More than ever, retailers can plan inventory, stock, logistics, habits, and customer expectations more precisely thanks to Big Data.
It’s no secret: the increase in data unlocks a wealth of information about customers, and retail has taken note.
For physical stores, applying Big Data enables understanding which products sell best and the habits and pathways customers follow within stores thanks to IoT technologies. Real-time tracking of sales and inventory levels is used to more effectively predict future demand.
Given that retail involves omnichannel strategies, managing online data—while complying with personal data regulations—is crucial. In Spain, e-commerce is consolidating as an alternative to traditional retail, with 55.2% of people having shopped online in 2021, up by 1.4 points from 2020.
First and foremost, to support data strategies applied to retail, one must not lose sight of the abundance of devices. Being able to gather information from all of them is central. Retailers need to observe customer behavior and purchase history from computers, mobile phones, tablets, and other devices.
On the other hand, customers prefer personalized interactions and suggestions from relevant brands and companies rather than generic proposals. Knowing what the customer is looking for and their preferences allows companies to generate tailored messages in a context where customer acquisition costs are notably high, and segmentation helps target those most likely to complete a purchase.
Access to customer data also allows organizations to see user journeys and identify where customers get confused about navigation and abandon the app or website. For example, auto-completing personal information such as name, address, and phone number can significantly improve customer satisfaction and, consequently, sales revenue.
In a constantly changing world like retail, the ability to predict market changes and customer behavior is a game changer. Based on historical data collected, companies can make accurate predictions and determine how certain trends and events may affect customers. Knowing what your customer base wants and needs allows for inventory planning and gaining a competitive edge. Evidence of this is that global giant Amazon has perfected the art of collecting and applying data and trends in its user recommendations, building an empire around it.
Big Data-based algorithms are increasingly making a difference in this area. For example, it’s possible to know what customers buy in the event of a sudden change in weather conditions. An interesting case is the collaboration between Pantene, The Weather Channel, and supermarket giant Walgreens. Pantene saw its sales surge by more than 10% in Walgreens stores through its data-driven ‘haircast’ project. With the help of weather forecast data from The Weather Channel, retailers could market selected products based on seasonal changes and that week’s weather forecast.
Using as much data as possible helps retailers and supply chains address inventory issues and potential disruptions to improve customer satisfaction, brand loyalty, and revenue generation. The role of big data in retail also involves identifying potential bottlenecks and finding alternative solutions before they have the chance to become major problems, saving downtime and disruption costs.
By Julio Cesar Blanco – November 22, 2022
