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Understanding the Value of Big Data in Retail Services

By: Kaylie Gyarmathy on July 15, 2020

Information is vital in the world of retail. Companies have long relied upon sales data and market research to create better customer experiences, streamline supply chains, and improve product offerings. Now, thanks to the use of big data in retail, that information is transforming the retail industry.

Why Big Data is Booming in Retail

Today’s digital tools provide retailers with more sources of data than ever before. Not only can they draw upon what products are being sold and where, but now they can identify what individual consumers and groups of consumers are buying, what they’re considering buying, and how their purchasing decisions are influenced by outside forces.

Data gathered from social media, Internet of Things (IoT) devices, and simple internet browsing can tell companies a great deal about consumer tendencies and behavior. Advanced analytics platforms can process this unstructured data to identify trends and preferences, which retailers can then use to make business decisions that are more aligned with the actual needs of their customers rather than guessing how to best appeal to them or forcing them into a shopping experience they don’t want.

5 Valuable Use Cases of Big Data in Retail

1. 365-Degree View of Customers

Big data allows retailers to learn more about their customers, which in turn allows them to create a comprehensive picture of individual customer behavior. Understanding what a person likes and dislikes, how often they make purchases, and how engaged they are on social media are all important factors that can flesh out more traditional demographic customer data, such as age group, gender, and geographic location. Analytics and machine learning tools help companies to identify these qualities across a broad range of sources and then match them up with the appropriate consumer. Once these customers are properly segmented, they can become the focus of sophisticated, targeted marketing campaigns that better reflect their actual customer journey.

2. Predicting Spending

The combination of data from loyalty programs, app activity, and eCommerce log-ins makes it easier than ever for retailers to track spending over time. This not only allows them to see what customers have purchased, but also get a better idea of how they make those purchases and under what circumstances. If someone is more likely to shop at a specific time of year, for instance, that provides a perfect opportunity to target them with recommendations and add-on suggestions. And during low periods, the same data can be used to inform marketing strategies designed to entice them back.

3. Forecasting Demand

For all the importance of customer information, big data isn’t just about data gathered from customers. It includes information from many different sources, all of which could have an impact on demand in the marketplace. One famous example was Pantene’s use of weather data to target potential customers with ads for anti-frizz hair products if the local forecast expected humidity. Big data analytics can also help to extract important insights about how everyday events impact consumer tendencies and provide retailers with a valuable edge over their competitors.

4. Streamlined Operations

From supply chain logistics to back-office bookkeeping, big data can help companies identify inefficiencies in their organizational structure. That means the right products will be on store shelves and in distribution centers more often, employees can spend more time focusing on serving customer needs, and (most importantly) unnecessary costs can be eliminated. This is especially critical for companies that still maintain physical retail stores, which face increasingly stiff competition from their online counterparts. Technology like RFID tracking and algorithms that optimize supply chain management can help them stay relevant in an era of free shipping and same-day delivery.

5. Better Service

The ultimate goal of the 360-degree view of the customer is to provide a better customer experience. This goes far beyond simply targeting the right person with the right ad at the right time. Big data analytics can be used to process thousands of customer calls to identify common challenges customers face and implement solutions to fix them. Sensor data can provide a more accurate picture of how people navigate a physical store, allowing companies to optimize the space to reduce friction. Although customers may not be immediately conscious of those changes, a good experience will stay with them, helping to build loyalty and keep them coming back in the future.

How to Leverage Big Data in Retail

Gathering the massive quantity of information needed to make the most of big data in retail is a major challenge for many companies. Setting aside the question of where to store all of that data, processing it requires massive amounts of computing power, which is often beyond the capabilities of many retailers.

Data centers provide an ideal solution due to their flexibility and reliability. They are often the most secure environment for customer data since they incorporate numerous redundancies and offer impressive disaster recovery services. When the time comes to process that data, their ability to connect rapidly to multiple cloud platforms ensures that companies will always have access to scalable computing resources that can handle the demands of big data processing.

With multiple data center locations in key growth markets around the US, vXchnge can help retailers get closer to their customers with low-latency networks and big data processing. Our award-winning in\site intelligent monitoring platform can help retailers see when its time to scale their operations and identify potential problems before they have a chance to cause damaging downtime. To learn more about how vXchnge colocation services can benefit organizations in the retail industry, contact one of our data center experts today.

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