The Future of AI in E-Commerce: Detecting Fraud or Trying on a T-shirt Online Will No Longer Be a Problem

Artificial Intelligence (AI) is often used as a buzzword to describe almost any automated system in the online industry. Many companies and startups boast about implementing AI just to make their products more attractive, but in reality, they often have nothing to do with AI at all. While this mischief has spread across various industries, that doesn't mean that AI doesn't realistically have something to offer anymore. Quite the contrary. Let's now take a look at arguably one of the most dynamic areas where AI can deliver real results if approached correctly, and that's e-commerce.

What real use does AI have here and where does its future lie?


1. Personalization

Artificial intelligence will increasingly be used to analyze customer behavior and preferences. Based on this data, e-commerce platforms will be able to provide personalized product recommendations, which will not only improve the user experience but also increase the likelihood of purchase. In practice, data on customer behavior on a given e-commerce site is first collected - ideally over a period of one to two months. The resulting data is then fed into prediction models to provide more accurate and personalized recommendations, including based on real-time user behavior. So, for example, it knows that you'll buy red wine rather than beer with your minced meat because you've done it several times in the past, or other users usually do.

The main allure of AI is its ability to recognize and adjust recommendations based on changes in your purchasing behavior, such as if you start choosing beer more often. This capability, called machine learning, therefore allows the models to improve and dynamically adapt based on the growing amount of data. In the future, most smart whisperers and search will work in a similar way, as will, for example, the management of marketing campaigns. In the case of emailing, it's enough to have a user's purchase history and a predictive model that can forecast what products they might be interested in next. With retention, this is a really powerful advantage.

2. Demand forecasting and inventory optimization

AI algorithms can also be used to predict current and future demand for products based on historical data, seasonal trends, and other factors. In simple terms, AI can predict exactly how much stock you'll need at different times of the year, regardless of whether you sell swimwear, groceries, or electronics. Among other things, algorithms can also predict the impact of unexpected events such as a pandemic or a change in legislation. The principle of operation is then the same as in the case of recommendation. You take historical data over a relevant period - in this case, it will certainly involve comparing several consecutive years for high statistical relevance - and populate machine learning models with it.

You can also use pre-trained models, for example, on data from other companies in the same industry. Yes, the use of AI in practice today offers such benefits as well and can be applied to your specific business. As a result, retailers can better plan their inventory for the entire year, leading to more efficient use of warehouse space and minimizing (sometimes) unwanted sales. Last but not least, the accuracy of such forecasting can significantly optimize cash flow.

3. Virtual test rooms and augmented reality

Imagine no longer having to go to the store to pick out furniture in person, because the store will create a virtual room that exactly replicates the one in your home. For example, you upload a photo of your kitchen, the virtual room opens up for you and you can start selecting the right set-up. Then all you have to do is put everything in the basket, order the assembly, and you have your new kitchen at home within a week. The first steps in this area are already being taken, for example, by the well-known Ikea.

The same is true for choosing new clothes in virtual fitting rooms. Artificial intelligence makes it possible to try on products before you buy them without having to visit a brick-and-mortar store. This, of course, brings a whole different level of user experience to the online shopping experience and also gives retailers the opportunity to save a lot of money with the operation of (often really big) stores.

4. Fraud detection and security analysis

Fraud can cause significant losses for online retailers and damage the credibility of their hard-built brand. So, AI is logically becoming an increasingly important tool to combat fraud in e-commerce. Primarily because it can very quickly identify technicalities leading to collusion from data, even if they differ only slightly from "normal" behavior. So how does it help?

AI can be used to monitor customer behavior and identify anomalies that could indicate fraudulent activity, such as unusual purchases, changes in payment methods, or attempts to access accounts without authorization. Behavioral data analysis using machine learning can also very accurately detect bots and crawlers of automated systems performing fraudulent activities that can be used to manipulate prices, purchase limited products, or generate fake reviews. Additionally, we filter bot and crawler traffic to more accurately measure the positive impact of our recommendations within Zoe.ai.

Another type of fraud, for example, is the takeover of a user account by a third party. AI can also detect such behavior very well by detailed behavioral analysis of the user account login process (e.g., by tracking keystroke dynamics when entering usernames or passwords). Analyzing written text also helps verify reviews, comments, or other customer feedback, detecting if they are fraudulent or automatically generated.

Conclusion

These ways of using AI in e-commerce are certainly not the only ones. We can also mention, for example, fraudulent transaction detection, customer support in the form of chatbots, or the integration of voice assistants. Artificial intelligence is already an absolutely essential tool for improving customer experience, increasing store efficiency, growing sales, and other absolutely crucial factors in the ever-evolving world of online commerce. It's safe to say that its influence will continue to grow in the coming years and will become indispensable for medium and smaller retailers as well.