Data is the key to unlocking insights about market segments and implementing merchandising strategies that work.
Information about how the user reached the site, their past purchases, browser behaviour and viewed items can all be used to generate user-unique merchandising strategies in real-time.
Artificial intelligence (AI) is at the forefront of putting such data to work – and it’s revolutionising the merchandising process.
Machine learning, self-learning algorithms and other AI-powered technologies allow brands to incorporate intelligent product recommendations and discovery, personalised dynamic content generation, retargeting ads, omnichannel integration and much more into their merchandising strategies.
Online retailers often find themselves with too little data to design merchandising strategies. But, conversely, they can also end up collating vast datasets that prove challenging to work with from an analytical or computational standpoint.
Where teams face the sparsity problem – the availability of little or no user data – Attraqt provides powerful out-of-the-box omnichannel merchandising strategies that don’t depend on masses of information to generate quick ROI.
For teams who struggle to make sense of extensive existing data, Attraqt provides pre-trained algorithms that make fast work of large data sets to seamlessly align merchandising touchpoints with little technical know-how or management required.