Abstract
Loyalty cards are a form of tracking and recording technology (TRT) that enables retailers to collect data about their customers' demographic and purchase behaviours. As recompense for sharing their data consumers receive 'loyalty points' which they can redeem for exclusive discounts and rewards. The design of loyalty schemes, and TRTs more generally, plays a key role in defining the economic terms of that exchange, and ultimately the economic value of personal data. In this paper we present findings from an interview study with 12 loyalty cardholders in the UK explicating the ways in which they create (and lose) value through the everyday practice of shopping with loyalty cards and the orientations associated with them. Based on our findings we suggest cardholders are less concerned with the protection of their privacy than with leveraging its value, only some of which was economic. We provide design guidelines for TRTs that may enable consumers to derive greater value from the data they produce and share.
| Original language | English |
|---|---|
| Title of host publication | CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery, Inc. |
| Pages | 4443-4453 |
| Number of pages | 11 |
| ISBN (Print) | 978-1-4503-4655-9 |
| DOIs | |
| Publication status | Published - 2 May 2017 |
| Event | 35th Annual ACM Conference on Human Factors in Computing Systems, CHI 2017 - Colorado Convention Center, Denver, United States Duration: 6 May 2017 → 11 May 2017 Conference number: 35 https://chi2017.acm.org/ http://www.scopus.com/inward/record.url?scp=85019570374&partnerID=8YFLogxK (Link to publication in Scopus) |
Conference
| Conference | 35th Annual ACM Conference on Human Factors in Computing Systems, CHI 2017 |
|---|---|
| Abbreviated title | CHI 2017 |
| Country/Territory | United States |
| City | Denver |
| Period | 6/05/17 → 11/05/17 |
| Internet address |
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Keywords
- Digital economy
- Interview study
- Loyalty cards
- Personal data
- Retail shopping
- Tracking and recording technologies
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