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How Artificial Intelligence Automates the Content Generation Process

Artificial intelligence (AI) is no longer a new topic. Companies are using this technology to optimise their business processes and improve their competitiveness. One area where AI can be particularly useful is in automated content generation. In this article, we will look at how AI can be used to quickly and scalably create media content to meet the needs of the target group, to recognise the moods of customers and, for example, to optimise price communication.

A/B tests

A/B tests are an effective means of finding out which content pieces of a campaign or which version of a single post, for example, are better received by the target group. However, the creation of different versions by mostly external partners is very time-consuming and above all cost-intensive. AI can help here. Not only by automatically creating several versions based on a template, which can then be tested. But above all in the creation of the template. Let's take an animated post with a simple structure as a basis: Background, headline and subline, product in focus.
What is possible here by combining different AI tools:
Generation of different background images according to the character of the product in combination with the attributes and preferences of the target groups or simple extension of reference images (outpainting) for optimal use across multiple formats.
Generation of headline and subline versions according to selected target group and their interests, also multilingual
Composition of the elements into a perfect post-visual
But that is not all. After the test has been carried out, the AI analyses the results and thus enables targeted optimisation.
Effort for the marketer with the AI: 15-30 minutes (incl. coordination rounds, no coordination effort necessary).
Effort for the marketer with external partners: 2-3 days (incl. coordination rounds and coordination)

Mood creation

As mentioned earlier, AI can analyse the results from A/B testing and make recommendations for optimisation. This can be done after a defined test period. However, AI can also directly detect and interpret the mood of customers. For example, text analysis and image recognition can be used to create tools that can capture the mood of the target group in real time. The results can then be used to create personalised content that is tailored to the respective mood and played out on-demand. The reaction time is shortened immensely, the customer can be "caught" directly or picked up again. This increases the user's interest in the product, he becomes a customer and customer loyalty can be strengthened in the long term.

Price communication

Using AI to optimise price communication is another area where companies can benefit. By analysing customer data and customer feedback, AI can, for example, help to optimise prices for products and services. Of course, this is done within a defined margin in which the price can move up and down. The design of the offer, for example, can also be taken over by AI, see A/B testing and mood creation.
In an article on the future in the retail media sector ("Wie Schwarz Media das Geschäft rund um Lidl und Kaufland ausbauen will", Horizont Online Version from 27.07.2023), Professor Antonio Krüger, CEO of the German Research Centre for Artificial Intelligence (DFKI), is indirectly quoted: He still sees great potential, especially in online retail, for addressing target groups by linking texts and images. In the in-store sector, he expects more opportunities for product recommendations.
This also confirms our experience. AI is a powerful tool that can help companies optimise their content generation process and better address their customers. If companies use this technology wisely, they can be more competitive and boost their business growth.

Finally, it is worth mentioning: Of course, it depends on the quality of the tools you want to use and that they are perfectly in line within the content production pipeline. The current amount of AI tools can quickly drive you to despair and the time to test all of them individually for their area costs a lot of time that you don't have as a brand manager and marketer. We have been dealing with the different AI tools of the various application areas for years and have set up a production pipeline within VARYCON with the best selection.

We would be happy to explain our approach and how we have set up the production pipeline using a demo case - please feel free to contact our consultant Barbara Stadler.

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