January 23, 2020
Online shoppers worldwide spent $3.46 trillion online in 2019, up from $2.93 trillion in 2018. The e-commerce industry is growing, thanks to technological advancements and new trends that are arising.
AI and machine learning are one of the most significant trends, making online retail stores more user-friendly and safer. AI has been the buzzword of the digital industry for the past few years, making it insightful and more innovative. Without AI, e-commerce stores wouldn’t be as smart as we know them.
AI is now changing the way e-commerce works. Manufacturers and online retailers have still a long way to go until they adapt and leverage the full potential this technology has to offer. If they know how to leverage its possibilities, they could gain significant competitive advantages and improve brand images.
AI-based e-commerce stores create a unique experience thanks to the ability to detect patterns, interpret data, and personalize the customer journey. Chatbots, voice assistance, and visual search are only some of the advanced experiences this technology has to offer.
The e-commerce industry will keep adopting smart solutions in 2020, helping online stores improve their profitability. Here are the biggest AI in e-commerce trends to mark the year:
Thanks to AI-powered tools, online retailers can now retain customers with more personalized offers, improving their conversion rates and gaining more loyal customers.
Recommendation algorithms are a powerful tool that encourages shoppers to buy more. For example, Amazon recommends new books based on those you’ve already bought. Or, Netflix recommends new shows that are similar to those you’ve watched before.
Valuable customer data allows you to filter your products and show your visitors relevant and personalized product recommendations. According to Salesforce, product recommendations can increase online retail revenues by 16%.
AI is a powerful tool that has the ability to learn what users like based on their past behavior, helping them find exactly what they want. Users will be loyal to a website that can give them what they want in no-time.
Visual search is an AI-based technology that helps customers search for items by only uploading an image of them. Regardless of where the image is from a magazine or social media, the engine finds the most similar product and displays it to the user.
Visual search is here to make the search for products more convenient and user-friendly. It eliminates the need for complicated keyword searches and scrolling through product catalogs. Now, the engine identifies the most similar product from the store’s product catalog in only a few seconds.
Marketers have recognized the rise of visual search, so 35% of them are planning to optimize for visual search by the end of 2020. Thanks to visual search, online retailers can improve their organic image visibility, customer engagement, and increase conversion rates.
Visual search will be a VERY big deal in 2020 and the following years, powering the AI image recognition market, which is expected to reach 622.03 million by 2025, growing at a CAGR of 24.82% during the forecast period (2020 - 2025).
For example, luxury retailer Neiman Marcus decided to make its customer service strategy digital-first, starting up its own lab where technologies like AI, AR, and visual recognition are being used to make the online shopping experience more advanced. The founding of the lab resulted in the retailer’s Snap Find Shop visual search app feature, which enables users to take a photo of a clothing item and find a similar one in the Neiman Marcus online store. The company’s step towards digitization contributed to a sales increase of 6.2% between 2017 Q2 and 2018 Q2.
Brands have started developing AI-powered shopping assistants that can help online shoppers save time when searching for some item. These assistants help users through social media, their virtual assistants like Alexa or Google Home, or they’re integrated with online retail stores.
They are based on AI and natural language processing algorithms that give them personality and make them human-like.
Shopping assistants that help users through social media or e-commerce stores are called chatbots. Chatbots provide 24/7 support through automatic responses for different scenarios that could occur when a user requires help with purchasing an item. This is a great upgrade to traditional customer care where customers have to make calls with store employees and wait much longer to get answers to their questions.
Chatbots are also used to perform other interactions with customers, like asking for feedback or notifying them about their order status. For example, eBay’s chatbot can answer to any kind of question about products that are available on eBay.
AI and machine learning can be of great help when it comes to making sure customers get exactly what they need at the right time. Smart stock planning and management are the key to satisfying this crucial customer need.
Retail managers can’t sell items if they can’t dispatch them right away. Running out of stock means losing customers to other e-commerce stores who have already planned purchase.
In this case, AI can help online store managers forecast customer demand and prepare for seasonal changes and industry trends. Everything’s much easier when consumers are online—all the vast amounts of data they leave can lead to better business decisions.
AI-powered tools convert this data into valuable information that boosts managers’ decision-making, highlighting the exact type and amount of products they need to have in stock in order to make their customers happy.
Even though online retailers still feel suspicious about using AI as something very complicated, the technology is rapidly spreading. Many of them have recognized its potential and the benefits they could get by embedding AI into their online stores.
In 2020, this trend will continue its rise. Don’t get left behind. Upgrade your online store. Pixyle’s visual AI for e-commerce stores can help you make customer experience unforgettable. Offer your website visitors relevant and personalised product recommendations based on their visual style preferences.
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