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Prelert Machine Learning Analytics Detects Incidents And Trends In Real Time

Prelert Machine Learning Analytics Detects Incidents And Trends In Real Time

With retailers facing difficulties monitoring high volumes of data and identifying trends in real time, Prelert launched the Retail Order Analytics solution, which focuses on providing merchants with machine learning behavioral analytics capabilities.

The solution is designed to assist digital and multichannel retailers in identifying technical and operational issues in real time in order to stem losses and protect revenue streams. Retailers can apply the solution to analyze real-time transaction metrics such as:

  • Orders per minute;

  • Carts created per minute;

  • Invoices per hour; and

  • Deposits per hour, so that revenue-impacting events can be found and fixed quickly.

 

With this data in hand, retailers can more easily identify issues such as the number of abandoned carts, the number of completed checkouts, or even an invoice brown-out, so that the root cause can be addressed in near real-time.

The machine learning algorithm adapts to changing data patterns that may result from seasonality or other factors, such as a new product becoming available or current events that cause a spike in product interest.

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