facebook Messenger. You can adjust based on the needs of the consumer.
In the other highlighted instance of smart data use, it should immediately be apparent how listening to the conversation surrounding your brand can benefit a retailer. Companies can use direct feedback, reviews, and other social chatter to better their product, whatever it is. People are talking more and more online, but not always in a way that directly interacts with the brands they are discussing. If you use the right tools you can listen in on the conversation and make things better. You can even use these same social tools for customer service, to respond to concerns and questions directly, whether they were aimed directly at you or not.
Intelligence is Artificial
But that’s not where the data transformation in retail ends. Ask anyone who follows these things, and they’ll tell you that the future is in artificial intelligence (AI); and in fact, there are many who would argue that this “future” is actually right now. Some retailers are already implementing various AI tools to give their business a boost against competitors.
For example, as mentioned, consumers are changing the way in which they shop. And as it gets increasingly social, customers have come to expect service 24 hours a day, seven days a week. This is fine if you are global powerhouse corporation, with employees on the clock at any given hour, in every time zone. But if you have limited resources, it can make it tough to keep up. That is why many companies are employing AI tools such as chatbots to respond to customers’ concerns with immediate answers and resources where possible.
You can even use these sorts of AI tools in other ways, such as offering more personalized product suggestions and remembering customers’ preferences. It can also be used for stock management — predicting consumer habits based on past patterns, and making sure that inventory is always correct.
Retail Transformation Continues
Data transformation has been affecting retail for a few years now, but that does not mean that we are going to near the end of the road any time soon. You can no longer ignore it. It’s not a bonus, it’s a necessity. People simply shop differently, and customers expect more. It is up to retailers to give it to them.
And yet, according to a 2018 survey, data professionals spend 73% of their time getting and preparing their data and just 27% on actually gaining insights. Import.io offers the opportunity to not only access and manage your data, but to gain crucial, real-time insights into your customers, with complete, actionable data. So instead of playing a game of trial and error to see what your customers like and dislike, you can monitor their actual sentiments and anticipate their needs before they even know what they are.
Consumers are telling us how they want to shop. And they’re telling us everything we need to know to make it as personalized of an experience as possible. It’s up to us to listen. Whether it’s data transformation, or a larger digital transformation, there is no denying a dramatic shift in the retail landscape. And those who don’t embrace could soon find themselves left behind.