Cited by 244Digital Marketing and Social MediaMarketing and Advertising StrategiesConsumer Market Behavior and Pricing

Personalization in Email Marketing: The Role of Noninformative Advertising Content

Sahni, Navdeep S., Wheeler, S. Christian, Chintagunta, Pradeep·2018·Marketing Science

Abstract

In collaboration with three companies selling a diverse set of products, we conducted randomized field experiments in which experimentally tailored email ads were sent to millions of individuals. We found consistently that personalizing the emails by adding consumer-specific information (e.g., recipient’s name) benefited the advertisers. Importantly, such content is not likely to be informative about the advertised product or the company. In our main experiment, we found that adding the name of the message recipient to the email’s subject line increased the probability of the recipient opening it by 20% (from 9.05% to 10.80%), which translated to an increase in sales’ leads by 31% (from 0.39% to 0.51%) and a reduction in the number of individuals unsubscribing from the email campaign by 17% (from 1.2% to 1.0%). We present similar experiments conducted with other companies, which show that the effects we document extend from objectives ranging from acquiring new customers to retaining customers who have purchased from the company in the past. Our investigation of several possible mechanisms suggests that such content increases the effort consumers make in processing the other content in the rest of the advertising message. Our paper quantifies the benefits from personalization and sheds light on the role of noninformative advertising content by analyzing several detailed measures of recipient’s interaction with the message. It provides external validity to psychological mechanisms and has clear implications for the firms that are designing their advertising campaigns. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1066 .

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Crossref · 10.1287/mksc.2017.1066

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Cites

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Research works printed but not linked: 6

  1. Allport GW, 1937, Personality
  2. Perloff RM, 1980, Persuasion: New Directions in Theory and Research, 67
  3. Petty RE, 2009, Emerging Theories in Health Promotion Practice and Research, 185
  4. Petty RE, 2000, Why We Evaluate: Functions of Attitudes, 133
  5. Petty RE, 2013, Comprehensive Handbook of Psychology, 5, 369
  6. Wegener DT, 1995, Attitude Strength: Antecedents Consequences, 4, 455

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Authors
Sahni, N. S., Wheeler, S. C., & Chintagunta, P.
Affiliations
  • Stanford University (US)
  • University of Chicago (US)
Venue
Marketing Science
Published
2018-03
Volume
37
Issue
2
Pages
236-258
ISSN
  • 0732-2399 (ISSN-L)
  • 1526-548X
OpenAlex
W2788138901
Cited by
244
References
46
Citations by year
2026: 20 · 2025: 38 · 2024: 28 · 2023: 44 · 2022: 43 · 2021: 21 · 2020: 22 · 2019: 16 · 2018: 11 · 2016: 1
FWCI
39.87
Type
journal article
Language
en
Open access
closed
Locations
  • Marketing Science (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
Keywords
email marketing, personalization, email open rates, sales leads, customer retention, customer acquisition, advertising campaign design

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