According to analyst Forrester, artificial intelligence, big data and analysis will increase businesses access to data, broaden the types of data that may be analysed, and raise the level of sophistication of the resulting insight. Customers increasingly want retailers to offer convenient, responsive and personalized services. A latest IBM study revealed 48% of clients believe that it's essential for retailers to provide on demand personalised promotions when on-line, while 45% want the same options in store. Customers also want to discover and purchase products however, whenever and wherever they want and are assuming ever greater ownership over their retail journeys.

Source: worldretailcongress









AI CASE FILES:

The brain can consume and process only a limited amount of info while traditional computing is pre-programmed and rigid, unable to learn, reason, relate or interact in natural language. In 2016, outdoor clothing retailer North Face began utilizing Watson, IBM's cognitive computing platform to power a personalised commercial experience for clients on its website. The retailer used Expert Personal Shopper, a shopping platform from Fluid, which IBM acquired in Nov 2016.

Otto, a German e-commerce company, uses AI to predict what customers are likely to buy in the following week—based 200 data points and weather data. The AI solution’s predictions are so accurate (90% accuracy) and so effective, that Otto lets the system buy 200,000 items a month from third-party brands, all on its own, without human intervention.

Source: Forbes

Another company looking at exploring the possibilities of cognitive computing and AI in retail is luxury fashion retailer Yoox Net-a Porter Group.

Tangible benefits of AI in retail:

Personalized product recommendations:

AI makes it seamless for retailers analyse shoppers in real time and recommend products that are based on images shoppers are looking at in real time, and reams of other data—resulting a more accurate product recommendation. AI reviews the data to understand each shopper needs and uses the company’s AI algorithm to offer thousands of products for personalized style recommendations.

Dynamic pricing - third dimension:

AI offers retailers apply dynamic pricing beyond the laws of demand supply. Dynamic pricing takes into account customer’s increasing trail data, which shall be used by pricing algorithms based on time of the day, location, prior purchase history etc...

Customer Segmentation:

AI powers sophisticated customer segmentation through real time data integration, enabling marketers to make the customer journey more personalized and efficient. AI to collect data to create a more complete view of each customer and thereby creating a whole lot of customer segmentation.

Target Marketing:

AI enables quick and personalized AD targeting based on shopper recent search history and behaviour on related platforms. Conversation ratio of campaigns powered by AI & deep learning surpass random marketing with huge gap.

Product Development:

AI adoption in retail unravel data points which ware not visible earlier. Result of which retailers shall be able to develop new product line quickly as per shoppers wish list, based on entry and exit behaviour and deep learning.