Artificial intelligence (AI) is one of the key technologies of the future and will change marketing over the next few years. The word “revolutionary” is probably one of the most frequently (inflationary?) Used terms in marketing.
However, in the context of artificial intelligence and machine learning (ML), it could be more than appropriate. Therefore, the interaction of machine learning and artificial intelligence is already considered to be one of the most important topics and advances in the age of digitization.
What Are The Differences Between Machine Learning And Artificial Intelligence?
The two terms are often mentioned in the same breath and differ significantly in words of process and goal. Artificial intelligence and machine learning are not exactly easy to understand on a technical level. Nevertheless, both technologies are important components of (future) digital marketing and are extremely interesting for marketers. ML is a sub-area of AI and learns from and from data based on algorithms.
With the help of machine learning, IT systems can recognize patterns and regularities in existing data and develop solutions. Existing experience and knowledge are used to learn from them and to optimize future processes.
On the other hand, artificial intelligence means detailed applications that imitate human capabilities and can act independently. Simple examples from practice are automatic image recognition or chatbots in messengers and for customer inquiries. In these cases, the AI can recognize certain patterns, analyze them and respond with a suitable solution.
The real revolution, however, lies in the interaction of the two technologies. Machine learning provides real-time knowledge and enables artificial intelligence to continue to improve and grow with new applications.
Turing Test As A Yardstick
When is an IT system considered intelligent? Are our machines already-intelligent today? There is still much disagreement about the answers to these questions. Artificial intelligence is rated differently overall. The much-discussed “Turing Test” is often used as a yardstick for an existing AI seen.
In the course of this test, a human questioner uses a keyboard and a screen without visual or auditory contact to have a conversation with two people he does not know. One of the interlocutors is a person, the other a machine. If the questioner cannot clearly say which of the two is the machine after intensive questioning, the machine has passed the Turing test. As a result, the device is assumed to have a mind equal to that of humans.
Artificial Intelligence In Marketing
Artificial intelligence has made considerable progress in marketing in recent years and is becoming more precise through machine learning. One of the most exciting challenges in today’s age is personalization and individual approach based on AI. Personalization enables long-term customer relationships, a unique approach to different target groups and independent problem-solving.
AI systems often take on a customer advisor’s task, imitate human conversations, and give personal recommendations for problem-solving. However, it is not about completely replacing the human being. Rather, the employee should be given new information and additional knowledge to simplify and optimize their work.
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Artificial Intelligence Topics
Artificial intelligence will develop rapidly in the coming years and will have an increasing influence on companies’ processes and marketing automation. Which areas can particularly benefit from progress?
Generation Of Content
Anyone who regularly has to create content for their website, online shop or blog knows about the time and effort involved in production. Software is already able to write and publish your texts. However, it has to be said that these “text robots” always depend on a good database and that really good texts can only be generated using recurring patterns.
This is currently, for example, content such as sports news, weather forecasts or stock market news that can be structured according to a certain way.
But even in eCommerce, text robots are already doing a large part of the text creation. Based on properties such as material, colour, size, accessories, etc., thousands of product descriptions for online shops can be generated within a very short time.
Of course, this also applies to social media such as Facebook and Instagram. On these platforms, AI can carry out a precise analysis of the interests and expectations of users and adapt the content perfectly to their needs.
Segmentation Of Customer Groups
When we talk about marketing automation or artificial intelligence segmentation, we often mean analyzing user data and user behavior. An analysis and evaluation of the data made it possible to address different target groups with suitable content specifically. The IT systems provide us with information on the purchasing behavior of a certain customer group, for example. In this way, marketing can be adapted accordingly to the buying process or possible upselling show accessories or alternative products are aligned.
Actions and KPIs can be evaluated according to their success and optimized for future measures. However, it must be added that most of the systems are still based on the use of rules and patterns and are not absolutely self-learning.
Personalization Of Content
Often we may not notice the personalization of content in marketing and on websites, but it is already ubiquitous. When there is “a website for everyone” or the time X for “the one newsletter” is over, the topic is constantly evolving.
If you visit an online shop today, the products are increasingly sorted in real-time according to the visitor’s interests and optimized to the highest possible willingness to buy. The system uses thousands of features. Based on gender, age, place of residence, brand affinity, purchase history and many other factors, it can produce the optimal shopping experience for each user.
More technologies with more and more new features will likely be added to the personalization area in the coming years. These are mainly powered by artificial intelligence and machine learning.
Personalization In Email Marketing is one step further. There, the AI already enables many automated steps and optimal sending of emails. The programs recognize the customers’ interests and align the content of the emails with the expected need.
Product recommendations, additional services or even the individual sending of emails at the best time are just some points where artificial intelligence is already being used today.
Big Data As A Driver Of Artificial Intelligence
The development in big data technology has also given artificial intelligence and machine learning an enormous boost. Since large amounts of data are available in artificial intelligence and have to be processed efficiently, big data systems form the ideal basis for successful use cases. With the help of big data, both structured and unstructured data can be analyzed quickly and with relatively little hardware expenditure and fed into the learning algorithms.
Conclusion And How Companies Use The Technology
All of this describes what is possible now or shortly. Which topics will prevail in the end remains to be seen, and there will be other exciting approaches. The technology is still relatively new, and so it is not surprising that many companies still refer to themselves as “beginners” or “newcomers” to the field.
AI enables companies to understand their customers as human beings and interact with them as one would expect from personal contact. The applications are becoming more concrete, and the advantages of the new technology are becoming visible.
Nevertheless, many companies are still obtaining information or exploring opportunities for their processes. Recognizing these opportunities and taking the first step will be a great challenge. However, forecasts say that companies that are the first to master AI-enabled marketing will have a significant competitive advantage.