Big Data

5 ways in which you can use Big Data to grow your retail business

In Big Data Analytics by dunritetechLeave a Comment

The retail industry has transformed rapidly over the past few years owing to the changing customer purchase patterns. One important aspect that has played an instrumental role in this change is – data. As the line differentiating online and offline is blurring, retailers are increasingly adopting a data-first strategy that helps them understand customers’ purchase behavior better and ensure they are delivering the right services to the right audiences.

Big data refers to the large mass of data collected through various channels, which is used to optimize retail performance. Retailers have been leveraging big data to increase stock, revenue, streamline sales operations and appeal to the existing customer base as well as target new audience at the same time. Big data has been helping retail businesses in delivering a multi-channel experience to end customers who are looking for a continuous online and in-store shopping journeys.

Here are some of the ways in which big data have helped retail businesses transform their operations:

Data-driven, strategic decisions: Retail firms that are equipped with the right, consolidated data can make better, well-informed, data-driven decisions without any hassle. These include customer-related, product-related and marketing strategy decisions. Retail data dashboards provide businesses with a high-level overview of competitive performance metrics and pricing promotions.

Calculate market assertiveness: As a scaling retail business, you are likely to be using Google AdWords, Facebook advertising campaign and other strategies to promote your service. But how effective are these campaigns exactly? Big data (inclusive of all these analytics) can give you valuable insights on how all the aspects of your business are performing. Big data helps in tracking a customer through his / her buying process, giving you an accurate picture of your sales funnel and the important touchpoints of a customer’s journey with your business.

Better customer support experiences: High-quality customer support helps in keeping your customers satisfied with your service and in turn, increases customer retention rates. By leveraging big data, retail businesses have been able to up their support game. How is this done? Think of the last time you dialed a toll-free customer support number. You are told that the call will be monitored for quality purposes. This kind of evaluation and feedback data have helped firms fix their commonly reported issues. In stores, retailers measure how frequently customers gravitate towards a particular area in the store and strategically place items that they are looking to sell first. All these are examples of how data can help retailers sell their products better and build stronger relationships with customers.

Pricing optimization: When it comes to pricing products, big data has proven itself to be very crucial. Closely monitoring relevant search words can allow companies to predict trends before they happen. This helps retailers present new products and fix an effective, dynamic pricing strategy. In addition to this, a 360-degree view of customers can also be used in the pricing process. This is because pricing is widely based on customers’ demographics and purchasing habits. Getting a better understanding of what their customers want can help retailers’ price and sell their product better.

Systemized back-end office operations: Stock management is one of the most important aspects of the retail industry. Retailers have been taking advantage of big data to manage the supply chain and product distribution. Server data, as well as product logs, give retailers insight about the stock-related operational workflows.

These are just some of the important use cases of big data in retail space. In addition to these, targeted promotions, enhanced lead conversions and predictive analytics are some of the areas in which retailers can streamline their business through big data.

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