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- Faculty Publications (7)
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- March 2022
- Article
Learning to Rank an Assortment of Products
By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...
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- March 2021
- Article
Assortment Rotation and the Value of Concealment
By: Kris J. Ferreira and Joel Goh
Assortment rotation—the retailing practice of changing the assortment of products offered to customers—has recently been used as a competitive advantage for both brick-and-mortar and online retailers. We focus on product categories where consumers may purchase multiple...
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- January 2021
- Supplement
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
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Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Online Channel;
Retail;
Retail Analytics;
Retailing Industry;
Data;
Data Sharing;
Ecommerce;
Assortment Optimization;
Assortment Planning;
Analytics and Data Science;
Retention;
Retail Industry;
Consumer Products Industry;
United States
- January 2021
- Exercise
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Online Channel;
Retail Analytics;
Retail;
Retailing Industry;
Data;
Data Sharing;
Ecommerce;
CRM;
Loyalty Management;
Assortment Planning;
Assortment Optimization;
Lifetime Value (LTV);
Analytics and Data Science;
Analysis;
Retention;
Retail Industry;
Consumer Products Industry;
United States
- 2019
- Working Paper
Large-Scale Demand Estimation with Search Data
By: Tomomichi Amano, Andrew Rhodes and Stephan Seiler
In many online markets, traditional methods of demand estimation are difficult to implement because assortments are very large and individual products are sold infrequently. At the same time, data on consumer search (i.e., browsing) behavior are often available and are...
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- Forthcoming
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to...
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- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the...
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