The global retail analytics market is expected to grow at a significant rate during the forecast period. The market growth is attributed to the increasing e-commerce industry, rapid and consecutive increase in big data, and increasing penetration of social media which has made shopping easy for the customers. Most of the retailers are leveraging several social media platforms such as Facebook to better understand the needs, brand perception, loyalty and feedback of the customers.

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The main function of Big data analytics in the Retail industry include

Price Optimization
Less Expensive Business Development
Future Performance Prediction
Demand Prediction
Select Better ROI Opportunities
Trend Forecast
Customer Identification

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Big data analytics in retail help companies in creating customer recommendationson the basis of their purchase history, which, in turn, results in personalized shopping experiences. For instance, Amazon used big data analytics for recommending items for the customers on the basis of their past searches and purchases. They generated 29% of their sales through their recommendation engine in 2018, which analyzesover 150 million accounts. This has led to big profits for the e-commerce giant, and hence increased the adoption of analytics solutions in the retail industry; thereby, surge the growth of the retail analytics market.

Further, big data analytics in the retail industry offers personalized customer experience. The advent of data offers a huge opportunity for the growth of the global retail analytics market by providing better customer experiences. For instance, Costco Wholesale Corp. uses its data collection tokeep customers healthy. When a California fruit packing company in 2014 warned Costco about the possibility of listeria contamination in fruits such as peaches and plums, Costco sent an email to specific customers who had purchased the items affected by the contamination instead of a blanket email to their lists.

Another application of retail analytics includes forecasting demand in retail. Apart from big data, there are some algorithms that analyzesocial media and web browsing trends for predicting predict the next big thing in the retail industry. One of the most interesting data points for forecasting demand is the weather.Brands such as Walgreens and Pantene worked with the Weather Channel for accounting for weather patterns for customizing the product recommendations for thecustomers.

Walgreens and Pantene anticipated increases in humidity–a time when women would be seeking anti-frizz products–and served up ads and in-store promotions to drive sales. With this, Walgreens witnessed an increase in the purchase of Pantene products. Such applications of big data analytics in the retail industry increase its adoption and hence drive the growth of the global retail analytics market.

Global Retail Analytics Market Segmentation

By Deployment Model

Cloud-Based
On-Premises

By Application

Merchandising Analysis
Customer Management
Pricing Analysis
Performance Analysis
Inventory Analysis
Yield Analysis
Supply Chain Management

Global Retail AnalyticsMarket Segment by Region

North America

US
Canada

Europe

Germany
UK
France
Spain
Italy
Rest of Europe

Asia-Pacific

China
Japan
India
Rest of Asia-Pacific

Rest of the World

Latin America
Middle East and Africa

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