Online-shops are operating in an environment that has changed rapidly over the last 10 years. Small companies in the online trade are already throwing buzzwords like "Machine Learning", "Artificial Intelligence" or "Recommendations" around. An essential driver of this progressive thinking is artificial intelligence (AI). Large, well-known market leaders such as Amazon and Zalando have long since relied on AI to improve internal processes and ensure a more pleasant shopping experience. In order to assert themselves against this strong competition, online retailers should take a close look at the potential of the technology and select the right application areas for themselves.

In this blog article, we'll show you how artificial intelligence is turning online retailing on its head, what kind of pitfalls you should look out for, and how a much better solution for online retailing will definitely make you outperform your competitors! 

Artificial Intelligence - What's behind it?

Artificial intelligence (AI) is the generic term for applications in which machines perform human-like intelligence tasks such as learning, problem solving and judgment. Machine learning technology (ML) - a branch of artificial intelligence - helps computers learn from huge amounts of data and many tests. This allows tasks to be performed better and better. Sophisticated algorithms can recognize patterns in unstructured data sets such as images, texts or spoken language and make decisions based on these patterns.

AI makes it possible: The right product at the right time?

Amazon shows it off, everyone else jumps after it. In the world of online retailing, "Recommendations" (or Recos for short) in technical jargon are legendary. It is claimed that the way it works is secret, just like the Coca-Cola formula. But the magic behind the slogan " You could also like" is easy to explain. Shop users are compared with previous customers who resemble them in behavior and personal characteristics. This forms the basis, on which finally further articles are faded in as product recommendations, for example on product detail sides.

If the user has looked at product A, then product B is recommended to him - because this is an article that customers often bought in addition.  However, the assignment of customers to segments is extremely inaccurate because it is model-based. In addition, many recommendations only refer to the recommendation spectrum of the selected product category. For example, if a user looks at a sweater, only suggestions for further sweaters are displayed. However, the fact that he actually wanted to buy a matching pair of jeans is not taken into account.

Often the articles do not fit the interests of the users, are simply offered in different colors or designs and lie outside the needs of the customer. What the users really want to see is rigorously hidden. Inspiring product recommendations look different.


Machine intelligence & gut feeling combined

Whether at Zalando, AboutYou or Douglas: The personalized product stream is one of the hottest features in online retailing! Machine learning algorithms analyze shopping behavior and assign the current user automatically to predefined customer groups. In order to play out the optimum product feed, this imprecise classification can be followed by further refinement through human influence.

This combination of curated shopping and model-based customer approach ensures that online shoppers are shown personalized product streams and can also incorporate their own input. At Zalando, this personalization is now taken over by a new product feed called "MyFeed". Here customers are given the opportunity to answer specific questions about trend favourites, favourite brands or physical conditions so that the visitor profile can be filled with precise information.

But be aware: This technology is not "top" for every online retailer and can quickly develop into a "flop"! Functions like this can cause costs in the five-figure range and represent high implementation costs. In addition, this method can only be used for users who are already logged in or known. The motto is: No customer data - no tailor-made shopping experience.


Omnichannel-Online-Shopping-InStorePersonalized product streams are a good, first step - but you don't yet fully satisfy the individuality of your shopper.


KI meets customer: this is how customer dialogue works around the clock

Like a tornado, technological progress is blowing around the world, not least changing consumer expectations. So if you want to survive in the e-commerce world, you have to be innovative and combine visual, written and predictive skills. So in order to drive business forward in this new era, artificial intelligence chatbots are a particular innovation of the many business strategies evolving through digital transformation.

A chatbot is a specific computer program designed to stimulate conversations with human users over the Internet. With the help of digital advisors, online merchants gain important insights into customer needs and problems that arise. At the same time, customers benefit from fast service and no waiting loops. A text analysis is necessary to understand the customer's intention and to respond to his needs.

The discounter Lidl has now launched a text-based dialogue system that draws on a knowledge database and thus enables dialogue with users. Anyone who wants to know which products are currently on offer at Lidl, where the nearest store is or when the food order arrives at home can now have the information provided by a machine. On the social media platform Facebook, "LiA" (short for Lidl Assistant) is available with real-time information via a dialog window in which questions to the Lidl Assistant can be entered. This is because customers want customer-centric support that is both efficient and precise as well as customer-oriented. This is the only way to solve individual problems quickly, easily and successfully.

Machine Learning-Roboter-1

Support requires efficiency, precision and customer focus. Make use of your existing data and secure a real competitive advantage through individualized service experiences.

Situationalization puts artificial intelligence in the shade

There is no question that artificial intelligence brings a breath of fresh air to many areas of online commerce. But in many cases the efficiency and effectiveness of this technology can still be optimized, as it reaches its limits more quickly due to the enormous customer requirements and the ever-increasing amount of data.

ODOSCOPE's situation rationalization represents the way out of this impasse, in which many online retailers are stuck because they have followed the major market leaders.

Situationalization is a method for the optimization of digital channels with which each user can be shown the most relevant content with the highest conversion or purchase probability in real time. By using this technology, you not only compete with the big players, but are even one step ahead of them.

Instead of surfing behavior and personal data, the situationalization solution uses situational information to characterize users: Whether they are in a metropolitan region or a rural area, use an Android Tablet or a Microsoft PC, and whether they come via the shop newsletter or a Facebook Ad, has a surprisingly large influence on their current interests and buying behavior. Based on these situational characteristics, online merchants can tailor their shops to each individual user - from the first moment of his visit and regardless of whether he is known or anonymous. In addition, this method is 100% DSGVO compliant, because the actual identity of the shop visitors does not matter.

The underlying Operational Intelligence technology goes further than artificial intelligence and works on the basis of a comparison with similar users - in this case those who find themselves in a similar situation to the current visitor. The group of statistical siblings is therefore much smaller and more precise. In this way, retailers really do justice to the diversity and individuality of online shoppers. Prescriptive analyses play out the shop elements with the highest conversion probability for the statistical siblings  fully automated in milliseconds.

Superkraft-Businessman-mSituationalization of ODOSCOPE gives your business the ultimate superpower!

Situationalization puts your business in the fast lane

With Situationalization, the entire shop can be tailored to each individual visitor - in terms of address, content and products. The individual re-sorting of product lists, for example, is particularly promising: browsers get more relevant products displayed on the 1st page - without any time-consuming search. So, they feel directly addressed, stay and buy more. This allows product feeds to be much more tailor-made through Situationalization, without users having to help much, or online merchants having to take a hand themselves!

In addition to improved product recommendations, product streams and offers, the solution represents an enormous added value for the service of the online shop. The ODOSCOPE platform consolidates data from all silos. These are full of valuable information about the customer, his needs and previous interactions, which can be used intelligently for an individual service experience.

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