5 Ways AI Will Revolutionize eCommerce

5 Ways AI Will Revolutionize eCommerce

May 6

According to Gartner, by 2020 over 80 percent of customer interactions will be handled by artificial intelligence.
Giants like Amazon, Alibaba, eBay, and Rakuten already use AI for their eCommerce efforts.
Three key elements of AI: data mining, machine learning (ML), and natural language processing (NLP) will help businesses increase their revenue and efficiency by completely eliminating repetitive tasks and allowing for more creativity.
Since eCommerce has become the standard for buying goods and services, and since these days customers are very informed and are quick to leave sites that offer them a substandard experience many brands around the world are continually investing into finding ways in which they can offer the customer a better experience and hence reduce churn. AI is one area that is picking up some interest and brands are seeking to embrace this in an effort to stave off competition.
Let’s talk about 5 ways AI will revolutionize eCommerce and why it is important for brands to equip themselves with the tools for informed decision making.

Better Customer-Centric Offering

Mobile is the medium of first consumption and consumers these days are highly informed. Whether they are comparison shopping for product features or pricing, they are quick to exit eCommerce websites if they are not satisfied with the experience. Some of the reasons why they exit sites are because products shown are completely irrelevant to their search. This is an area where AI can assist by narrowing and improving search results for online shoppers.
Pinterest is a good example of creating innovative visual search capabilities within their website. Their Chrome plugin allows users to select a product in any photo online, and it will then showcase similar items thanks to their image recognition software.
Salesforce also launched an AI-powered pilot feature called the Einstein Visual Search. It enables searching, shopping, and discovery through photos. The tool lets shoppers find the same product or most relevant option based on the photo they uploaded.
Rebecca Taylor, a women’s wear brand from New Zealand is one of the earliest adopters of the Einstein Visual Search. The website lets users find products within seconds without having to guess product names or type on a small screen. See how we helped Rebecca Taylor implement an omnichannel solution.
The Einstein Visual Search is currently in the pilot but it is projected to be available in late 2019.
This innovative visual approach assisted by AI provides for a much better customer experience, and allows online shoppers to be presented with similar product options to what they were searching through the site or the app.

More Efficient Sales Process

Customer Relationship Management (CRM) is another area where we see brands begin to integrate AI into their CRM solutions. Many AI systems enable natural language processing, and this enables CRM tools to answer many customer queries and even identify new markets and opportunities for the sales team. There is one aspect of delivering information from internal systems that are relevant to the customer, and the other aspect is capturing data that may show customer interest in other areas.
Using AI techniques along CRM software can also help with customer retention if designed and used appropriately. AI technology can also crunch the after-sales engagement numbers and highlight customers who have reduced engagement or shown lesser interest with your eCommerce brand.
Another area of keen interest these days is Voice enabled technologies. With the emergence of Siri (from Apple), and Alexa (from Amazon), among many others, Voice based applications and integration with eCommerce is taking shape. North Face, a globally known retail brand, has started to utilize voice input to enable AI technology.
Technology platforms such as Microsoft Azure have also extended features such as image analysis and can also comprehend speech through AI. The integration of all of these advanced features can help brands make better predictions using data.
The software asks the questions, the user answers using voice, and the software then scans the whole database of products in order to find the perfect matches. The additional advantage is that this dialogue with the customer enables AI mechanisms to potentially detect other areas of interest by the customer. This data is valuable in terms of marketing, promotions, and even using it to combine offerings with products. Some examples of this are linking a product added to the cart with another via a message that is similar to ‘customer also purchased these items together’.

Low-Cost Customer Experience Through Chatbots

Chatbots are becoming the norm for many online businesses. Most consumers are already logged into their social media platforms when they are browsing for products online.
Which means chatbots can provide instant online support for your customers and instant confirmation of orders.
eBay’s shopbot is a good example of a bot used to improve eCommerce. Users can communicate with the bot via text, images, and even by voice.
Salesforce offers a native Einstein Agent chatbox within its platform. Using Einstein AI technology, brands can deliver automatic service at scale. Microsoft’s Azure chatbox service is another solution that can help build conversational experiences for shoppers.
AI technology can improve chatbot experience, and increase eCommerce revenue by offering a more personalized recommendation based on past chat history or purchase history.
The use of chatbots can also significantly reduce the financial costs companies because chatbots can reduce the need to hire extra team members for customer-support operations as many of the support tasks for online shoppers can be handled via chatbots.

Improved Hyper-personalization

AI can also help brands scan and analyze vast amounts of data, so they can predict consumer behavior with greater accuracy and offer relevant recommendations. AI algorithms can be tailored to pull data from customer preferences, account information, history of purchases and provide actionable insights. All of that information allows the creation of Hyper-personalized experience so e-commerce businesses can offer the best of offline shopping experience to online shoppers.
For example, Netflix is a good example of hyper-personalization done right. The streaming service offers recommendations based on a user’s interaction with certain categories on the site. Netflix goes as far as to display different thumbnails to users based on the image sentiment and user preference!

Filtering Fake Reviews

Fake reviews are a big problem for eCommerce brands and their online shops. According to Dimensional Research’s survey, more than 90 percent of shoppers stated that positive online reviews are one of the most important aspects when choosing whether to buy or not. However, eCommerce brands and online shops also have to deal with a large number of fake online reviews. A misleading review or a fake bad review can seriously damage the reputation of an eCommerce brand.
That is why many eCommerce brands use AI in order to combat fake reviews and inflated star ratings. As AI algorithms learn to recognize fakes, the process can go much faster through many comments, reviews and ratings to quickly assess the fakes versus the real reviews so brands can take action.


Although AI sounds like the end-all solution to every problem with eCommerce platform implementations, we are not quite there yet. To be effective, AI needs access to data and a meticulous foundation and relevant skills to tailor the specifics of how these algorithms sort, process, scan and work on the data to deliver useful information.
Visionet Digital helps clients build a platform, a single touchpoint for processing online and offline data and gets them ready for the AI revolution.
Reach us so we can help you define, build and support a unified commerce experience across all stores and digital channels.

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