Artificial Intelligence: Leading the Future of e-Commerce
Ai based personalization strategies enabled retailers to see an increase of 6–10 percent in sales, twice or three times as fast than other retailers. This technology is expected to boost profitability rate by 59 percent by 2035 in the retail and wholesale industries.
Ai technology has become more and more common in the last few years, in fact in 2017 more than 60 percent of business utilized Ai tools in some form or another. Of those 77 percent used Ai technology to improve their marketing and sales operations. Furthermore, based on a recent study by Business Insider it was estimated that by 2020 85 percent of all customer interactions will be managed without human involvement. An argument further strengthened by the heavy investment in the field pioneered by Google recent purchase of the startup DeepMind for the hefty sum of £ 400 M.
What is Ai?
While Artificial intelligence gives the impression of a highly complex technology it doesn’t necessarily have to be and is a name of a wide range of technological solution that reduces the need for human involvement. In simple words, Ai technology is the ability for a computer to complete tasks that would normally require a human, following a set of rules (algorithm) to make decisions. Machine learning which is another widespread term often connected to Ai is the ability for the computer to make its own rules and improve upon the original algorithm for better results, thus the origin of the name learning.
How can Ai benefit e-commerce?
There are many potential applications for Ai in e-commerce, from improving and automating customer service, to the enhancement of marketing and sales, and even to forecasting customers future needs. The possibilities are endless and potential for revenue is high, so much so that we can already witness numerous of the biggest companies put Ai in the center of their competitive advantage. Making Ai technology the future of their firm.
There are many examples of such companies, not all of them can be reviewed but a few examples can be named to shed some light on the future of Ai implementation in e-commerce. The first example is The North Face, a well-known e-commerce retailer, which utilized Ai to better understand its consumers. The North Face is using IBM’s AI solution called Watson to help their online shoppers find the perfect jacket, by asking them a series of questions through a voice input Ai. By analyzing the answers Watson scan through the hundreds of products until it identifies the perfect match in real-time.
Amazon is another great example of making Ai and machine learning part of your core company’s competencies. Amazon uses machine learning to drive their product recommendation (estimated to drive 35 percent of the company’s revenue), utilizing a combination of collaborative filtering and next-in-sequence models to accurately predict the specific products each individual customer might want to view next. Amazon further uses Ai to enhance its logistical operation, as Ai is responsible for reroutes, changes delivery arrival times, as well as other adjustments to best assure accuracy and efficiency.
Flipkart, the Indian-based e-commerce giant, has even attempted to build human brain-like capabilities for smarter sale process to its to more than 45 million of its registered online shoppers. Creating a shopping assistant known as Ping, which was later shut down in order to focus on its new ‘user-to-seller’ chat. Pinterest has further pushed the envelope with the recent update of its Chrome extension by allowing users to easily select items in any photograph online and present them with similar products for purchase, thus bringing social media and e-commerce one step closer.
inFASH & Ai
inFASH, a fashion first social platform, is another company to take us a step further in the journey for Ai. InFASH much like Instagram encourages its community members to share pictures of themselves, though in this specific case, the images and videos are all connected to fashion and style. The app then utilizes Ai to analyze each posted image and video, break down the items included to different categories, and tag them with shoppable links of the same item and similar ones from different price ranges. By doing so, inFASH is able to offer an engaging and fun shopping experience to its users, while further rewarding the individual who posted by rewarding him/her with a percentage of the value of each item purchase based on the post. This combination of a fiscal incentive combined with better shopping capabilities seem to be the next natural stage of influencer marketing, this time widening the selection of potential influencers to everyone with an account on the app.
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