Business Intelligence for Retail

Power your offering with data driven insights for superior customer satisfaction

Analytics for retail industry

What does this data spell out for retailers?

Shoppers have digital touch points – online, social, mobile and stores, and all this information can be brought together to build business insights.

Systematic and data built customer profiles help customers find the products they want quicker than ever before, and in many cases the items find them even earlier.

Omni-channel digital retail strategies

The New Generation Of Embedded BI Will Close The Insights-To-Action Gap – Forrester Research

At every stage of retail, you can unearth copious amounts of structured and unstructured data about customer behavior and interests. Predicting trends, forecasting demand, identifying interests and giving them an exemplary shopping experience is all within reach when you bring in analytics and insights.

Big Data analytics process

Being in-sync with the customer and forecasting demand not necessarily related to customer retail inputs alone. Economic indicators, demographic data, in-store purchases etc. will all contribute to better demand management.

IoT retail forecasting

Social buzz and sentiments drives sales to a great extent. Trend predicting algorithms comb social and web browsing history to determine context, analyze top selling products and accurately predict the season’s best for tomorrow.

Social buying, online retail analytics

Predictive approach to the rise and fall of product demand can help in an accurate pricing strategy. The best play in price reduction to boost demand and increase revenues can be zeroed in through algorithmic tracking of demand, competitor activity and real-time price updates.

Barcode, shopping optimization