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Research Provides New Way to Fill-in Data Gaps to Drive Penetration for Foodservice Distributors
Dr. Wang's talk, “Learning from Only Positive and Unlabeled Data Using Generalized Stochastic Model," solves the business challenge of predicting whether a customer needs certain items that they have not purchased with limited data available.
Since many customers in the foodservice industry are served by multiple distributors and vendors, when working with any one distributor only information about what customers are purchasing from that distributor is available. In order to identify which items are good choices to issue coupons to induce existing customers to purchase new items, Dr. Wang developed a method to predict what items the customers purchase from other vendors. Dr. Wang’s work extended the stochastic frontier model to address classification with only positive and unlabeled data. Within the data, it is clear that a customer needs specific items (a positive label) if they purchased the items before. However, if they haven’t purchased the product from the distributor then there are two possibilities:
“Even in a world that has more and more data available every day, there are limitations to the amount of data that is accessible to solve any one problem. This recent development in modeling enables us to fill-in the crucial information needed by our clients to extend their business,” said Dr. Wang. “Without this sophisticated analysis, our clients would only be able to guess at new items their customers need and waste time and money with blanket penetration attempts. We are able to greatly increase their penetration success using this method of extending the stochastic frontier model to non-Gaussian data.”
This new method is optimal for addressing situations with limited data and can be applied to similar challenges in any distribution or vendor centered industry.
To learn more, please download Dr. Wang’s presentation here: http://sentrana.com/
About the Joint Statistical Meetings
The Joint Statistical Meetings (JSM) are the largest gathering of statisticians held in North America. These meetings provide an opportunity for more than 5000 leading scientists, researchers, and interested individuals to come together for a comprehensive program that address the application of statistics to various real-world problems. The JSM is held jointly with the American Statistical Association, the International Biometric Society (ENAR and WNAR), the Institute of Mathematical Statistics, the Statistical Society of Canada, the International Chinese Statistical Association, and the International Indian Statistical Association. Attended by over 5000 people, the meetings include oral presentations, panel sessions, poster presentations, continuing education courses, exhibit hall, career placement service, society and section business meetings, committee meetings, social activities, and networking opportunities.
Sentrana is a scientific marketing company. We help our clients make more informed and accurate decisions about product assortment, promotions & advertising, pricing, and sales force alignment with the data and capabilities they already possess. Our holistic demand optimization solutions integrate advanced predictive technology with the qualitative insights derived from human knowledge and experience. Sentrana’