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Machine learning can give D2C brands the edge

CEO Tom Cijffers letter on how machine learning can give D2C brands the edge

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This Article originally appeared here in The Grocer.

 

There’s more competition in the D2C arena than ever – the easy ideas are done, the big boys have muscled in, and tech and distribution barriers have largely vanished. It’s open season. As a result, customer acquisition is more expensive and, as D2C brands grow, their pool of obvious target customers gets smaller. Most chocolate lovers already know Hotel Chocolat.

That’s why advanced segmentation, driven by machine learning, is integral for D2C success – especially for startups. With no human bias, this approach can analyse data sets and find potential customers, their browsing habits and purchase triggers. This can be as simple or as complex as you like – you can build from multiple data sets (social, analytics, reviews, returns), or just out of an analytics platform. This can deliver rich, game-changing information from areas you’d likely miss using traditional, human-led techniques. It unlocks groups of otherwise overlooked potential customers, which are vital for D2C brands vying for pole position.

Tom Cijffers, CEO UK, Artefact