Why Big Data is A Big Revolution in the Retail Sector?
In the retail sector, market trends are ever changing and Big Data analysis is the key in predicting these changes in real time. Indeed, if the role of data is already important in the sector, especially with the multiplication of digital channels and the effort made to produce insight as well as the customer experience, the weight of Big Data should increase significantly.
However, an efficient use of Big Data requires above all being able to cross the information. However, the actors of the retails collect more and more data, coming from more and more different channels, which make the analysis of these more and more difficult.
The debate on omnichannel is therefore moving. Focusing on the purchasing process and the customer experience over the last few years, it is now expanding and concentrating on sales optimization and consumer loyalty.
Technological growth allows data collection with a new scale
This harvest is made possible by new tools to gather even more data and insights on the digital channels as point of sale. We’re talking about Experience Analytics technologies, which are experiential analytics technologies that examine consumer behaviour. It can be facial recognition tools, to detect the contentment or frustration of customers, but also “eye tracking” or “click to purchase” tool for analyze online behaviour.
However, how to reconcile these data? How to relate them to each other? If we can analyze the behaviour of a consumer in store, it remains an anonymous customer that cannot be related to any behavioural history or purchase.
The advent of omnichannel in data
Wifi technology and mobile devices can work around this problem. By connecting directly from their mobile phone in the store, customers are identified and the data collected on them in physical outlets is reconciled with information from their online behaviour and loyalty programs.
For example, a report from MarketandMarket forecasts an increase in the WiFi data market from $2.94 billion to $10.72 billion between 2017 and 2022.
From predictive marketing to prescriptive marketing
This de-compartmentalization of information as well as the increase in the amount of data and progress in the field of machine learning moves the cursor of predictive marketing to prescriptive marketing.
Where predictive analysis informed us of what was going to happen, the prescriptive analysis informs us of decisions to be made based on future events. In this way the analysis is more certain and avoids the emotional and human bias while allowing adapting to the speed and scope of analysis to provide. With algorithms, decisions are taken directly or at least are validated by objective data taking into account a number of factors that could not have been analyzed on a human scale.
Big Data transforms point of sale management
We may already see the effects of this new era of analytics on the management of sales outlets. In fact, Knowing the customer and anticipating their behaviours according to their habits makes it possible to adjust the layout of the shelves as the location of the products (important sales vector). For example, a store will be able to analyze online and store behaviours, determine which products to highlight according to the different hours of the day or days of the week, with a precision and tenfold relevance.
In addition, at the level of team management, behavioural analysis of the consumer associated with data and machine learning also makes it possible to adapt staffing needs, the analysis of which can be complex depending on the season, the hours and the weeks, or holidays.
Towards a more personalized customer relationship
In doing so, responding more closely to the needs of the customer in terms of service, data analysis should improve the customer experience in-store. For example, with facial recognition, immediate help can be provided when the customer seems tense. In addition the customer should benefit from more individualized offers, with personalized notifications as soon as you enter the store, product proposals bespoke or real-time promotions and in connection with his previous searches or purchases.
In summary, technology and Big Data at the service of retail and the revaluation of the point of sale, promises to be a vector of change. This evolution enables customer experience to be the growth driver, as shown by the trend away from conversion indicators to satisfaction indicators.
