Leading international researchers and practitioners present new perspectives on AI and advanced analytics in retail.
In the near future, there will be a shift from person-centric decision-making to more data-centric and automated decision-making. Predictive and prescriptive analytics, including AI, play a key role in this shift. To realize the potential of AI for retail, we need to know how these technologies are going to impact the converging worlds of online and offline.
This webinar gives you a glimpse into where the retailing field will be evolving in the near future. First to present is Eleanora Pantano, University of Bristol, who discusses how prescriptive AI systems can be used to systematically provide consumers purchase based on characteristics and historical purchases (i.e., subscriptions to food, beauty, etc.) and to replace consumers’ traditional shopping. Cameron Tayor from Boost.ai describes their strategy for using evaluative methods to better understand how people interact and engage through and with AI-powered virtual agents. Arno de Caigny - IÉSEG School of Management presents his research, which shows that a deep convolutional neural network using structured customer data and unstructured textual data achieves best predictive performance in financial services retail. Finally, Yulia Vakulenko describes research that applies text mining techniques to capture customer experience. The research take a closer look at online star ratings and associated reviews as a proxy for customer satisfaction and a reflection of consumer experience.
You can watch the recorded webinar on our website.
Slides from the presentations are also available to download as pdfs:
- Eleonora Pantano's slides on Using AI to predict consumer demand
- Cameron Taylor's slides on User experience of AI-powered chatbots
- Arno De Caigny's slide on Leveraging textual data for customer life event prediction
- Yulia Vakulenko's slides on Navigating by the stars