AI in marketing: how efficient marketing works

Artificial intelligence (AI) is no longer a futuristic term, but has become a key driver in many industries - including marketing. Its use is fundamentally changing the way marketing managers work. Large amounts of data can be analysed or repetitive, time-consuming tasks automated in no time at all. The potential of AI in marketing is enormous and can fundamentally change a company's marketing.  

In this blog, we will therefore show you how AI is redefining marketing, what benefits it offers and how companies can start using AI for themselves. Whether you're a small start-up or a large enterprise, understanding and implementing AI can give your marketing the kick it needs. 

The categorisation of different terms 

In order to recognise the full potential of artificial intelligence in marketing, it is first necessary to have a basic understanding of the associated terminology. Artificial intelligence (AI), machine learning (ML), algorithms and predictive analytics are not just buzzwords, but fundamental building blocks that form the backbone of modern marketing strategies, which is why it is important to have a basic understanding of them. We therefore explain these terms and their interrelationships below:

Artificial intelligence (AI): This is the overarching field that deals with the creation of machines or programmes that can perform tasks that require human intelligence, such as visual perception, speech recognition, decision making and translation between languages. 

Machine learning (ML): ML is a subfield of artificial intelligence that focuses on the idea that systems can learn from data, recognise patterns and make decisions with minimal human intervention. AI leads to ML, which means that ML is a method to achieve AI.

Algorithms: In the context of ML, algorithms are the specific processes or rule sets that the machine follows to perform tasks, learn from data and improve over time. Algorithms are at the heart of machine learning and enable computers to recognise patterns in data and make predictions based on them.

Predictive analytics: Predictive analytics is a method for predicting future events. It uses machine learning algorithms based on the analysis of historical data to derive future developments. Predictive analytics is used in various areas. The spectrum ranges from risk assessment and the prediction of customer behaviour to the optimisation of marketing strategies, making it an indispensable tool for data-based decision-making.

General fields of application for AI

Since the release of the best-known AI tool, ChatGPT from OpenAI, AI has become ubiquitous. However, many people do not realise that the application of AI goes far beyond pure speech processing (like ChatGPT) and that AI offers a wide range of applications. Four main fields of application for AI can be identified: Language processing, image processing, expert systems and robotics.

Language processing, often referred to as natural language processing (NLP), enables computers to understand, interpret and generate human language in written or spoken form. Applications in this area range from speech recognition software such as Siri and Alexa to translation services such as Deepl. By processing natural language, AI can analyse texts, recognise the mood behind words and even understand and answer complex questions.

Image processing by AI includes techniques that enable computers to interpret visual information. This ranges from recognising and classifying objects in images to generating new images or videos. Examples of applications include facial recognition systems, automatic inspection systems in production, improved medical imaging and the development of autonomous vehicles. The ability of AI systems to recognise complex patterns and structures in visual data has brought about revolutionary changes in areas such as security, medicine and the automotive industry.

Expert systems are a category of AI that aims to emulate the knowledge and decision-making skills of human experts. They are used in specialised areas to solve problems or make recommendations based on rules and data. By integrating expert knowledge, these AI systems can make supportive decisions based on extensive data analyses and help to reduce human error.

Robotics as a field of application for AI is concerned with the development of robots that can perform tasks autonomously or semi-autonomously. AI enables robots to learn from experience, adapt to new situations and solve complex problems. This is used in manufacturing, where robots perform precise and repeatable tasks, in agriculture for automated harvesting, in medicine for surgical procedures and in research and rescue under difficult conditions. The combination of AI and robotics leads to systems that not only perform tasks, but can also interact with and improve their environment.

How is AI changing marketing?

As already explained in the last chapter, AI offers a wide range of possible applications that also extend to marketing. The question arises as to what extent AI is used in marketing and how AI will change marketing. To answer this question, we have listed the most important areas of influence below:

1. Customer analysis and segmentation

With the ability to analyse huge amounts of data, AI makes it possible to gain deeper insights into customer behaviour and preferences. Machine learning and algorithms identify patterns and trends that human analysts might overlook. This leads to more effective segmentation of target groups and enables companies to develop customised marketing strategies.

2. Personalised customer experiences

The days when standardised advertising messages were enough are over. Today, customers expect customised experiences that meet their individual needs and preferences. AI technologies such as the recommendation algorithms behind many online platforms make it possible to deliver personalised content, product suggestions and messages in real time.

3. Automation and efficiency

KI automates numerous marketing tasks, from customer segmentation and content creation to email marketing. This automation not only saves time and resources, but also increases the accuracy and effectiveness of marketing campaigns. Chatbots and virtual assistants, for example, offer round-the-clock customer support without the need for human staff to be constantly available.

4. Predictive analytics and decision-making

The use of predictive analytics enables companies to predict future trends and customer behaviour. This makes it possible to act proactively instead of reacting. For example, AI-supported tools can predict which products or services will be popular with certain target groups or recognise when the best time to send marketing emails is.

5. Content creation and management

AI is also becoming increasingly important in content marketing. Tools for AI-supported content creation can help to produce relevant and appealing content more quickly. AI systems can also help to analyse the success of content and make recommendations for future content strategies.

Opportunities of AI in marketing

The potential uses of AI in marketing are diverse. The use of AI in marketing therefore also offers a number of advantages. These include:

• Improved customer knowledge and segmentation: By analysing large amounts of data, AI can provide deep insights into consumer behaviour. This enables more precise customer segmentation and targeted marketing strategies.
• Real-time personalisation: AI enables personalisation that goes far beyond simple product recommendations. By utilising learning processes and data analysis, AI can create individual customer experiences, which increases customer satisfaction and loyalty.
• Automation and efficiency: Automating repeatable and time-consuming tasks not only saves costs and time, but also reduces human error. AI can work around the clock, enabling constant customer support and interaction.
• Prediction and decision support: Predictive analytics enables marketing managers to predict future consumer trends and behaviour. This leads to more informed decisions and a proactive rather than reactive marketing strategy.

Challenges of AI in marketing

In addition to the major advantages of AI in marketing, it is also important to understand the challenges that AI brings with it. In order for AI to be used in the company, an understanding of these is absolutely essential. These include:

• Privacy and ethical concerns: The use of AI in marketing requires access to large amounts of consumer data, which raises issues of privacy and data security. Companies must ensure that they act ethically and respect customer privacy. It is therefore essential that employees use AI tools appropriately and comply with customer privacy regulations to avoid any breaches.
• Over-reliance on technology: Over-reliance on AI can lead to human intuition and creativity being undervalued. While AI can efficiently recognise patterns, it lacks the ability to be truly creative or demonstrate deep human understanding.
• Misinterpretations and errors: AI systems are only as good as the data that feeds them. Distorted or incomplete data can lead to incorrect analyses and decisions. This could have serious consequences. Companies must be aware that data quality is of crucial importance and should also develop a process accordingly to ensure the quality of the data.
• Displacement of jobs: Concerns about the loss of jobs in marketing due to AI automation are understandable, but the reality is different. AI does not replace marketing specialists, but supports them. The technology automates routine activities and allows marketing managers to focus on more complex and creative tasks. In addition, AI-generated content still requires careful review by specialised personnel to ensure its accuracy. AI is therefore not so much a replacement as a valuable tool that increases efficiency and opens up new possibilities in marketing.

Practical application examples of AI in marketing

The application of artificial intelligence (AI) in marketing is diverse and constantly growing. Here are some specific examples of how AI can be used in marketing: 

Example 1: Product recommendations

The use of AI can significantly improve the customer experience. AI platforms can analyse large amounts of data to determine which products, types of content, designs and messages are most effective for different target groups. One example of this is product recommendation systems. These systems use past transaction data (e.g. purchases, bookings, orders) to develop customised product suggestions for all customers.

The recommendations are based on statistical frequencies: When a customer buys a product, the system analyses what other customers have bought in addition to this product. Customised product recommendations can then be displayed based on this information.

Example 2: Marketing analytics

AI technologies such as machine learning and predictive analytics are also used in marketing to analyse and interpret data. AI can recognise patterns and trends in large amounts of data that are too complex for humans to understand. This enables marketing managers to better evaluate the effectiveness of their campaigns and make informed decisions about how resources should be allocated for maximum impact.

Example 3: Content creation

AI is increasingly being used to support and optimise the content creation process. The fast and automatic generation of high-quality texts reduces the effort required to create texts enormously. AI-driven tools can help to identify relevant topics and keywords, create initial drafts for blog posts, social media or advertising texts or even entire product information. The texts are created at the touch of a button, but must then be refined by human editors. Using these tools saves time and ensures consistency across different content formats.

Example 4: Search engine optimisation (SEO)

AI tools can also be of great benefit in the field of search engine optimisation (SEO). Not only can they help to identify the right keywords for texts, they can also generate entire metatexts (titles and descriptions) that are optimised for both search engines and potential readers. By understanding and applying SEO best practices, AI systems can help improve the visibility and ranking of content in search engines. Read our blog post "AI and SEO" to find out more about how artificial intelligence can help with search engine optimisation.

Example 5: Chatbots  

More and more customer enquiries are being made digitally, as waiting on hold by phone is no longer an attractive option for customers. The switch to digital service processing such as chats and emails offers the opportunity to process more enquiries per employee. On the other hand, it also enables automation. This is where chatbots come into play. There are already many bots on the market that have been developed with AI. The chatbot's AI makes it possible to correctly prioritise incoming enquiries and assign them to the appropriate departments - be it marketing or customer service. The algorithm can then decide whether it is a problem that can be answered automatically. This can be done, for example, by referring to FAQs, a link or other digital solutions.

Successful implementation of AI in the company

You have now learnt where AI can be used in marketing and what risks and opportunities are associated with its use. If you now want to firmly integrate artificial intelligence into your company's marketing processes, this step requires careful planning and implementation. In the following, we will show you what you need to consider during implementation and how you can proceed based on the three pillars of employees, organisation and systems:

1. Employees 

A decisive factor for the success of the introduction of AI technology is the unity and cooperation of all those involved. It is extremely important to secure the consent and active involvement of the workforce at an early stage. Teams need to be fully on board before the crucial integration of AI. Furthermore, it is crucial that employees fully understand and accept both the opportunities and risks of AI. Training on data protection or general information campaigns on AI are essential to teach employees the right way to deal with AI. Further training also helps to deepen knowledge about how AI works and dispel any doubts.

2. Organisation

The introduction of AI has an impact on the entire organisation and its way of working. New processes and workflows need to be defined and implemented in order to realise the full potential of AI technology. This may require adjustments to the organisational structure and the reallocation of tasks and responsibilities. An open and transparent communication style within the organisation is therefore essential to prepare employees for change and encourage their collaboration with the AI systems.

3. Systems

Finally, the company's technical infrastructure must also be designed in such a way that the integration of AI in marketing can take place seamlessly. This requires the establishment of integration points through which AI systems can communicate effectively with existing company applications and data sources. It is important to ensure that the implementation of AI does not disrupt or interfere with existing processes. Looking at your own IT infrastructure, selecting suitable software solutions and developing a clear integration strategy are therefore crucial for success in this area.

Conclusion: The future of marketing with AI

The integration of artificial intelligence is fundamentally changing marketing and offers companies both opportunities and challenges. The use of AI in marketing is seen as an exciting development that has the potential to fundamentally change the way we interact with customers and conduct marketing. The ability to provide personalised customer experiences in real time and make marketing decisions based on sound data and predictions is fascinating.

However, it is important to keep ethical and privacy issues in mind and ensure that the technology is in line with consumer needs and expectations. A holistic approach to the integration of AI that takes into account both technical and human aspects is therefore essential and the key to sustainable success.