NextOrbit: Out-of-Stock Alerts for Enhanced Customer Experience

The recent surge of technological advancements in the retail industry has given rise to a multitude of opportunities for carrying out up-to-the-minute services. Perhaps the retail industry is witnessing the best of times; however, there is still trouble in paradise. A consistent nine percent incidence of Out-of-Stock (OOS) condition in the retail stores is leading to a direct sales loss of nine percent for the retailers. Aware of the fact, Kishore Rajgopal, Founder and CEO, NextOrbit elaborates, “The Retail and Consumer Product (CP) companies are all about creating ‘moments of truth’— the moments when customer makes a choice to buy the product.” The retailer needs to capitalize on those ‘moments of truth’ by ensuring the availability of product or be prepared to hear customer experience concerns. “For example, customers are quite specific when it comes to HABA – Health Care and Beauty Aids. If their brand and color is out of stock, they will either delay the purchase or go to another store,” enunciates Mayank Shende, Co-Founder and Data-Scientist, NextOrbit. Helping alleviate such critical issues, Frisco, TX, based NextOrbit provides a cloud plat¬form that offers insights to predict and mitigate out-of-stock events in the retail business. The ability of the platform to perform fine grain OOS prediction allows the retailers to cater to more customers and hence reduce walkouts. This resultantly leads to enhanced customer experience and higher profits.

The NextOrbit platform generates out-of-stock alerts and prescriptive store orders by leveraging the power of Cloud, Big data, and Prescriptive Data Sciences. The alerts and orders are produced by the clues obtained from retail and external data. The retail data includes information such as point of sale, store deliveries, store orders and promotions. The collected data is then combined with external data such as weather, calendar events, income levels and social media indicators to enhance the accuracy of predictions. The resultant analytics are utilized to produce on-demand, daily and weekly predictions of SKUs (Stock Keeping Unit).