The transition to a data-driven company is a necessary step if in the near future it wants to be able to meet the needs of a very demanding consumer in terms of customer experience increasingly oriented towards omnichannel. Indeed we could almost say that today’s customer has become channel-less by definition, given that he moves with ease between all the touch points and uses in an undifferentiated way all channels, but what is able to conquer him is the ease of access to the product and a tailored response to his requests, thanks to the customization possible only through a data-first approach to business.
An effective data-driven business model is the backbone of Retail 4.0. Data and technologies optimize the customer experience, improve customer engagement and also refine the management of internal processes, such as those relating to the supply chain.
How? In large-scale retail, for example, big data are all the information on consumer behaviour and preferences that a brand can collect, both online and offline, through all the available touch points (from physical ones to those of e-commerce and social networks, right down to loyalty programs). With data it is possible to better know your customers, the preferences shown during their visits to the e-commerce website, the needs of the moment, the trends that are gaining ground, but also the number of visits to the store, the conversion rate, the duration of visits, average spending, requests made to the contact centre and chatbots and much more.
According to research conducted by Google and Boston Consulting Group to understand what are the most effective proprietary data strategies for brands, companies using proprietary data for their core marketing activities achieved up to a 290% increase in revenue and a 150% increase in cost savings. However, despite the clear advantages they offer, most brands are still unable to fully exploit the potential of first-party data.
But big data can be useful only thanks to an appropriate IT framework capable of collecting, transmitting and processing data through AI and machine learning for implementing the personalization of the shopping experience. In fact, without the capability of collecting and transmitting data, but above all the capacity of centralized processing and application of advanced algorithms, the improvement of the customer experience, interactive kiosks, proximity marketing, virtual assistants and computer vision would be no more than a future hypothesis. Instead, all this is not only available today, but it is a path that must be taken in order to build a solid position on the market.
Let’s see what are the main trends and technologies that characterize the digital transformation of retail, always with a view to improving the customer experience and big data usage.
- The synergy between AI and other technologies such as machine learning can have a huge impact on the in-store experience and retail in general, as for example the central role of video analytics in the process of transforming a brick-and-mortar store into an intelligent store;
- Cameras and sensors can provide detailed information on customer behaviour as they can identify the most frequent itinerary and areas in which people stop more so as to determine the best point for setting up a promotion, or send ‒ through beacons ‒ a targeted offer to a customer who stops in a defined area;
- Facial recognition and voice interaction technologies allow to create a more personalized offer, making possible to propose ad hoc content on digital signage displays as the customer approaches, as well as activate virtual assistants that act as digital shoppers to maximize the customization of the offer;
- Virtual and augmented reality for an extremely engaging customer experience such as virtual dressing rooms where customers can virtually rather than physically try on clothes before they buy;
- Finally, clienteling, a marketing technique focused on maximum personalization of the shopping experience guided by a personal shopper, making possible to merge the benefits of personal contacts with the information assets coming from the company’s ERP and CRM systems.