How A.I. can improve the search bar

With changes in ecommerce taking place at a faster rate than ever before, two major shifts in consumer behavior have impacted retailers in a way that they cannot ignore.

The first is the increasing importance placed on consumer reviews. This trend has grown in significance, with one survey stating that 88 percent of consumers trust online reviews as much as a personal recommendation. Google itself is paying more attention to reviews, with industry analysts noting that consumer opinions are impacting page ranking more than ever before.

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The second shift is around retailers who are using semantic search technology to power their search bar. Semantic search aims to improve search accuracy by understanding the searcher’s intent and context. This technology improves by, for example, learning from past results. However, anyone who has spent time playing with Siri — Apple’s digital assistant — will know that the search engine “still needs a lot of work.”  In fact, the experience of using the search bar is far from intuitive and can even be quite frustrating, forcing shoppers to sift through product suggestions and waste time retyping text to find what they are looking for.

Although retailers have made big gains, these two trends have served to condition consumers, who now expect an intuitive experience and will go elsewhere if they don’t find the product they want, with accompanying reviews, in the first 10-20 seconds.

With 30 percent of shoppers starting in search (a number that’s expected to increase), how can retailers update this important tool to serve consumers, increase conversion, and reduce bounce rates?

The good news is that ecommerce is on the cusp of a wave of change, thanks to Artificial Intelligence. Already being used in finance to help pick stocks and in healthcare to predict the next life-saving drugs, A.I. technologies such as machine learning and natural language processing (NLP) have huge potential to help retailers dramatically reduce the path to purchase.

Although most artificial assistants are not quite as sexy as IBM’s A.I.-powered Watson, which appears on Jeopardy and in the company’s self-driving cars, sites such as Amazon and Netflix are not-so-quietly looking at A.I.

A great example of interest in A.I. is Etsy’s recent purchase of Blackbird Technologies, which uses machine learning to analyze user behavior and other variables to suggest relevant search recommendations. The 10-person startup will help Etsy improve its search and discovery to point shoppers toward items better matched to their tastes.

Another factor driving this change is the impact of mobile on ecommerce. As eyeballs are increasingly glued to mobile, the retailers themselves are pushing their dedicated apps as a shopping portal. With space at a premium on smaller screens, it is vital that the most relevant products are shown first when shoppers are searching in-app or on mobile sites, thus bypassing the need for shoppers to scroll through page upon page.

Consider the popular travel website Expedia. The company realized that the standard travel search framework doesn’t work as well on mobile devices and that the prospect of searching through thousands of options isn’t attractive to tablet or mobile users. According to Expedia’s VP of global product, David Fleischman, the company is applying A.I. to ‘’the mounds of traveler data we look at en masse to predict trends and identify patterns.”

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Natural language processing and machine learning technologies help analyze the massive volume of consumer opinions that are documented across the web on any product or service. The insights garnered from consumer opinions help retailers identify the products shoppers are searching for and, for the first time, allow customers to search for products by intent, rather than by product specification or description.

Artificial intelligence allows consumers to search for hotels in New York that are good for kids, or washing machines that fit small apartments and are able to handle pet hair. Shoppers can find what they are looking for without having to read through numerous reviews, which results in higher on-page interactivity and lower bounce rates.

The potential to suggest products according to shopper intent creates an online experience more akin to having a conversation with an in-store assistant, except it’s powered by millions of opinions from across the web. With the expected growth of voice recognition and chatbot technology, it is safe to predict that this is just the beginning of a sea change we can expect to see continue in the ecommerce sector. The revolution has well and truly begun.