Transforming E-Commerce: The Introduction of Artificial Intelligence

By Martin Rugfelt — November 19, 2013

There is a case to be made that soon, "online" experiences will be replaced entirely by "mobile" experiences. E-Commerce has been the first industry that has aimed to fully transform the way people live and act as consumers in a mobile world. Indeed, the m-commerce market investment is apparent. Recent revised projections by eMarketer reveal that by 2017, mobile retail sales will be more than $100 billion. Additionally, ComScore analysis has found that one out of every three monthly visitors to the average digital retailer web site comes exclusively on mobile platforms.
 
However, there remains a surprising lag in e-commerce at this time. Despite its rapid surge as it entered the landscape, it is growing at a slower pace. In part, this is due to a maturation process underway for e-commerce. If you consider the online/mobile shopping experience today –with its mobile apps, video integration, visual advancements and social engagement aspects –in many ways they are not applying anything genuinely transformative to the shopping experience; we have concepts but no real, new, immersive experience in our present online shops.
 
So, what does it take to really change shopping? One key is to bring the best of the offline world to the online world, and this can be summed up in the seamless way we "discover" in physical environments and the way we "learn" about new products. According to a recent survey of marketing executives by Accenture, 69% agree that consumers expect the kind of relevant offers and interactions such insight allows, yet only 12% said they are leading edge at it. The only way to replace our eyes and our personal context in the mobile world is by allowing machine learning to adapt to our behaviors when it benefits us to do so, and this is especially true in the shopping experience.
 
As a shopper, one wants to be able to get the best possible professional advice and recommendations online. This requires extensive Artificial Intelligence (AI) and the long term solution to a better shopping experience is offering virtual assistants.
 
Virtual assistants are, in effect, highly intelligent recommendation systems. These recommendations systems for the future will drive sales by gathering knowledge from the organization, information and data to create intelligent solutions that differentiate businesses. Such systems are needed to take the current omnichannel retail space to its transformative potential and to make the ease of mobile shopping the only online experience in the near future.
 
Two other transformative ways Artificial Intelligence can grow mobile commerce are bringing the long tail to life through discovery and personalization.
 
Bringing the Long Tail to Life: Discovery
The long tail changed shopping, and now AI will bring intelligence to that tail. E-Commerce brought the magnitude of diversity and the long tail to shopping, however it still requires people to know what they want in order to find the products they'll purchase. For those of us in a store, it's as easy as visually locating what we want to explore and discover –this process transferred to the internet is an ongoing challenge. Collaborative filtering helps for reasonably popular products that are not driven by personal needs but for the long tail discovery and recommendations it doesn't provide the accuracy that's needed. AI picks up where collaborative filtering left off and can find, recommend and help people discover products. There is a clear need for this as illustrated by Amazon, one of the largest e-commerce marketplaces in the world, who reported that it receives about 35% of its revenue via product recommendations.
 
Long Tail Personalization
Recent findings have found that 53% of online merchants report an increase in returning visitors when using personalization. Personalization can be done for popular products but does not work for long tail products. The reason is simple: there are not enough clicks, or data, to form patterns on which to base the personalization. By using AI to create a knowledge space around products it is now possible to enable personalization even for long tail scenarios. The results will have a massive impact on large retailers with thousands, even millions, of long tail products. With the added perspective of multiple data sources and big data from brick and mortar storefronts, advanced analytics can result in better conclusions and personalization can be augmented.
 
The future of e-commerce is m-commerce with AI included. The question is not if, but when we'll see the first truly transformative offerings that embrace the exciting world of AI and use it for our benefit to create better experiences for every single user.
 
Martin Rugfelt is CMO for Expertmaker, an Artificial Intelligence (AI) and Big Data analytics software company for developing intelligent solutions.

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2014 ENGAGE
2015 Retail Technology Conference