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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... View Details
Keywords: Assortment Optimization; Retailing; Imperfect Information; Sales; Strategy; Consumer Behavior
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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... View Details
Keywords: Online Learning; Product Ranking; Assortment Optimization; Learning; Internet and the Web; Product Marketing; Consumer Behavior; E-commerce
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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... View Details
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
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  • 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; E-commerce; Retail Industry; Consumer Products Industry; United States
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  • July 2022
  • Supplement

Solution for E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer

By: Ayelet Israeli
Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Consumer Products Industry; United States
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  • July–August 2023
  • 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... View Details
Keywords: Experiments; Pricing And Revenue Management; Retailing; Demand Estimation; Pricing Algorithm; Marketing; Price; Demand and Consumers; Mathematical Methods
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  • October 2024
  • Article

Canary Categories

By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
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  • Research Summary

Overview

By: Kris Johnson Ferreira
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... View Details
Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry
  • 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... View Details
Keywords: High-dimensional Data; Demand Estimation; Consideration Sets; Consumer Search
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  • Research Summary

Current Research

 

I am interested in research on various topics in retail operations and supply chain management, including inventory management, product variety, distribution logistics, financial performance of retailers, and linking operational performance to... View Details

    Kris Johnson Ferreira

    Kris Ferreira is the Edgerley Family Associate Professor of Business Administration in the Technology and Operations Management (TOM) Unit. She teaches the Supply Chain Management course in the MBA elective curriculum and analytics in numerous Executive Education... View Details

    Keywords: retailing
    • 02 Oct 2018
    • First Look

    New Research and Ideas, October 2, 2018

    are robust to alternative model specifications and sample selection procedures. We demonstrate that an optimal pricing policy should take into consideration the potential costs of two types of strategic customer behavior: opportunistic... View Details
    Keywords: Dina Gerdeman
    • 22 Nov 2016
    • First Look

    November 22, 2016

    might affect retailer demand. We explore the drivers of this demand increase, including changes in retailer assortment and order frequency. We discuss features of a retail buyer’s decision context identified through our field work that... View Details
    Keywords: Sean Silverthorne
    • Web

    Winners & Runners-Up | New Venture Competition

    automatic cloud solution to workforce optimization and management. Qweek helps business achieve significant savings by breaking traditional rigid shift scheduling and using dynamic shifts to align workforce supply with demand. Ubiquitous... View Details
    • Web

    2022 Reunion Presentations - Alumni

    will look at an example—a company that is optimized to operate in a differentially turbulent environment and is thriving in part by virtue of its ability to handle elevated levels of risk. We will then consider other ideas about how firms... View Details
    • 25 Jun 2024
    • News

    On the Move: Alexis DePree (MBA 2007)

    When Nordstrom announced the promotion of Alexis DePree (MBA 2007) to COO in early June, media outlets noted DePree’s expanded, end-to-end role in managing operations and customer experience in an increasingly complex retail environment. DePree joined Nordstrom in... View Details
    Keywords: retail; customer service; supply chain management; career experience; Retail Trade
    • 01 Jun 2018
    • News

    Case Study: Tip the Scale

    be maintained. —Don Cottle (MBA 1961) Try establishing several serial assembly lines with small buffers in between. The buffer is an indicator of where more staff is needed. This optimization could be done according to Kanban principles.... View Details
    • 30 Jan 2018
    • First Look

    January 30, 2018

    Luck and Support for Classical Benefit-based Taxation By: Weinzierl, Matthew C. Abstract—U.S. survey respondents' views on distributive justice differ in two specific, related ways from what is conventionally assumed in modern optimal tax... View Details
    Keywords: Sean Silverthorne
    • 18 Sep 2018
    • First Look

    New Research and Ideas, September 18, 2018

    data, is computationally light and allows for flexible substitution patterns. We apply the model to a data set containing browsing and purchase information from a retailer stocking over 500 products, recover the elasticity matrix, and solve for View Details
    Keywords: Dina Gerdeman
    • 09 Jul 2024
    • Research & Ideas

    Chance Encounters: What's at Stake in Return-to-Office Decisions

    extent to which their work overlapped. If they could combine findings from across their assorted research projects, they could fit together a big-picture view of office-space configurations and how well they support different kinds of... View Details
    Keywords: by Jen McFarland Flint, HBS Alumni Bulletin