Trade 4.0 – an introduction

Artificial intelligence, machine learning and trade 4.0 – you will certainly have come across these terms already. But what’s up with these buzzwords, where are the new digital technologies being used and what are the opportunities for e-commerce? Today’s article will tell you everything you need to know.

What is artificial intelligence, What is machine learning and trade 4.0?

Artificial intelligence (AI) describes algorithms that enable computers to imitate human behaviour. Machine learning is a component of artificial intelligence. Here, the algorithms are trained to continuously collect information like a human being and to learn from it how to better solve the task assigned to them. What is special about machine learning is that algorithms are not taught the rules of behaviour; instead, intelligent computer programmes learn this from the collected data itself.

A look into the history of artificial intelligence will help to understand the current state of developments.

As early as in 1997, the IBM computer Deep Blue defeated the then reigning world champion Garry Kasparov in chess. The victory of artificial intelligence in the strategic board game made big waves and increased interest in new computer technologies enormously. Deep Blue consisted of a computer with ground-breaking computing power, but which did not learn from the features of its human opponent but calculated the advantages and disadvantages of each possible move. Thus Deep Blue was not based on machine learning and could not generate new knowledge.

Chess Grand Master Gary Kasparov, left, comtemplates his next move against IBM's Deep Blue chess computer while Chung-Jen Tan, manager of the Deep Blue project looks on in New York, Saturday, May 3, 1997, during the first game of a six-game rematch between Kasparov and Deep Blue. The computer program made history last year by becoming the first to beat a world chess champion, Kasparov, at a serious game.(AP Photo/Adam Nadel)

The AI Deep Blue in the game against Kasparov 1997: Intelligent, but not capable of learning. Source: engadget.com

The real triumph of intelligent computer applications that can perform machine learning began just a few years ago. This has partly to do with the big data revolution, which is now also penetrating medium-sized companies. The collection of ever more extensive data also intensified research into how these data can be evaluated. The developments in data generation and evaluation were made possible by the exponentially increased computing power of modern computers.

In the meantime, research on artificial intelligence has made huge strides in many areas. From self-propelled cars to healthcare, there are many exciting prospects for innovation in the near future. Most of them are based on self-learning algorithms that gain their experience from huge data pools.

Retailers are also increasingly using artificial intelligence to make processes more efficient. Analogous to industry 4.0, we can therefore use the term trade 4.0. Which processes are suitable for automation?

Current AI trends in trade 4.0

No more confusing websites with irrelevant offers – machine learning is used in e-commerce, among other things, to learn what customers want and thus optimize their experience. The streaming provider Netflix, for example, uses machine learning to provide a personalised range of films and series. The more content a user looks at on Netflix and evaluates after viewing, the more precisely the algorithm of the streaming service limits which other content might be of interest.

Netflix uses machine learning specifically to optimize the user experience. Source: neilpatel.com

Netflix uses machine learning specifically to optimize the user experience. Source: neilpatel.com

The topic of fraud detection through artificial intelligence is also becoming more relevant. According to this study, between 2015 and 2017, the number of fraud cases in e-commerce increased by an average of seven percent in all industries surveyed. Internet fraud takes many forms, ranging from unpaid bills to the theft of digital identities. What is the best way to protect yourself against Internet fraud? Artificial intelligence gives you the opportunity to learn from online scams of the past and prevent them in the future. In addition, a self-learning algorithm recognizes those order characteristics that indicate an attempted fraud, classifies them and sounds the alarm.

Artificial intelligence is revolutionizing even more areas of e-commerce. We have put together a few for you:

#1 Retail in Transition: Business Intelligence meets AI 

#2 Retail in Transition: Artificial intelligence in action 

Trade 4.0 – challenges and opportunities in the implementation of AI

Artificial intelligence offers promising solutions for e-commerce in many areas. These innovations also pay off for the corporate strategy as a whole: with an intelligent automation strategy, you increase efficiency and at the same time reduce costs and risks. Because one thing is clear – machines perform their tasks reliably; the risk of manual errors is minimized.

Artificial intelligence enables significant increases in efficiency

Artificial intelligence enables significant increases in efficiency

It is very tempting to use artificial intelligence, but it must be done correctly; often the company lacks the visions on how to use the collected data precisely, for instance from its own website. Only when you are aware of the value of the data can your big data strategy be successful!

In general, artificial intelligence is only as good as its database. This is most often the key problem. Self-learning algorithms often receive poor quality data. In addition, most companies face structural challenges; there are simply too few data analysts to be able to initiate far-reaching transformation themselves. This is why it often makes sense to cooperate with a specialized partner company.

Market analysis in trade 4.0

The internet has created worldwide distribution opportunities and, with this, globalized, complex e-commerce markets. At the same time, as an e-commerce provider you usually have little capacity in your day-to-day business to keep a constant eye on your direct competitors, not to mention new competitors that may enter the market. This mass of information is impossible to filter manually.

Innovative machine learning technologies such as blackbee Insights bring you important gains in efficiency. blackbee Insights collects all relevant product and price data for you worldwide. The outstanding data quality and the unique matching technology of blackbee guarantee that you have clear competitive advantages.

See for yourself! Test the intelligent market analysis tool blackbee Insights now.