Building superior persuasion mechanisms with GenAI

The 5th industrial revolution announced itself over a decade ago. Initially in the form of the big data hype. Then artificial intelligence (AI) came under the spotlight, and now we are completely under the spell of Generative AI (GenAI). What we need to realize is that GenAI was made possible by those huge mountains of data needed to train artificial intelligence. Big data was indeed a serious trend breaker, but its far-reaching impact is only now becoming clear through techniques like Nvidia and OpenAI.

Learn from internet

From the Internet bubble we have learned that the Internet cannot be free, is not a panacea and can by no means be ignored. Non-food and fashion retailers, for example, have now got the hang of it, even apart from new challenges such as the cost of serial returners. We can see that the Internet has taken the business by storm. What can we learn from this when it comes to the next industrial wave?

For any industrial revolution, the promises are enormous, as is the increase in complexity to successfully exploit those promises. Often that complexity is one of the causes, leading to the bubble bursting. For example, it proved difficult to estimate how profitable a dot-com operation could be. The enthusiasm regularly lacked a viable revenue model and too often relied on future growth potential. This was often matched by hefty investments. Proper implementation of disruptive technology thus proves costly and certainly not without risks. With GenAI, we will go through an even steeper learning curve. That learning curve starts with exploring the business potential.

Customer intimacy

We hear and read enthusiastic stories about the power of GenAI in marketing, for example. With the previously proven algorithms for dynamic pricing, loyalty cards and recommendation systems, it is now possible to respond even more personally to the needs of potential customers. Customer intimacy gets a boost, for example by applying GenAI in chatbots that use artificial characters to help customers with questions or problems about services or products. With GenAI, this can be done much more professionally than with the sometimes rigid puppets and hopeless answers of today's mainstream chatbots. You can now communicate with customers extremely naturally, without exhausting staff. And that's far from all.

Regenerating emotion

With the further integration of digital technologies into our daily customer contact, the mountain of data is growing exponentially. By constantly digitizing customer responses, in any situation or channel, the future intelligent customer relationship system is becoming smarter and smarter. The patterns returned by the customer feed the AI environment with billions of parameters. With that, the system finds new contextually relevant patterns, predictions and answers. Online, of course, but also in-store with the use of motion detection and video observation, among others. However, these models are not only focused on formulating relevant answers correctly in terms of content. One example: deep fake started with photos, then came videos and now even the voice of a random person can be regenerated. From a marketing perspective, this offers the possibility of generating completely product-specific one-to-one personalized advertising videos that exactly match the customer's needs. But what is even more interesting is that with today's AI systems, emotion can not only be analyzed, but also regenerated directly in the right context.

Superior

Customer loyalty and purchase behavior are all about emotion. On social media, completely natural-appearing characters can be generated that build a community around your brand or services. Because the GenAI system flawlessly picks up on the emotions of the community and its individual members, it will respond appropriately on the same emotional wavelength appropriate to the circumstances of that specific moment. In this way, each retailer can become an anchor in each consumer's friends’ zone. With deep learning techniques, it will become increasingly clear what issues play a role in potential customers' decision-making. With the help of conversations on social media, among others, superior persuasion mechanisms emerge that the artificially generated person in this community can use. Very subtle but also very persuasive, because precisely tailored to the person. By the way, this technique can of course be used just as well in B2B marketing activities, because the choice of suppliers also remains human work.

Laws and regulations

Is this ultimate form of hyper-personalization, with a personal influencer for each consumer, legally and ethically sound? The advent of the GDPR has set clear boundaries for online privacy and the use of personal data. The EU AI Act will become binding from 2026, making recommendation algorithms with social impact subject to strict rules. Consumers will also have the right to rectify personal data in the profile you have built.

For GenAI, it's learning by doing. We are going to learn what should and should not be done transparently, how we moderate algorithms, how consumers should be informed, what they should give explicit consent for and how that can be revoked. Furthermore, we are going to experience that GenAI is anything but cheap. One thing is certain: companies that ignore this development will, with exceptions, eventually lose out - just as the Internet has proved indispensable in the battle for consumers.