How AI can move customer personalisation to customer contextualisation

Abstract

Reaching beyond personalisation to achieve contextualisation is the holy grail for brands and retailers — a challenge that countless businesses hope to crack by applying emerging artificial intelligence (AI) technologies. International business leaders are increasing their investments in technology and data analytics to drive performance. This includes building out marketing teams with data scientists and acquiring tech start-ups to transform their businesses’ capabilities to more accurately predict customer needs and wants. McDonald’s US$300m acquisition of AI start-up Dynamic Yield is a clear example, described as fuelling the business’s vision to create more personalised customer experiences. In the race to tailor communications and customise recommendations, however, few businesses can deliver contextualisation — the ability to understand what a customer wants, immediately, at a particular moment in time. Advances in voice interfaces and consumer use of personal assistants only accentuate the need for greater sophistication in analysing situational context. This paper shares a view of the emerging AI-fuelled voice and virtual assistant ecosystem, how businesses can drive demonstrable value by solving the contextualisation challenge, and how new low-code development practices can accelerate and democratise these coming technological advances.