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Learning from the Dark Web: leveraging conversational agents in the era of hyper-privacy to enhance marketing
Open accessAbstract
The Web is a constantly evolving, complex system, with important implications for both marketers and consumers. In this paper, we contend that over the next five to ten years society will see a shift in the nature of the Web, as consumers, firms and regulators become increasingly concerned about privacy. In particular, we predict that, as a result of this privacy-focus, various information sharing and protection practices currently found on the Dark Web will be increasingly adapted in the overall Web, and in the process, firms will lose much of their ability to fuel a modern marketing machinery that relies on abundant, rich, and timely consumer data. In this type of controlled information-sharing environment, we foresee the emersion of two distinct types of consumers: (1) those generally willing to share their information with marketers (Buffs), and (2) those who generally deny access to their personal information (Ghosts). We argue that one way marketers can navigate this new environment is by effectively designing and deploying conversational agents (CAs), often referred to as “chatbots.” In particular, we propose that CAs may be used to understand and engage both types of consumers, while providing personalization, and serving both as a form of differentiation and as an important strategic asset for the firm—one capable of eliciting self-disclosure of otherwise private consumer information.
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“Thomaz et al. (2020) identify two types of consumers who vary in willingness to share information.”
From A strategic framework for artificial intelligence in marketing (2021) · cites this paper as Thomaz et al. (2020)
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“There are a variety of bots, including conversational agents (chatbots) that help to market products (Thomaz et al., 2020), decision-making bots that manage organizational activity (Kellogg et al., 2020), and online bots that disseminate information (Salge et al., 2022).”
So, I. G., Haron, H. B., Gui, A., Princes, E., & Sari, S. A. (2021) · Sustainability · doi:10.3390/su132313023 · Cited by 26
Hey, Alexa! What attributes of Skills affect firm value?
Bahmani, N., Bhatnagar, A., & Gauri, D. K. (2022) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-022-00851-0 · Cited by 26
“Privacy concerns Consumers, firms, and regulators have become increasingly concerned about privacy and the ways in which online data are handled (Thomaz et al., 2019).”
BackgroundImpact of cultural tightness on consumers' preference for anthropomorphic AI services
Sui, J., Shen, H., & Zhou, X. (2024) · Psychology and Marketing · doi:10.1002/mar.22086 · Cited by 25
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The Impact of Chatbots on Customer Satisfaction: A Systematic Literature Review
Vergaray, A. D., Robles, W. F. P., & Jiménez, J. D. C. R. (2023) · TEM Journal · doi:10.18421/tem123-21 · Cited by 33
“Thus, when customer satisfaction is related to the use of the “Chatbot”, it has positive points of view, being present 2 hours a day, every day, as well as the comfort that people feel when using it [7], [8], and reducing costs for brands [9].”
BackgroundIsrafilzade, K. (2021) · JOURNAL OF LIFE ECONOMICS · doi:10.15637/jlecon.8.4.12 · Cited by 23
Carmichael, L., Poirier, S., Coursaris, C. K., Léger, P., & Sénécal, S. (2022) · Applied Sciences · doi:10.3390/app122412660 · Cited by 26
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The role of marketing analytics in the ethical consumption of online consumers
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Chatbot recommender systems in tourism: A systematic review and a benefit-cost analysis
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“These individuals may be concerned about the safety and security of their personal information, as they are aware that these technologies can store and use the data they provide [45].”
BackgroundResponsible Artificial Intelligence Attention and Firm Innovation: An Attention‐Based View
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“2015 [ 4 ] 2016 [ 214 ] 2017 [ 212 ] 2018 [ 10 , 187 ] 2019 [ 213 ] 2020 [ 72 ] Figure 14.”
BackgroundAn Exploration of Personalization in Digital Communication. Insights in Fashion
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“This will ultimately strengthen the awareness of both brand privacy security and privacy protection (Thomaz et al., 2020).”
RetractedElevating Business Experiences
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“Of these, security is one of the most important dimensions, since the consumer may be reluctant to provide personal information when using a digital service [32].”
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“Firms widely use chatbots across various functions and contexts, including marketing (Thomaz et al., 2020), sales (Gartner, 2018; Luo et al., 2019 ), finance (Luo et al., 2019), health care (Health Europa, 2019), and education (Tourangeau et al., 2003).”
Choi, S. (2025) · Journal of Consumer Behaviour · doi:10.1002/cb.2505 · Cited by 18
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“Conversational agents are one common way that artificial intelligence is used in marketing [8].”
BackgroundShort-term and long-term effects of touchpoints on customer perceptions
Cambra‐Fierro, J., Polo‐Redondo, Y., & Trifu, A. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102520 · Cited by 18
Digital Transformation and Resilience
Abidi, O., Richet, J., & Vitari, C. (2025) · Journal of Global Information Management · doi:10.4018/jgim.367873 · Cited by 16
Exploring the frontier of anthropomorphism in AI agents: Trends and way forward
Chaturvedi, R., Verma, S., Srivastava, V., & Khot, S. S. (2025) · Business and Society Review · doi:10.1111/basr.70002 · Cited by 19
The State of Artificial Intelligence in Marketing With Directions for Future Research
Chen, J., Rosas, J. H. A., Frankwick, G. L., & Arévalo, F. R. J. (2022) · International Journal of Business Intelligence Research · doi:10.4018/ijbir.297062 · Cited by 16
Human Resources Management After Industry 4.0
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Metadata
- Authors
- Thomaz, F., Salge, C., Karahanna, E., & Hulland, J.
- Affiliations
- University of Oxford (GB)
- Wake Forest University (US)
- University of Georgia (US)
- Corresponding author
- Thomaz, Felipe
- Venue
- Journal of the Academy of Marketing Science
- Published
- 2019-11-11
- Volume
- 48
- Issue
- 1
- Pages
- 43-63
- ISSN
- 0092-0703 (ISSN-L)
- 1552-7824
- OpenAlex
- W2986577019
- Cited by
- 204
- References
- 131
- Citations by year
- 2026: 25 · 2025: 30 · 2024: 38 · 2023: 38 · 2022: 36 · 2021: 23 · 2020: 13 · 2019: 1
- FWCI
- 8.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of the Academy of Marketing Science (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- University of Oxford
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Keywords
- dark web, chatbots, consumer privacy, customer data, self-disclosure, personalization, customer segmentation, marketing strategy, information sharing
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