One area where we, as an agency, leverage AI is undoubtedly in maintaining or building e-commerce platforms. Implementing such solutions allows our clients to optimise team performance. As a result, we can deliver solutions much faster and more cost-effectively. Of course, from my perspective, we are still at a point where programmers, and designers (essentially people) are responsible for the final shape of the product. Their work can simply be supported by the vast array of tools available on the market. Regardless of the task’s scale, the time needed for its completion is significantly reduced.
Our developers create tools to streamline their work and avoid repetitive tasks (which are frankly tedious). Preliminary analysis for adapting a website for people with various disabilities is a task best handled by the right AI-based tools. Continuous monitoring also falls into this category. Instead of analyzing line by line or page by page, one can use a crawler or a code analyzer for WCAG compliance. This can be integrated into a monitoring tool, which significantly reduces maintenance costs and, in turn, improves search engine rankings—an outcome that directly translates into more sales.
A well-functioning e-commerce platform delivers positive buyer experiences on multiple levels. It also achieves a balance between sustainable buying and selling practices. Efficient procedures, both internal and external, where employees and customers can seamlessly navigate are crucial. Customer service presents a significant challenge, especially for major players. Returns, complaints, inquiries, emails, and phone calls result in departments dedicated to these tasks employing dozens of people. Yet, chaos can still arise despite these efforts. This is understandable; e-commerce is a dynamic ecosystem connecting people—those who wish to buy and those who wish to sell.
Customer service departments handle a massive volume of inquiries that must be filtered and directed to the appropriate personnel. Problems abound, and every customer expects their issue to be treated as a priority.
75% of online consumers expect a response within 5 minutes.
An efficiently functioning AI-powered system can perform an initial analysis of incoming issues and route them to the appropriate department. Furthermore, after preliminary classification—entirely without human intervention—it can request additional information from the customer if something was omitted when reporting the issue. Sounds promising, doesn’t it? Now, imagine adding a chatbot, an intelligent FAQ system, and reducing the number of direct inquiries. This results in automated customer service processes, less frustration among employees, and a buyer who feels like a top priority.
For several years, our agency has collaborated with a client running an e-commerce business offering products with numerous certifications. Each product comes with a wealth of certifications and specifications describing dozens of attributes and uses. For the customers of these products, this information is crucial.
Instead of browsing through countless pages to filter suitable products, an intelligent configurator or search engine can be developed. For instance, a query like „Show all products with fire-resistance certification up to X degrees that can be used to connect material A with material B” could yield accurate results in no time.
The possibilities are vast. Imagine creating a virtual advisor for a cosmetics store that suggests products based on a consumer’s query, such as: „I have a company party on Saturday with a casual dress code. Recommend an outfit suitable for a 26-year-old woman. Oh, and I don’t like red.” By the way, I’m eagerly anticipating the first fashion show featuring outfits entirely curated by AI! 🙂
A particularly intriguing application of artificial intelligence in e-commerce is user profiling. By analyzing consumer activity on a website — such as browsing, searching, and navigation patterns—we can classify their intentions. This allows us to suggest appropriate products. While several tools are available for this purpose, many operate based on pre-designed scenarios. For example, we can feed an AI algorithm data about what a user is reading, which products they are viewing, and which subpages they visit. The algorithm independently classifies the user based on this data.
We internally developed a tool that analyzed viewed subpages and visited links to determine the type of user and the optimal moment to suggest a contact. The insights generated by these algorithms were sometimes surprising but often proved to be highly accurate.
Artificial intelligence can undoubtedly assist in optimizing any e-commerce platform. However, the extent to which it is helpful depends on the specific challenges faced by the platform’s management team. Given the variety and accessibility of AI-driven solutions, we will increasingly witness their implementation in various online stores and sales platforms. Search engines will no longer be limited to simply responding to product name queries. A significant portion of customer interactions could be handled without human intervention. However, it is essential to avoid overusing AI in every possible scenario. Implemented solutions should result from thoughtful analysis and effectively address real-world problems.
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For over a year there have been discussions in every industry about the role of AI in the workplace. Mainly these concerns are about whether or not it an going to take away our jobs? So far, no one is likely to be able to answer this question clearly, so I’ll throw in a quote that I think hints a little at the answer. AI won’t replace designers. A designer […]
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