The Technologies That Are About To Appear In Retail
Many, if not most, of the technological innovations introduced in the retail market over the last twenty years have mainly concerned products. The supply chain has focused on building new possibilities to move products quickly and efficiently, cut prices, etc. This has helped retailers become more efficient and increase their customers’ profits.
Data collection and analysis have been central to these initiatives, which has been possible thanks to retailers’ migration from the old paper-based planning and execution systems to more precise and efficient digital systems. But all of that was still focused on products. In recent years, however, retail has shifted attention to the people, to the customers themselves, who should buy those products. With this new focus on people, data science and machine learning are crucial to helping retail achieve new levels of efficiency, profitability and customer satisfaction.
Table of Contents
The Customer Experience
We are today in the new era of e-commerce. Customers can buy anywhere and anytime, in the shop, from home via their PC or on the move. Customers have instant access to product reviews and price comparisons and can easily find other product content on social media. Never in history have customers had so much power and been so demanding. So how to satisfy these customers? Giving them what they want! Not only must retailers provide customers with what they want, but they must also do it in a way that is profitable for them.
To give customers what they want in a way that doesn’t increase operating costs, you need to know them and know their behavior. Big data helps solve these problems. For example, some programs exploit big data that can help retailers understand purchasing behavior. This activity requires analyzing a large amount of structured and unstructured data. Solutions of this type are often very intuitive because they are designed with the customer in mind. With these solutions, retailers can give the customer what he wants when he wants it while maintaining an adequate margin.
The New Store Experience
Now that retailers can give customers what they want when they want it, can customers be satisfied? Still waiting. Because going deep into what modern customers want are experiences. They want a quality shopping experience that makes them feel unique, and this experience must exist across all channels, digital and otherwise, from an omnichannel perspective.
To give consumers the desired experience, stores must optimize their work and activities in a more complex commercial context and enable new processes that memorize customer behaviors. Optimization also requires good data and visibility across all store operations. For this reason, there are programs to help understand the best positioning of products within the store. Product interest data is collected in real-time and can help the retailer offer customers a better shopping experience.
Robots In Shops
Cognitive robotics can do even more. This is one of the most advanced retail technologies that exist today. These robotic collaborators will be able to collect and synthesize many pieces of information about a consumer in ways that a human can’t. Let’s imagine a customer looking for a pair of shoes and can’t find them. He might ask the robot, “I’m looking for these size 41 shoes, but I can’t find them”. The robot could reply, “You are right. We don’t have this size 41 shoe model in this store, but we have three pairs 500 meters from here. Alternatively, I can order them and send them directly to his address. We also have many other shoes in that size. You can see some here.”
They Learn And Remember
Over the long term, cognitive robotics will be a powerful differentiator for those choosing this path. The robot is also able to record all these questions and analyze the gender, mood, age range and other information about the person who asked the question and can record all this information. Like a flesh-and-blood clerk, the robot can gradually learn from the questions it asks, but unlike the former, it can memorize all the information received.
After an operating period, it is not so absurd that when someone approaches the robot, it already knows what that person will ask for. Over time it will learn which products are most often missing and which people are generically asking for something. This information not only automates business processes but optimizes and learns from them to provide better customer service. All this, therefore, assumes a scientific form and not as now an activity based on sensations and intuitions.