Data Analytics

How Retail Leaders Apply Big Data

Teresa Wingfield

July 14, 2023

retail big data analytics

Retailers can use big data to gain insights into their customers to enhance the customer experience, improve marketing and to optimize pricing, inventory and supply chain management. The collection of vast amounts of data and using advanced retail analytics to discover insights, make predictions and generate recommendations provide tremendous opportunities. Data-driven decisions can maximize sales and profit, strengthen customer loyalty, improve operational efficiency, and reduce costs.

Here’s a quick overview of some of the key uses for big data in retail:

Customer 360

Customer 360 gives retailers a complete view of customers by aggregating data from the various touch points that a customer may use to contact a company to purchase products and receive service and support. This requires bringing together big data from enterprise and SaaS applications such as CRM, ERP, customer service and support, sales, social/behavioral and third-party data sources and applying advanced analytics to uncover deep insights, make predictions and generate recommendations.

Customer 360 can lead to improved business outcomes and more importantly, increased revenue. Using Customer 360, you’ll learn more about your customers, the best ways to engage with them, the targeted offers that will resonate, the likelihood to churn, and the best ways to personalize the customer experience in real-time to win more business and drive greater customer loyalty. You can also discover more about your products, including the most profitable product groups, which products benefit the most from associations with other products, optimal shelf arrangements and how to optimize promotions.

Data-Driven Pricing Decisions

By using advanced analytics to inform pricing decisions, retailers can make more informed, data-driven decisions based on customer behavior and market conditions.  Retailers need big data, including internal data such as customer behavior and sales data, and external data such as market and competitor data to drive pricing analytics for:

Price Optimization

  • Dynamic Pricing to adjust prices in real-time based on customer demand, competition, and other factors.
  • Price Gap Analysis to compare prices to those of competitors.
  • Bundle Price Analysis to set the optimal discounted price for a bundle of multiple products or services.

Inventory and Supply Chain Optimization

By analyzing big data for inventory management, retailers can identify sales trends, forecast demand, and make informed decisions about ordering, stocking, and distribution. This helps retailers optimize their inventory levels to reduce stock shortages and overstocking.

Big data analytics can also help retailers reinvent their supply chain across sourcing, processing and fulfillment of goods.  Supply chain data comes from procurement, inventory management, order management, warehouse management, fulfillment, transportation management, and more sources. Analyzing this data identifies opportunities to align supply with volatile demand, avoid supply shortages, achieve faster delivery, and decrease labor costs.

Ready to Get Started?

Retailers will need to accelerate their use of big data and advanced retail analytics to anticipate changing customer needs and dynamic market conditions.  We’ve just scratched the surface of use case opportunities, including customer 360, data-driven pricing and inventory and supply chain optimization.

Are you looking for a solution to support your big data needs? The Actian Data Platform makes it easy to analyze big data from terabytes to petabytes. The Actian Data Platform to learn how it makes it easy to connect, manage and analyze data. Download the Ventana Research Analyst Perspective, Actian Manages Avalanches of Data, to learn why the platform is so scalable.

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian where she is responsible for communicating the unique value that the Actian Data Platform delivers, including proven data integration, data management and data analytics. She brings a 20-year track record of increasing revenue and awareness for analytics, security, and cloud solutions. Prior to Actian, Teresa managed product marketing at industry-leading companies such as Cisco, McAfee, and VMware.