Applied Examples of Artificial Intelligence in Digital Marketing

The fear of losing one’s own workplace through Artificial Intelligence also causes displeasure among marketers. I’ll try to figure out how you can see the use of artificial intelligence (AI) in digital marketing as an opportunity and regain time for strategic, creative marketing.

How does Artificial Intelligence change digital marketing?

It may seem strange to some that machines increasingly seem to replace (or supplement) human intelligence. In everyday life, however, artificial intelligence has long since arrived and is widely accepted, depending on the field of application. In times of big data and driven by AI, the job of the marketer is not to collect enough data about the customer. Rather, it consists of efficiently evaluating the data and deriving concrete recommendations for action from them.

AI is already one of the most important technology today. Self-driving cars and robots are just a few of the hottest examples of artificial intelligence currently being discussed. In fact, the terminology of artificial intelligence has existed for over 60 years, describing technologies and systems that can learn how to act using large amounts of data.

The Google search engine is one of the world’s most famous AI inventions. The technology searches innumerable sources and displays the matching search results within seconds. The aim of artificial intelligence is to support people rather than replace them. Especially in digital marketing, technology has proven to be a supportive hand so far.

As part of the customer journey, the majority of customers are moving along a number of digital touch points. As a result, organizations are increasingly being asked to provide customers with the best possible user experience: faster, more personalized, and more digital than before.

It is all the more important for marketers to be able to derive concrete findings and measures from the collected user data. But so far they are not. According to the Wunderman study, 62% of marketing decision-makers are unable to use the company’s own data for marketing activities. This is despite the fact that 99% of respondents believe that data already determines the success or failure of marketing and sales today.

What opportunities does artificial intelligence offer for digital marketing?

So what can the interplay of data and new technologies look like in this age of increasing digitization? For example, through the targeted use of artificial intelligence? With the help of AI, marketers can handle the huge amounts of data that big data delivers.

It is not about the comprehensive possession of data, but rather to be able to identify and filter out the right data in order to develop patterns that can then be used profitably in the company. The task of AI in digital marketing is therefore to support data analysis and to evaluate the data. And in speed and a scope that humans cannot afford.

The use of artificial intelligence in digital marketing offers the opportunity to realize targeted and individual campaigns, which reach the customers at the right moment and offer high investment potential. For this reason, it becomes all the more important for marketers to understand and engage with self-learning technology. Especially in the digital industry, they should stay on the ball, which investments, technologies, and innovations will dominate the market. At best, even before the competition does.

Those who miss out on fear of change will not only be overtaken by the early adopters and pioneers, but will also miss the opportunity to hand in cumbersome data analytics, campaign driving, or customer and lead generation to the machine.

So how can Artificial Intelligence be used in digital marketing? In the following, I present 10 application examples for the use of artificial intelligence in digital marketing.

1. Digital language assistants in daily life

One of the keys AI trends in 2018 was a digital voice as Google Assistant. They are becoming increasingly popular and follow users in their daily lives. More and more companies are using them for their products and services. Here, content marketers and SEOs should especially integrate the topic of language search in the marketing mix.

2. Evaluation of Big Data Analytics (Big Data Analytics)

The work of marketers is constantly changing as a result of digitization. While a few years ago they had mainly worked out creative and strategic concepts for campaigns, most of them are now dealing with large amounts of user data, Google Analytics & Co. through the use of Artificial Intelligence In the evaluation of these data volumes, the technology can create targeted reports through competent support, which form the basis for targeted marketing measures.

3. Pattern recognition in the usage behavior of the customers

Data is the basis for almost every digital marketing measure. The use of AI on web pages can recognize certain patterns of behavior of potential or converted customers and provide them in the form of detailed reports to the marketing. Based on this insight, marketers can make decisions about future marketing measures and activities and, with the help of the AI, address new, strategically meaningful target groups.

4. Classification of websites and advertising content according to relevance

The AI ​​technology can learn when playing advertising content, on which websites the content should be displayed and on which not. It classifies the websites or website contents. On the basis of existing data, the technology recognizes and assesses whether the advertising content environment can be qualified as “brand safe”.

If this is not the case, it can prevent the delivery of advertising on this website. Also website content such. B. product recommendations or personalized home pages, can be equipped with AI and thus individually adapted for each user. The technology can evaluate which content works with which customers and enables uninterrupted AB testing.

5. Automated control of marketing campaigns

Through the use of artificial intelligence, advertisers can benefit above all in email marketing and in the control of campaigns. The technology can automatically target, evaluate and adjust marketing campaigns in real time.

Keywords such as “real-time bidding”, “programmatic advertising” or “search advertising” are increasingly emerging as part of digitization and have been operating for many years mainly through the implementation of AI technology. Marketers can decide if they want to automate their marketing campaigns (using AI) or manually target and optimize them.

6. Hyper Targeting

Hyper Targeting describes the personalized automation of ads and customization of advertising content to an individual user through the implementation of AI technology. Potential customers benefit from this type of targeting, as do businesses. Because consumers only see content relevant to them. To make this possible, an algorithm is used that analyzes the user data.

In this way, it is possible to determine in which phase of the purchasing process consumers are stuck and which advertising media might work best. The algorithm remembers the results of the analysis and continues to learn. In Programmatic Buying, For example, AI calculates which ad space is most profitable for the advertisers and tests countless variations within fractions of a second.

7. Chatbots in customer service

The chatbots use artificial intelligence and a learned algorithm that contains the most important data the Chabot needs to know. He is particularly in the customer service on the website or in social networks such as Facebook used.

Currently, they are used for simple customer inquiries, such as travel or product inquiries. In the future, however, the communication between the customers and the Chabot can be made much more individual and personal in order to speed up and improve customer service. With Artificial Intelligence, bots learn with every customer conversation and deliver better results.

8. Behavioral predictions

The e-commerce giant Amazon and streaming service provider Netflix make it happen: With the help of the recommendation AI can reliably predict how a customer will behave at any given time. For example, Amazon achieved about 35% of its annual sales in 2013. With AI, companies can make automated product proposals.

Another example: Intel’s subsidiary Saffron has developed an AI that can predict with up to 88% accuracy on which channel and for which product a customer will ask for help.

9. Personalized content/content creation by the algorithm

Artificial intelligence instead of human editors? AI also offers a variety of application possibilities in content marketing. For example, when creating content. This is especially true for texts based on certain rules, such as financial announcements or sports scores.

In addition, the AI ​​can classify large amounts of text, compress and independently evaluate various wordings and sources to optimally address a target group. The necessary data is usually available in the companies, but the necessary resources to evaluate this data and address individual user groups, but not. The use of AI can help because technology can significantly improve the use of data.

Artificial Intelligence has just begun. For the marketer, this means above all to deal with the key issues around the topic of AI and to question what effects are on the individual customer, but also on society and the economy through AI.

Conclusion

An integral part of marketing is and remains human action, even when using artificial intelligence. AI offers great potential to accelerate, simplify and constantly optimize digital marketing in real time. AI technologies can be used throughout the customer journey of a prospective client, and access and address new audiences based on data.

The potential uses of AI will continue to increase over the next few years. However, Artificial Intelligence also reaches its limits. Many AI technologies are far from bug-free and can only diitperate on the parameters that marketers have defined for them. The basis of the AI ​​comes from a human hand and mistakes can happen during programming.

They cannot learn completely independently on the basis of their own experience, or they can take new solutions themselves, but require constant control, care, and care by humans. Marketing and digital experts will continue to bridge the gap between advanced technology and the human mind.