According to IBM, 90% of the data that exists today has been created in the last two years. The spread of digital media – and social media in particular – means that consumer trends and fashions can spread more rapidly and more widely than ever before. Brands have to identify and make use of them before consumers move on, but the vast quantity of data available makes this a resource-intensive task.
Machine learning can streamline the process, by digesting data from a variety of sources to identify the underlying patterns. Humans will still need to interpret and explain the trends, but they will be able to concentrate on responding to the trends instead of the drudge work of finding out what they are.
For example, Netflix uses data on the viewing habits of its 86 million subscribers not just to recommend titles they will find most interesting, but also to decide which new shows it will put into production, based on how popular it calculates they will be.
This huge explosion of data gives brands the opportunity to quickly spot and react to the latest trends, fashions and fads among its customers and potential customers. As the amount of data generated online continues to grow, so marketers will need more help from artificial intelligence in making sense of it.
What does this mean for brands?
Brands have a great opportunity to stay ahead of the competition by setting trends and constantly surprising consumers with new products and designs. The ability of artificial intelligence to identify patterns from an increasing pool of real-time data will help content specialists to effectively create stories and pools of assets that can be easily and quickly adapted. It will also create opportunities for product development teams, enabling them to stay on top of the latest category demands.
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