How e-commerce can use AI to improve service and create a competitive advantage
7. 8. 2024
Artificial Intelligence (AI) is a revolutionary technology that has the potential to completely change the way online stores operate in the digital environment. AI will be a key tool in e-commerce in the years to come. This is because it can instantly analyse large amounts of data and provide accurate and personalised information, which is extremely valuable when it comes to online purchase incentives.

Personalisation and search
One of the main uses of AI in e-commerce is service personalization. AI can analyze data about user behavior on a website and create personalized product offers and recommendations based on that data. Smart search works in a similar way, except that search results are displayed as a list of products, usually in a search window. How do these systems work?
Let's take a specific example. You are a regular visitor to an online shop selling medicines, cosmetics and drugstores, and once in a while you make household purchases there. Thanks to the advanced data collection technologies offered by today's personalisation tools, the e-shop knows very well who you are and your shopping history as soon as you arrive. So, for example, the homepage already tempts you with a "tailor-made" selection of goods. This is either to save you a trip to your usual shopping destination or to "throw" more items into your basket that get "lost" among other products along the way.
These so-called recommendation areas accompany you in every major e-shop in all steps of the shopping process - i.e. on the homepage, when selecting products in individual categories, but also - and most often - on the product details themselves. Recommendation systems are even smart enough to recognize if you are not interested in the product you are looking at (for example, if you "move" your cursor away from the picture and description). So the recommendation areas below are cleverly placed to immediately entice you to choose, for example, a suitable alternative.
And we can't forget the popular "add more" trick in the basket, where you entice the customer at the last minute with good deals on products, for example, in combination with products already placed in the basket. Some e-shops go even further and try to speed up your purchase or "discount" by offering smart product bundles, where you can throw a product into the basket with its most frequently sold accessory at the click of a button. This, of course, helps merchants to increase sales substantially, as you wouldn't even know about the existence of the add-on through the standard shopping route. Beware, this is not an unfair business practice - customers are "lured" to buy in this way every day, even in brick-and-mortar stores. For example, buying goods "at the last minute" from the shelves that line the checkouts. Eshops only use the advantages of the virtual world, which allows them to dynamically change and adapt individual goods to the customer's needs as they pass through the store.
But of course, recommendation systems or even smart searches can also target "unidentified" visitors - all those they don't have enough data to identify at the moment. For such purposes, so-called cookies are most often used, or data freely available about the device from which you access the e-shop from your web browser (the so-called "device fingerprint"). This data can serve partly as a substitute for identifying an already known user and matching their purchase history, or it can provide valuable data about what type of goods you are interested in at the moment, and what to offer you when you click on the search window or in the next step of the purchase process.
So why go down the AI personalization route? By doing so, eshops offer customers a faster path to the product they're actually interested in (i.e., they practically shorten the buying process itself). At the same time, they significantly increase their chances of better conversion rates, an increase in average order value thanks to cross- and up-selling opportunities. Last but not least, search and recommendation tools also increase the so-called engagement, i.e. the interest of customers in the recommended goods and strengthen the customer's relationship with a particular e-shop.
Predictive analytics
Another use case is predictive analytics. AI deep machine learning models can be used to automatically adjust prices based on demand, predict customer needs and/or optimize product supply. By doing so, e-commerce businesses can avoid surplus or shortages of goods and improve the efficiency of their business model. The ability to react efficiently and "real-time" to market needs is already proving to be a key factor, especially for large players such as Zalando, Amazon, etc.
Imagine that you own a successful e-shop that sells groceries on the Czech market and, based on market analysis, you have found it promising to expand into Austria and Germany. You are planning to open new warehouses in our neighbours, but how to estimate the initial stock level for such fast-moving goods, which are also largely perishable? This, too, can be solved today with smart software that can not only analyse your online shop based on input data, but also compare it in terms of estimated purchases with your competitors, and thus provide qualified stock estimates for - not only - the first months after launch. Basically, such software can save you the work of an entire team of purchasing specialists these days.
The advantage of such tools, which nowadays always work on the basis of artificial intelligence, is also that the more data you provide them with for the initial calculation (and continue to provide over time), the more accurate they are thanks to their self-learning capability. In other words, they learn from their own deviations. Thus, over time, the deviations from the real state steadily decrease and the risk of error in the calculation is minimized. The only condition is a sufficient volume of data to the so-called "cold start", i.e. in practice the first qualified estimation.
Process automation
Another use is "purchase automation". We are referring primarily to communication with smartly trained chatbots to speed up responses to queries and faster selection of goods (e.g. even faster than via smart search). Chatbots use AI to provide fast and efficient answers to customer queries. They can be programmed to help customers with product selection, answer questions about orders, or provide information about product availability. This reduces the burden on customer support and increases customer satisfaction.
Can't decide which type of clothing fits you and don't want to go through the categories? For example, do you need a men's shirt size M, ideally with a check pattern in dark blue, and matching trousers size 34? A smart chatbot can process exactly this type of query in a fraction of a second and answer it efficiently. Imagine, in essence, a shopping advisor with a built-in language model that knows perfectly the entire catalogue of thousands of fashion items in your e-shop and actually recommends not only suitable products, but also their combination to your customers in real time.
In practice, you won't lose customers who get "lost" in the standard navigation by searching or browsing through the categories and don't complete the purchase for whatever reason. Such a chatbot also fundamentally helps user retention. If it gives you good advice on a purchase, you will probably remember this eshop the next time you need to make a purchase...
In the field of e-commerce, there are numerous opportunities to leverage artificial intelligence to enhance services and create a competitive advantage. Personalization of services, process automation, better customer understanding, improved search capabilities, and chatbots are just a few examples of how e-commerce companies can utilize AI. In the coming years, especially in e-commerce, it will be absolutely crucial for companies to transform their approach and adopt modern technologies like AI, which can help them move forward and deliver top-notch services to their customers.
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