How can companies build consumer-centric, future-proof and innovative business models in the age of AI? And how can they do so as they scale across markets and channels while making sustainability a genuine source of customer value? 

These were just some of the questions posed at a recent INSEAD webinar hosted by Joerg Niessing, Senior Affiliate Professor of Marketing at INSEAD. He was joined by Tina Scheele (MBA’02J), customer strategy expert and former partner at consulting firm Monitor Deloitte, and Martin Murray (MBA’15D), founder and CEO of global hydration company waterdrop.

The business of hydration 

Niessing began by introducing waterdrop, an Austrian startup founded in 2017. Rather than shipping heavy bottles of flavoured drinks in single-use plastics around the world, it created compact, sugar-free cubes enriched with fruit and plant extracts that consumers can simply add to water. 

By bucking convention, waterdrop grew into a €126 million business spanning e-commerce, experience stores, retail partners and marketplaces. The company was able to move away from the supply-chain- and shelf-space-driven business model that dominates the beverage industry, slashing not just logistics costs but also carbon emissions and plastic waste. 

And thanks to its direct-to-consumer approach, waterdrop has forged millions of customer relationships, using the data it’s collected for personalisation, prediction and product development. “The core asset is… the data flywheel,” revealed Niessing, referring to the feedback loop where data collected from customer processes is used to continuously refine AI models. “The data creates better models. The better models yield better products [and] experiences, which yields higher loyalty, which… creates more customers [and] gives you more data.” 

The role of digital and AI tools 

Speaking of the importance of meeting consumer preferences and delivering value, Scheele said digital and AI tools can help by “[compressing the] innovation timeline from years and month towards weeks”. A few big brands, she noted, are already using these technologies to speed up testing recipe formulations and to engineer virtual shopping experiences. 

“It’s not enough if the typical customer likes the product… you really need to get granular when it comes to which customer segments and on which occasions these products are being used and sold, because then you can actually adapt your proposition and marketing towards it,” said Scheele. 

How AI can help 

Niessing then steered the conversation towards sustainability and how AI can help customers make more sustainable choices. The first area Scheele identified is transparency. AI allows companies to fully track aspects such as their carbon footprint, impact on biodiversity and amount of plastic saved, which they can then disclose to consumers through their sales and marketing approach. The second area she called out is platforms: think AI-driven apps for second-hand clothing or produce that’s about to reach its sell-by date. 

For companies looking to leverage AI and data holistically throughout the organisation, as waterdrop has done, Murray stressed that it’s critical to distinguish between noise and signal. “There’s a lot of noise in AI because everybody’s doing [it],” he said. “But what actually moves the needle?”