According to a new market research report, “Retail Analytics Market – Global Forecast and Analysis to 2020“, published by MarketsandMarkets, The Retail Analytics Market size is estimated to grow from USD 2.2 Billion in 2015 to USD 5.1 Billion by 2020, at an estimated Compound Annual Growth Rate (CAGR) of 18.9% from 2015 to 2020.
Merchandising and in-store analytics solutions are expected to gain maximum traction
Retail analytics solutions help retailers gain useful insights that can help them in making decisions from offers to the on-to-consumers to displaying the right product at right place at the shelf. These analytical solutions collect data from several data sources, integrate it, and further present it in a structured format, which enhances the data visibility and analytical capabilities. The Retail Analytics Market is expected to gain traction in the next five years due to growth in digital data.
Silverstar Analytics: Our powerful data analytics combined with the most extensive array of supported devices. Bring all your electronic events into one system. Turn data into decisions.
Big data insights with advanced analytics
Allow our powerful data analytics to quickly locate suspicious, abnormal or out of policy transactions within your establishment. Automatically baselines normal behavior patterns. Find outliers and differences from known good activity patterns. Take your data from efficient hindsight to rapid insight. Understand trends and become predictive. Use our automated anomaly detection to find activity worthy of investigation.
Automatically baselines behavior patterns
Automatically baseline activity on a shop, operator or till basis. Understand what is ‘normal’ behavior and compare to other groups providing a valuable insight to current activities. Variations across similar groups can be investigated, locating pockets of best-in-class or worst-in-class behavior.
Identifies and scores anomalies
Allow our analytics to locate and score anomalies. The scoring provides a ‘stack-ranked’ list of transactions or events worthy of investigation. Each highlighted item will have attributes that cause it to deviates from what is standard, normal, or expected within your environment
Outliers to normal employee activity
Our analytics automatically defines normal behavior within your environment. Outliers with significant anomalous attributes will be highlighted to you, for further investigation. Transactions which are widely separated from the main cluster of normal activity will be highlighted and a score provided to indicate the amount of deviation.