In 2015, the Chinese e-commerce market generated an estimated $562 billion in sales, with shopping named as the fastest-growing online activity among Chinese consumers.
Though the rise of e-commerce is hardly a surprise at this point, the global reach and consistent growth in this sector make it one of the most significant global trends.
What makes this all the more notable is that the rapid transition from the brick-and-mortar shops of old is still heavily limited by technology – specifically, the limitations of online product searches, which, especially compared to a conversation with a real world sales associate, return far too many irrelevant and unspecific results to be of reliably convenient use.
Accordingly, what is left is a global phenomenon that has succeeded in profoundly disrupting the traditional shopping experience, but has yet to reach its full potential.
The bright side to this story is that the key to unlocking the next wave of e-commerce disruption has arrived, this time with the advent of artificial intelligence (AI).
>See also: How artificial intelligence is driving the next industrial revolution
Much has been said about the implications of AI, particularly for industries reliant upon manual labour, from car manufacturers to surgical clinics.
But consider the potential impact of such technology in the multi-trillion-dollar global e-commerce industry, one that has evolved into an integral feature of the average consumer lifestyle and a common medium across countless verticals.
The confluence of AI and e-commerce could not only transform the millions of online transactions that occur every day, but also in-store purchase behaviours, already influenced by digital interactions at a rate of 36 cents for every dollar spent in the retail store, or approximately $1.1 trillion total.
Where exactly will this impact be felt? Here are three key implementations of AI that will fundamentally change the face of e-commerce, bringing it many leaps closer to its optimal impact.
Arguably the biggest limitation in the e-commerce industry today is the burden placed on the consumer to choose and then fine-tune a keyword that accurately identifies or describes the product they want.
If they choose right, the respective search engine’s algorithms’ will fish out relevant results. If not, they will have to iterate with the keyword trial and error until they find what they are looking for. More often than not, this does not go as planned.
The scenario usually plays out something like this: a shopper inputs “smartphone android” into the search bar. While a human representative would either understand the meaning or probe for more details, the current digital results are far from promising (try it on some of your favorite e-commerce engines and see). The result is often pages upon pages of smartwatches, phones, cases and other android devices.
This is because current search engines typically work by retrieving results based on matching keywords in a search query to keywords in product titles and description, without factoring in the greater context. By design, search engine algorithms adhere to specificity, a characteristic typically absent in everyday vernacular.
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