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How marketers are driving their campaigns and teams forward with generative AI

diconium
Written by diconium

The most important facts in 20 seconds
  • The use of generative artificial intelligence (AI) offers marketing a great deal of potential for content creation, personalization, and market segmentation.
  • The right data basis and strategy are part of the central starter kit for the use of AI in marketing.
  • Specific training courses provide the necessary know-how for AI-optimized value creation.
Agenda

If you look at the stylistic quality of ChatGPT's texts or the photorealistic results of AI image and video generators, it’s clear that we’re seeing a revolution in the field of content creation. However, generative artificial intelligence (AI) can be used to add value not only for the creation of advertising copy or the generation of image and video material but can open new doors in other areas of digital marketing.

Taking campaigns to the next level with generative AI

A Reason Why provides generative AI for content creation: smart AI models support marketing managers in creating content faster, with higher quality and greater variety - from ChatGPT to Midjourney. At the same time, generative AI opens new potential in data analysis and customer engagement. For example, in-depth personalization and the further improvement of customer interaction through AI are becoming increasingly important success factors for tailored and individualized marketing, by responding directly to written or spoken requests and inquiries, for example. Target group feedback can be evaluated and clustered into topics and correlations between positive and negative aspects can be identified. As a result, AI can suggest an action plan and much more. In addition, Large Language Models (LLMs) can be used to perform smart customer segmentation, further cluster the segments, adapt targeting and personalize each message with individual messages.

 

Create a database and define an AI strategy

The data used to train the algorithms always determines how successful and innovative the AI deployment is in the end. Efficient data management is important for the successful use of AI and is the first step when it comes to AI planning. Marketing managers should maintain and strengthen their basic data, IT infrastructures and systems. This also includes cleansing customer data, on the quality of which potential AI use cases in marketing inevitably depend on. The rule is simple: high-quality data equals high-quality output from the generative AI solution.

Once the data has been checked, the next step is to plan possible AI measures with the question: Which AI fields of action offer the greatest individual benefit for value creation to further advance marketing objectives? Before using AI, the marketing team faces the major task of defining its specific goals and use cases to proceed in a structured and targeted manner. This is because the specific added value of AI must be defined, coordinated, and aligned with the corporate objectives to avoid working at cross-purposes with the future viability of the company's own business. In short, a proper AI strategy is the key success factor for ensuring the effective development, implementation, and scaling of AI projects. The focus is on three important fields of action:

1. Adapt marketing strategy: AI strategies require a clear vision, thorough planning and the willingness to adapt and renew existing marketing models in a focused manner. Integrating AI into the overarching marketing strategy is a crucial step in addressing target groups individually and in a personalized way.

2. Find and select use cases: Initial plans for use cases can be derived from the strategic goals. Here, a multi-stage process is beneficial, comprising preparation, ideation, evaluation, prioritization, and implementation, to yield optimal AI applications. For instance, an AI chatbot in marketing could effectively handle intricate customer inquiries, thereby saving time for the marketing team and reducing the burden of repetitive questions in customer service. Companies that are just starting out with AI should focus on applications that they expect to deliver the greatest added value.

3. Build partnerships: An ecosystem of partner companies offers helpful support for the development of AI applications by providing access to diverse expertise, resources, and different perspectives.

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Empowerment: Workshops for important tips on AI

A wide range of skills is required within the team for the utilization of AI. In marketing practice, there often exists a lack of corresponding prior knowledge and appropriate structures in marketing departments. Thus, it becomes even more important to empower employees accordingly, enabling them to create the right data and AI conditions for optimized value creation in central marketing areas.

Our experts recently conducted an AI training course for 35 international content and marketing managers at Bosch Rexroth, the leading specialist in drive and control technology. The focus of the joint workshop was to establish a general understanding of generative AI and explore how the company's own content marketing can be utilized most efficiently. Divided into three central parts, the six-hour training course combined knowledge transfer with practical application:

  1. The practical potential of generative AI was initially showcased through a live demonstration.

  2. The participants were then able to try out specific examples along the content value chain to evaluate and discuss the concrete effects on the future role of marketing.

  3. Based on the practical use of generative AI, the team quickly identified the most important individual use cases to keep all phases of content management and creation more efficient.

More information on the practical AI training course from Bosch Rexroth can be found in Bitkom's new guide "Artificial intelligence in digital marketing" on pages 41/42.

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