Channels have traditionally been viewed as intermediaries that facilitate the transfer of products from manufacturers to consumers. Innovations in digital technologies help firms to integrate the customer experience across channels and devices. This new phenomenon is referred to as “omnichannel marketing.” Existing research on omnichannel marketing has emphasized that this means that firms need to integrate and optimize across channels rather than within channels. In this paper, we argue that questions of data integrity are now at the forefront of the challenges that firms face embarking on omnichannel marketing strategy. The emergence of digital platforms, AI-powered assistants, and mobile devices have led to even more voluminous and diverse data, beyond simple binary formats, being created about consumers. However, we argue that tracking consumers across so many different devices and touchpoints is problematic, especially when the firm does not control that channel. We discuss two technologies that firms are using to address these challenges of data-tracking: Machine Learning and Blockchain. Firms now need to use machine learning to attempt to track consumers across different touchpoints and predict their response to marketing actions. Firms can also use a variety of blockchain technologies to better ensure data is tracked in a robust way across different devices. Last, we highlight that the need for individual-level tracking implied by omnichannel marketing and the technologies deployed to address this need are often in tension with consumer privacy, and that firms need to recognize the tradeoffs between optimizing omnichannel marketing strategies and consumer privacy.
Note: Research papers posted on SSRN, including any findings, may differ from the final version chosen for publication in academic journals.