Designing the content of advertising in a differentiated market

David A. Soberman (First Author), Yi Xiang (Participant Author)

Research output: Contribution to journalJournal

1 Citation (Web of Science)

Abstract

In many markets, consumers use attribute information to assess the value they expect from purchasing a product or service. This includes many low involvement experience goods including take-out food, many packaged good categories and restaurants. In these markets, quality differences exist but many differences are horizontal in nature: the consumer is interested in finding a product that meets her unique tastes. Beyond ensuring that consumers know the brand, the category and the price; it seems advertising should provide consumers with attribute information. However, a significant proportion of advertising does not provide it. In fact, within the same category, competitors respond to messages that emphasize detailed attribute information with messages that are devoid of attribute information. These messages are uninformative about product attributes. We explore how competition in a differentiated market is affected by the ability of a firm has to choose uninformative messages. We construct a model to investigate the factors that affect a firm's decision to use advertising with detailed attribute information or advertising that does not provide it. The model demonstrates that content decisions about advertising are affected by the differences between products, the range of heterogeneity in consumer tastes and the degree to which costs increase as a function of the quantity of information in advertising. Surprisingly, even when the cost to increase the quantity of information in advertising is low, uninformative campaigns can be more profitable than campaigns with attribute information. The analysis also demonstrates that firms can be more likely to provide attribute information when there are less consumers that are attribute-sensitive. Finally, the model shows that uninformative messages can create "artificial differentiation" in some situations. (c) 2021 The Author(s).
Original languageEnglish
Pages (from-to)190-211
Number of pages22
JournalInternational Journal of Research in Marketing
Volume39
Issue number1
DOIs
Publication statusPublished - Mar 2022

Corresponding author email

yixiang@ceibs.edu

Keywords

  • Uninformative messages
  • Advertising content
  • Horizontal differentiation
  • Matching

Indexed by

  • SSCI
  • Scopus
  • ABDC-A*

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