One of the many Artificial Intelligence (AI) applications is improving an eCommerce site’s performance by offering personalized experiences to shoppers, thanks to an in-depth analysis of customer consumption patterns. To make this possible, we need as much as possible about our customers to improve how we serve them better by inferring what they want, and identify a target audience to grow our customer base. The limit on the amount of information we gather depends on local applicable laws and the value we put on our customers’ privacy.
There is no human way to process, analyze and take action on all collected data, so all this information is processed through machine learning (ML), which allows the system to make automated decisions based on large amounts of data. It identifies patterns, learns and turns data into predictions.
See our previous article on AI and ML
One step further goes deep learning, a subcategory of machine learning that seeks to imitate the human brain and offer personalized and more precise recommendations. These algorithms identify the intention and attitude of the users who visit the web, making specific recommendations based on the data collected. According to RTB House, these personalized messages can make advertising activities up to 50% more efficient than the typical machine learning approach.
The main advantage of this technology for online sellers is that they will be able to give up control of their virtual stores without having to guess the peaks of the activity or user wishes, reacting at the moment according to the stimuli that are received at a speed far superior to that of any human being.
Another of the outstanding great achievements that artificial intelligence has allowed in the field of user experience is visual search. It allows the customer to locate objects on the internet through a single description based on image recognition. For sellers, it will mean being able to manage their catalog more quickly and efficiently, automatically recognizing models or colors, and developing new ways of relating to their buyers, who are increasingly relying on visual content in their personal relationships and with brands.
The areas of application of AI, ML and deep learning are vast, and once you start there seems to be no end. It also seems to be extremely hard to start its implementation. Big companies have built AI capabilities in house and expanded the areas of application from one department to another. It requires a very specialized and knowledgeable team, but most importantly the active participation of the rest of the company.
Smaller companies can also benefit from AI, you might be able to outsource the technical capabilities from the right technology partner, the most important part is identifying the business area to improve and have an open mind on how to improve it. In any case, keep in mind that although AI and ML will improve a process or your whole business, the best improvements in applying the technology are those where the people who manage the current process actively participate in defining the solution, allowing machines and humans to learn from each other.
If you are interested in developing an AI solution in your business we can help. Contact us at info@mahisoft.com with no compromise.
