Consumer Trust and Platformised Retail Personalisation

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As retail is becoming increasingly digitised in its operation and consumer relationships, much faith is put into automation, prediction and insights drawn from consumer data to shape consumer experiences and expectations. Under the umbrella of data-collection and artificial intelligence (AI), this chapter studies the role of consumer trust in retail personalisation. We draw empirical insights from focus-group interviews conducted with Swedish consumers regarding three main aspects: (1) consumer sentiment on data collection; (2) data-dependent retail personalisation; and (3) the digitised market logic that follows from platformisation. Firstly, the results indicate that the level of trust that consumers have in general for data collection is of relevance for how successful retailers use of recommendations systems and targeted ads will be. Secondly, and echoing earlier studies, the user agreements and privacy notices are something that most interviewees find hard to comprehend and pay attention to. And thirdly, data collection, automation and personalisation is often third-party dependent and platformised. To consumers, this adds to a lack of transparency and a sense of lost control over data, which should be taken as a call to action for retailers to be more attentive to consumer trust and to avoid third-party sharing to the extent possible.
Original languageEnglish
Title of host publicationThe Future of Consumption
Subtitle of host publicationHow Technology, Sustainability and Wellbeing will Transform Retail and Customer Experience
EditorsKristina Bäckström, Carys Egan-Wyer, Emma Samsioe
PublisherPalgrave Macmillan
Number of pages18
ISBN (Electronic)978-3-031-33246-3
ISBN (Print)978-3-031-33245-6
Publication statusPublished - 2023 Oct 9

Subject classification (UKÄ)

  • Law and Society
  • Social Sciences Interdisciplinary
  • Media and Communications

Free keywords

  • platformisation
  • consumer personalisation
  • data-collection
  • retail personalisation
  • consumer sentiment
  • consumer trust
  • artificial intelligence
  • data-dependent retail personalisation
  • privacy
  • third-party collection
  • transparency


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