Big Data revolutionizes operations across multiple industries, and technological trends help the solution to improve efficiency in retail management.

FREMONT, CA: The retail industry is rapidly adopting data-driven technology to increase sales. Retailers who use predictive analytics generate more sales than those who do not. Retailers are clamoring for big data solutions via customer analytics to develop faster, boost profitability, and outperform competitors by tailoring their in-store and online product offerings. Retailers personalize various factors such as store formats, promotion techniques, product pricing, and staffing. It also provides:

• Browser information.

• IP addresses of users.

• Any other technical data may help enhance analytic models to detect and prevent fraudulent activity.

Fraud detection and prevention 

The frequency of data breaches has risen to the point that one major retailer is victimized by fraud every week. Fraud detection is a critical issue to avoid losses and maintain client trust. The most common types of theft are fraudulent product returns and stolen credit or debit card information. Manipulators are constantly developing new methods and technology, and businesses must use retail analytics to detect and prevent fraudulent activity. Retail analytics is based on massive datasets that contain financial information about transactions.

Customer-driven promotions localization and personalization

Personalization may be influenced by various factors, including demographics, location-specific qualities (proximity to neighboring companies), and client buying behavior. E-Commerce giants have mastered the art of providing individualized service. Retailers attempt to do the same by offering personalized messaging, shopping deals, and seasonal freebies. Big data technology will give individualized customer service, resulting in satisfied customers.

Supply chain management using retail analytics

In the long run, supply chain management is critical for retailers. Retailers want to develop an optimized, flexible, global, and event-driven supply chain model to maximize efficiencies and strengthen relationships with supply chain partners. Without Retail Big Data Analytics, Supply Chain Management would be inefficient since it would be unable to track individual items in real-time and acquire meaningful information about shipments. Optimizing inventory, replenishment, and transportation costs is part of retail analytics in the supply chain.

Dynamic pricing

Customers increasingly compare online and showroom costs, so there should be complete price transparency. A dynamic pricing platform with retail analytics can power millions of pricing decisions among the largest retailers is required. Every online transaction is tracked at the unit level for profitability, considering variable costs. For a particular set of store products, retail analytics provides real-time information about those products on the competitor's website, along with matching prices.