A few years ago, artificial intelligence was introducing itself to the world of e commerce. In 2020 it has already evolved into an irreplaceable part of the business.
Although many e commerce platforms have already worked with AI models and tools for some years now, the majority of customers did not see the impact of artificial intelligence before the implementation of chatbots and recommendation engines, which became fundamental for most e commerce platforms in the last few years.
While now it is a big trend and more and more machine learning models are being adapted by this sphere.
In this article we will talk about ecommerce trends in 2020 and how they are affecting the industry. We gathered for you 5 important AI practices which are already turned AI in e commerce today.
Perhaps one of the most important aspects of artificial intelligence in e commerce at the moment, and how it is enhancing business performance, is personalization. Targeted personalizations have been proven to increase user experience for many e commerce companies such as Amazon, Ebay, and many more.
Artificial intelligence technologies create better personalization without human interaction. It can use many different data resources to individualize individual communication. And through machine learning, AI will get smarter every day. It’s a kind of automated business-intelligence on a very high level.
Ecommerce trends: Usage of Predictive Analytics in e commerce
Personalization does not end here — customers can also get product suggestions that are not just based on what the user was searching and looking up before. Machine learning can be used to predict what a customer would like to buy in the future, depending on all the various customer information we have and how their tastes might evolve with time due to age, location, trends, and other factors.
This kind of predictive analytics model is probably one of the most important influences of artificial intelligence in e commerce trends today.
The goal is an improved consideration of what customers would most likely want to buy next as well as decide when to show those offers to a customer in order to increase conversion rate.
The role of pricing is no less important. Predictive analytics is already used for identifying the right price point at the right time for each customer. With the help of AI, it will get to a higher level — it is becoming faster, more reliable, and cheaper.
3. Inventory Management
With predictive analytics, e commerce companies are also able to forecast their inventory demand. This is highly valuable, since inventories cost a lot of money and by knowing product demand more precisely beforehand, they can save a lot of resources.
4. Predictive advertising
Automated emails, and retargeted ads for customers that were adding items in their basket but never finished the order — marketers have long been struggling to turn these missed prospects into leads.
With the help of artificial intelligence and predictive analytics, we can target ads better based on the historical data and behaviour of each user. Unlike traditional retargeting, with predictive retargeting marketers are able to provide more prosperous solutions for rewarding targeting practices.
The difference between traditional retargeting and predictive retargeting is that in traditional retargeting all the customers are treated the same way regardless of what their behaviour on your site was, while predictive retargeting analyses the user’s behaviour based on historical data and gives more accurate and personalized retargeting optimization options.
In the near future, artificial intelligence will be able to track and measure the feelings of customers that influence their willingness to buy. AI will automatically react and deliver the information needed to satisfy leads and customers, which finally will result in an increase of revenue.
This topic has gained a lot of attention on the web during past years and many e commerce companies are aware of the upcoming changes in SEOand keyword research and analysis.
Natural language processing allows for catching those product searches that were mismatched or lost in the past.
In earlier times, online shoppers had to find the correct keywords to enter in the search field in order to find the product they were looking for. NLP allows the keyword entered in the search field to be related to the product, but does not necessarily need to be exactly the keyword of the product itself. This increases the chances of showing correct product listings to the customer and avoid lost prospects and keyword mismatching.
Despite natural language processing, voice search and image search methods have gained popularity, especially among Millennials and Generation Z, since they are using their mobiles on a daily basis. E commerce companies are aware of this growing habit and many of those are already working on the implementation of voice and image search into their online shops. By uploading a picture of a desired item onto the online shop, it will provide all relevant products that match the image that the user uploaded — that is more natural for a lot of users compared to typing the right words into an input field.
In this article we had a look at ecommerce trends in 2020. It is only a matter of time before most e commerce platforms will turn to AI in most of their processes. The change is already happening and many companies are experimenting with different AI technologies and machine learning techniques. Artificial intelligence has already proven to have a positive impact on e commerce by providing more convenience, a faster decision-making process, and a better user experience.
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