Because machine learning can detect individual patterns by comparing these against a database of customer journeys. This means a typical marketer’s segmentation is useful in some cases but the likelihood it will be less relevant for the individual is higher.
Today’s marketers tend to focus on how they optimise campaigns and the ROI of these. They are mainly driven by events; Christmas, Black Friday and others. Or they are led by products; new collections, sale, promotions and the like. But as marketing resources are finite, AI is able to augment efforts by optimising the individual journey or the “long-tail”. However, optimising the long tail requires a different skillset. Instead, marketers and organisations on a whole need to work with algorithms and data analytics in order to consider and appeal to the individual. This needs a whole new set of skills and a fresh mindset.
These days, brands must have two different strategies and competencies, one for short-tail queries, where the mass of searches occur. These are generalist, short search queries that can have a curated product offering, with some degree of personalisation and automation. Versus the long-tail. This involves much more sophisticated searches and therefore varied offerings. Relevance, context and shopper intent must be understood and catered for directly.