Kiran explains why especially retailing can benefit from Artificial Intelligence: ‘AI offers the opportunity to bridge the traditional retail gap between what consumers want and what retail can offer. Retail pricing is traditionally set twice a year and will usually be equal across the country. Promotions may have a six week cycle from idea to execution. AI can analyse a huge amount of data and according to the outcome, differentiate prices and promotions according to location, availability, freshness and dozens of other factors. Real time.’

Marketing is all about finding out what consumers need and responding to it. A number of factors dramatically enhance the possibilities we have for that, Kiran explains. ‘First of all, the new types of data we can collect. For example, cameras can register anonymous demographics of people who are in a store at any given moment: gender, age, type of clothing, even the mood they express. This is no rocket science; there is open source software available that you can use for this. Another example is imaging of fresh produce by visual images or spectral imaging with e.g. infrared. This can give a better prediction of the freshness of a product than human interpretation could. If you know a batch of apples will go bad in two days, you can quickly generate a price discount or promotion to sell them. There is a lot of development in the field of sensory data.’

‘The second major game changer is that AI can combine many factors in one model,’ Kiran states. ‘For example, you can combine data on inventory, type of people in the store, location of the store, weather conditions, competition’s pricing and a report on consumer buying habits in a model to come up with the ideal pricing of a given product at a given moment in a given location. A client of us in Latin America has 225 zone prices in its 13.000 stores. You can apply this type of intelligence real-time and in a very differentiated way. In fact you could say that every product at every store has its own brain in the cloud.’

‘The third powerful feature of AI is that it can also assess which type of data is relevant,’ adds Kiran. ‘You can put in new data types and have the system analyse if this data has a correlation with consumer demand. For example, does the haircut of the people in your store have an influence on the demand for a certain hair product? If yes, you have another element you can use to assess consumer demand and apply the right pricing and promotions accordingly.’

‘There are so many possibilities to improve your marketing results by using AI. It is possible to react real-time to any given factor and thus give people exactly what they need, at the price they like, in the store where they are. It can be used in any industry, from food to fashion to electronics. In the US, many retailers already use these techniques and the PIM event of May 14, I will discuss some interesting examples. Europe yet has to discover the ample possibilities. One factor I am personally excited about is that AI can seriously help reduce food waste. In the EU, around 88 million tonnes of food waste are generated annually with associated costs estimated at 143 billion euro (source: FUSIONS EU Project). If we can only reduce this by 10%, we are making a big impact. This is also the power of AI.’