Sales Policies for a Virtual Assistant

38 Pages Posted: 15 Dec 2020

See all articles by Wenjia Ba

Wenjia Ba

University of British Columbia (UBC) - Sauder School of Business

Haim Mendelson

Stanford University - Stanford Graduate School of Business

Mingxi Zhu

Stanford Graduate School of Business

Date Written: October 23, 2020

Abstract

We study the implications of selling through a voice-based virtual assistant (VA). The seller has a set of products available and the VA decides which product to offer and at what price, seeking to maximize its revenue, consumer- or total-surplus. The consumer is impatient and rational, seeking to maximize her expected utility given the information available to her. The VA selects products based on the consumer’s request and other information available to it and then presents them sequentially. Once a product is presented and priced, the consumer evaluates it and decides whether to make a purchase. The consumer’s valuation of each product comprises a pre-evaluation value, which is common knowledge, and a post-evaluation component which is private to the consumer. We solve for the equilibria and develop efficient algorithms for implementing the solution. We examine the effects of information asymmetry on the outcomes and study how incentive misalignment depends on the distribution of private valuations. We find that monotone rankings are optimal in the cases of a highly patient or impatient consumer and provide a good approximation for other levels of patience. The relationship between products’ expected valuations and prices depends on the consumer’s patience level and is monotone increasing (decreasing) when the consumer is highly impatient (patient). Also, the seller’s share of total surplus decreases in the amount of private information. We compare the VA to a traditional web interface, where multiple products are presented simultaneously on each page. We find that within a page, the higher-value products are priced lower than the lower-value products when the private valuations are exponentially distributed. Finally, the web-interface generally achieves a higher profit share for the seller due to the postponement option available to the consumer with the VA.

Keywords: Virtual Assistant, product ranking, pricing, electronic commerce, voice commerce

JEL Classification: L81, L86, D4

Suggested Citation

Ba, Wenjia and Mendelson, Haim and Zhu, Mingxi, Sales Policies for a Virtual Assistant (October 23, 2020). Available at SSRN: https://ssrn.com/abstract=3718080 or http://dx.doi.org/10.2139/ssrn.3718080

Wenjia Ba

University of British Columbia (UBC) - Sauder School of Business ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada

HOME PAGE: http://https://wenjiaba.github.io

Haim Mendelson (Contact Author)

Stanford University - Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States
650-725-8927 (Phone)
650-725-7979 (Fax)

HOME PAGE: http://https://www.gsb.stanford.edu/faculty-research/faculty/haim-mendelson

Mingxi Zhu

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, 94305
United States

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