Why Data Science is so important for building Retail 3.0

Consider the following scenarios:

• A supermarket that provides personalized offers to each of its customers not only through digital channels, but automatically during the checkout transaction, increasing sales, shopping visits and customer retention.
• A collaborative marketing portal where partners create content and promotions for different customer segments, measuring the effectiveness of each action and each channel.
• A new distribution model that provides a real-time view of the movement of inventory from production to the dock for delivery to the store and achieves significant cost savings by accelerating the distribution cycle, reducing inventory and creating new efficiencies at the store level.
• A cutting-edge system that makes customer data actionable and automatically creates comprehensive behavioral customer segmentations and achieves improved ROI by integrating traditional product category management with customer category management.
• Time- and location-based mobile marketing services capable of delivering a lunchtime promotion to a customer’s mobile phone a mile away from the store at noon – the system then switches to delivering marketing promotions based on where the customer is in the store.
• And imagine what happens when you start connecting these seemingly disparate parts, when you start exploiting the synergies that can be created throughout the supply chain, both in product efficiency and in marketing efficiency – all with the individual customer as the focus.

Congratulations! You have just imagined what Retail 3.0 is.

It is worth a kind of historical retrospective. After all, if we are entering the era of Retail 3.0, it means that we are going through Retail 1.0 and 2.0. So let’s understand a little more about this evolution.

When did the story begin?

Retail 1.0 began exactly on September 11, 1916, when Clarence Saunders opened the first Piggly Wiggly store in Memphis, Tennessee, and started the self-service revolution.

Simply put, he was able to convince a large distributor, Shanks, Phillips & Co, with whom he had other business partnerships, to build a store with exposed shelves so that people could see the goods and their prices, move freely under guidance and independently transport the products to the till. . So, it does not differ much from the current supermarket. In just over ten years, the distributor has opened more than 2,500 supermarkets in the United States based on the idea of ​​self-service. Walmart pioneered the concept and took the idea even further by introducing “One Stop” stores – a store that could offer all types of goods/products under one roof.

second phase

Retail 2.0 was the era of e-commerce retail, buying and selling goods online using a digital experience platform to transfer money and data to facilitate the transactions involved. Technology and the Internet were real disruptors because together they completely transformed sales/buying models. This is how we saw how Amazon transformed from just an online bookstore into the world’s largest e-commerce platform in the shortest possible time. This was only possible with the use of the most advanced technologies and an efficient global supply chain.

In e-commerce, the focus is on customer experience management as an element that can change the balance of business. From the late 1990s to the present, the concepts of multi-channel and multi-channel have become increasingly popular.

Go offline or online, go offline + online

The line between offline and online is becoming more and more blurred. And this has pushed the world towards Retail 3.0, characterized by the continuous interweaving of the physical and digital worlds. The new ecosystem is essentially a mix of brick-and-mortar stores and e-commerce platforms with a focus on managing the customer experience on their digital journey.

The fact is that this implies that there are no longer any differences between the physical and digital identity of consumers. Likewise, buying trends and customer experience seem to have become much more similar, regardless of the interaction channel. Now they are more and more consistent and personalized.

The approach strategy therefore ceases to be related to the interaction channel and begins to focus on the customer. There is no longer an abstract customer buying journey and it becomes important to know the specific buying journey of each customer. Therefore, the effectiveness of the approach will depend solely on how willing we are to use disciplines such as Data Analytics and Data Science/Engineering.

The numbers are impressive. When it comes to the retail niche, according to the experiences of the consulting firm Expert, having information about who your customer is and how they behave can result in an increase in sales between 30% and 50%.

Even when it comes to mass retail, where the battle is mostly in the discount arena and where every penny counts, data-driven initiatives have shown a growth rate of more than 3%. And that’s something that was previously unheard of, according to Stacey Widlitz, president of SW Retail Advisors, analyzing Target’s sales growth — 3.4% — compared to its competitors. He drew attention to the fact that marketers using data analytics are winning the war for consumer preferences.

In the next article, we will delve a little deeper into the key technologies of Retail 3.0. Until then.