AI in marketing: Perfect vision, imperfect implementation
Most everyone recognizes the significance of artificial intelligence (AI) in the business world today. The implementation of AI projects in marketing, however, is still in its infancy. In the first part of our interview, Prof. Dr. Claudia Bünte, an acclaimed marketing expert, who has been focusing on the topic of AI in marketing for a number of years, shares with us why that is the case and in what areas AI can already create added value.
In 2018 and 2019, you surveyed marketing managers regarding the future of marketing. What were the results in a nutshell?
Everyone is talking about AI. 80% of the surveyed marketing professionals say that AI is essential for their company. 92% believe that it will become even more critical in the future, particularly in the areas of customer insight and execution, i.e., advertising and sales, which are areas where a great deal of data is available. However, as it often happens, the reality is quite different: Only 7% use AI extensively, and the tools they use are primarily isolated solutions (see chart). A frequent obstacle I have encountered routinely in my work as a consultant is that many projects get stuck in the pilot phase. And there is not only one particular problem with the implementation of AI projects. Rather, the reasons range from a lack of budget and an unsuitable mindset in the team to a lack of IT support. Even those who are already using AI give themselves poor grades for implementation. But there is good news too: Among marketing professionals, the number of AI skeptics is decreasing.
Let’s get a bit more specific: In your estimation, which applications of artificial intelligence in marketing are feasible in Europe, or are already in use?
There are indeed many AI tools for marketing that are already in operation in real life and that work. As part of our study, we analyzed more than 30 cases, including their impact numbers for the five principal tasks in marketing – consumer insight (understanding your customers), strategy, product development, advertising and sales, and marketing ROI (measuring the effectiveness). There are excellent tools available in almost all these areas. The only area where AI can provide little support is the area of strategic tasks. That is hardly a surprise, though, since no one likes to volunteer their strategic data. But data is what AI needs to be able to learn. Despite these specific use cases, Europe lags far behind the U.S. and particularly behind China in the field of AI.
China, a fitting keyword. What does looking at China teach us?
To put things in perspective, Germany plans to invest three billion Euros in artificial intelligence by 2025. That is what China invests in a single development center in a single AI model city such as Shenzhen. There are three reasons why China will be a leader in AI. First, the population numbers: There are 1.4 billion people. And the motto in China is mobile-only. The Chinese organize their entire lives using super apps like WeChat on their smartphones. This means data is coming from 800 million mobile phones. Secondly, the lax data protection regulation in China clearly gives companies more freedom in how they use data. Thirdly, there is the one-party government with a clear focus on artificial intelligence. Its goal is to be a global leader in AI by 2030, and it has developed a detailed 5-year plan to achieve that. To learn about the future in Europe, it’s worthwhile having a closer look at China.
Compelling information on this topic:
- Bünte, Claudia (2020): “Die chinesische KI-Revolution: Konsumverhalten, Marketing und Handel: Wie China mit Künstlicher Intelligenz die Wirtschaftswelt verändert” [The Chinese AI Revolution: Consumer Behavior, Marketing, and Trade: How China is changing the business world with artificial intelligence]: https://www.amazon.de/s?k=9783658297954&i=stripbooks&linkCode=qs
- Tips and information around the topic of AI: https://kirevolution.com/
- AI self-test: Are you an AI optimist or AI skeptic? Six questions, 2 minutes, anonymized results: https://kaiserscholle.de/de/ki-typomat/
- Bünte, Claudia (2018): „Künstliche Intelligenz – die Zukunft des Marketing: Ein praktischer Leitfaden für Marketing-Manager“ [Artificial Intelligence – The Future of Marketing: A practical guide for marketing managers]
- Free download of the referenced study “AI – The Future of Marketing 2019”: https://kaiserscholle.de/de/kuenstliche-intelligenz/