Retail is one of the sectors experiencing an enormous transformation in the world of business.
Thanks to IT, retailers are using the boundless data resources to make vital decisions for their business success. It seems, in fact, that the efficiency of retail can no longer be a reality without big data analytics. Even the smallest business today has so much data available that it’s impossible to analyse it using previous database techniques.
What is Big Data?
Big data describes the limitless amounts of data available for organisations and businesses. The large volumes of data are gathered from multiple online sources including social networks, sensors, videos, digital images and sales records.
As it would be impossible for businesses to analyse the large amounts of data using conventional database techniques, big data storage is enabled by infrastructure designed to support the storage, management and retrieval of such data. Businesses can then connect to the computing server nodes to access, process and use big data indicators to make key business decisions. Precisely analysing the large quantities of data reveals crucial patterns and connections among those who supply the data.
For retail, big data analysis has a core focus on the consumer. Consumer trends provide valuable insights which can be used to the advantage of the business. This is why, when defining big data, underscore is often made to the fact that ‘big’ is not exactly about the amount of data. It is instead about the benefits that users can draw from using the data to the advantage of their businesses.
But how exactly is big data useful in retail? We highlight the top 3 ways big data is transforming the retail sector.
1. Identifying Consumer Trends to Predict Product Demand
How do big online sellers like Amazon deliver goods on the order date, or a day after, anywhere on the globe? Not a question of transportation speed. Big data allows companies to do demand sensing by tracking consumer trends for a particular product in specific parts of the world and using that to predict future product demand and purchase.
Thanks to consumers in your area who have recorded consumer interest and purchases online, retailers can create product warehouses in your area to ensure prompt delivery upon online purchase or create brick and mortar stores for consistent supply.
2. Price Optimisation
Through big data, retailers have valuable information related to customer willingness to pay for a product. For example, big data algorithms are being used by retailers to automatically detect which among the consumers is likely to pay higher prices for a product. Additionally, retailers are using big data to track the pricing trends of their competitors and decide on their pricing. With the information on customer willingness to pay and competitor pricing, retailers can incorporate their business profit targets to optimise pricing.
3. ‘Manipulating’ Repeat Business
For any retailer, selling a product to a consumer once does not make business. Customer retention or repeat sales are core to business success. With big data analytics, retailers can study customer patterns and put in place strategies for consumer retention. This could range from knowing your customers’ spending trends (how much and on what), showing loyalty to your customers by listening to them (connecting with them on social media and listening to their consumption feedback) and delivering the right products to the right consumer and at the right time (targeting families with seasonal products before festivities).
In a world where data is majorly digital, the retail sector will continue to thrive if the big data resource will be consistently used to inform business decisions that link production, marketing, and sales to customer demand and purchasing trends.
Looking for a partner to help your business maximise the benefits of the big data revolution? Contact Dynavics today.
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