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Let's go Retail: Data Science and How it Helps in Retail 

The exploitation of the ever increasing mass of information generated by retail organizations requires not only powerful information systems, but robust and scalable analytical engines to identify trends and patterns, opportunity and threats, forecast future performance, streamline operations and optimize decisions.


The development of analytics solutions for the retail industry is a specialist area. Retail-Analytics is seen to have a pivotal role in transforming retail companies into successful information management organizations. 

Retail Analytics has built a comprehensive series of sophisticated modeling and optimization tools to provide analytical support to essential business functions. Analytics allows retailer organizations to get the most out of their existing management information systems and information sources without the risk of committing to significant investments; assist retailers to focus on characteristics of the marketing activities that increase the probability of better returns, making more effective decisions leading to:

Purchase acceleration

Brand switching

Volume increases

Basket effects

Store choice




Retailers turn to SAS because SAS drives better results. SAS has retail business knowledge built in, is easy to use and provides unparalleled analytics to drive the best financial results. SAS retail solutions can grow with you at your desired pace using flexible deployment models. With SAS' retail business expertise, spanning more than 30 years, retailers choose SAS for customer insight, localized assortment optimization, size profiling and pack optimization, price optimization, merchandise planning and advanced analytics.

SAS provides software and services across all retail market segments, including apparel, fashion, grocery, specialty retail, general merchandise, online and hardlines retail.


We help in building capability around:

Demand Forecasting

Price/Promotion Modeling

Markdown Modeling

Price And Promotion Optimization

Promotional Effectiveness Benchmarking

Dynamic Market Basket Analysis

Consumers Behaviour Analysis

Customers Segmentation