This post was featured in Venture Beat and can be read here.
With the pace of change 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% of consumers trust online reviews as much as a personal recommendation (source). Google themselves are paying more attention to reviews with industry analysts noting that consumer opinions are impacting page ranking more than ever before.
Second, the adoption by 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 by, for example, learning from past results. Anyone, however, who has spent time playing with Siri – Apple’s “digital assistant” and user of semantic analysis – 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% of shoppers starting in search (a number expected to increase), how can retailers update this important tool to serve consumers to increase conversion and reduce bounce rates?
Change is Afoot
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 or in healthcare to predict the next lifesaving drugs, AI technologies such as Machine Learning and Natural Language Processing have huge potential in helping retailers dramatically reduce the path to purchase.
Although not quite as sexy as IBM’s AI powered Watson appearing on Jeopardy or self-driving cars, sites such as Amazon and Netflix are quietly looking at AI and specifically at the search bar.
A great example 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-man start-up will help Etsy improve its search bar as well as general discovery capabilities to point shoppers to items better matched to their tastes.
Another factor driving the need for change in the search bar is the impact of mobile on eCommerce. As eyeballs are increasingly spent on 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 when shoppers are searching in-app or on mobile sites, the most relevant products are being shown without the need for shoppers to scroll through page upon page.
Consider the popular travel website Expedia. They realized that the standard travel search framework doesn’t work as well on mobile devices and that searching through thousands of options isn’t attractive for tablet or mobile users. According to Expedia’s VP of Global Product, David Fleischman, they are applying AI to ‘’the mounds of traveler data we look at en masse to predict trends and identify patterns’’.
At Aspectiva we are using Natural Language Processing and machine learning technologies to analyze the massive volumes of consumer opinions across the web on any product or service. Realizing the potential of leveraging consumer generated content to power a better online experience, we are working with sites like Walmart, Shop.com and the travel site Amadeus to present shoppers with the products closest matched to buyer intent.
We are then able to use the insights garnered from consumer opinion to better match the products that shoppers are searching for, and for the first time, allow them to search for products by intent and not by product specification or description.
Aspectiva harnesses Artificial Intelligence, allowing consumers to search for hotels in New York that are the best for kids, or washing machines that fit small apartments and are good for pet hair. Shoppers can find what they are looking for without having to read through numerous reviews which result 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 instore assistant, all 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.
Ezra Daya is the co-founder and CEO of Aspectiva.
Using Artificial Intelligence technologies, Aspectiva analyzes consumer opinions from across the web, turning them into comprehensive and valuable insights, helping eCommerce visitors make informed decisions resulting in increased online conversion rates.