Most managers already agree that artificial intelligence (AI) will change the world, but as soon as people talk about the use of AI in their own company, there is often an embarrassing silence.

On the one hand, this is understandable, because for non-mathematicians the idea of thinking machines or self-learning software is still very difficult to grasp. On the other hand, because AI is growing exponentially and able to turn entire markets inside out, this is quite dangerous. Hence, to keep up in the race of being ahead of technological innovations, we must get into using AI for marketing—especially since many AI-based solutions have already arrived in everyday life.

The importance of data in digital marketing is growing steadily. In just 30 years, the number of published websites grew from 0 to 1.8 billion, and it is estimated that 50-80% of them use Google Analytics to collect and process visitor data. SEO, UX or content experts still use this information to develop optimization tactics.

Increasingly often however, AI-based systems independently derive strategies and measures from them. In fact, this is already the status quo in high-turnover e-commerce, but it is only a matter of time before we see AI-based advertising media in physical environments as well. The connection with wearables and sensors as well as rapid advances in image recognition creates undreamt possibilities here.

The future is completely personalized

Artificial intelligence is not just a vision when looking at Siri and Alexa today that are already planning appointments and filtering add-on emails based on experience. And the success of YouTube, Netflix, and Amazon is strongly related to their constantly improving real-time recommendation technologies. For instance, Amazon Personalize now offers its machine learning recommendation system as a commercial marketing tool and is not alone in the market. Several large and small vendors are working on solutions to personalize every interaction on a website. There is a demand for that since most decision-makers assume that the personalization of customer approach will be decisive for being competitive in the future, according to surveys conducted. The fact is that an AI-controlled personalization enables an individual customer journey, not to mention that machine learning draws its knowledge, among other things, from user behavior regarding what customers want to buy.

The advantage of personalization does not only lie in the possibility to enlarge the shopping cart or to discover new things but helps to make the shopping process faster where it is not just about rummaging. For many everyday products, shopping is more of a routine than an experience, but you still must do it. Previously, customers had to search for each product individually in the online shop, select it and place it in the shopping cart. Studies confirm that it often takes longer to fill an online shopping cart with groceries than to do the shopping in the supermarket, even if you include the trip there. AI-based predictive baskets provide a remedy here by analyzing individual purchasing behavior and automatically detecting trends in the behavior of all customers, so that forecasts can be made about what the respective customer likely wants to buy today.

Even offline, the intelligent personalization will advance since with the help of sensors billboards will be able to recognize whether a viewer is sad or happy, young or old, and whether a person is in a hurry or has a lot of time. And with every reaction of a viewer to an advertising message (“continues”, “stops”, “scans QR code”, “smiles”) the system learns to display the right advertising. Retail displays could recognize which specific item of clothing on a stand attracted the customer, which products were viewed afterwards, and show corresponding recommendations.

AI-supported dialogue marketing

In addition to personalization, automation is currently the most important use of AI in marketing. AI-supported dialogue marketing, for instance, is not only becoming more effective by constantly learning new things using previously unused data. In the field of applications known today, chatbots are probably the instrument that comes closest to the science fiction scenario of a service robot. Important to know is that chatbots do not work with "real" AI per se: most bots are programmed for specific applications and just look to see which answer in each list best fits the question. In contrast to such rule-based bots, semantic AI bots can understand the meaning of the question entered and derive answers from larger amounts of data. Semantic AI bots do not work with question-answer assignments, but rather try to analyze the context of a voice input. So, we can expect that instead of comprehensively trained support staff, highly specialized staff will be needed in the future, to whom the bot only refers to if it cannot solve the problem on its own. However, although Artificial intelligence is still in the early stages, and the big changes are yet to come, it will obviously bring enormous growth opportunities for companies.

Besides foresight and know-how, integration into corporate marketing requires the willingness to gain valuable new experiences and to learn steadily. Therefore, employees should be directly involved in the implementation right from the start, as the change process through self-learning systems usually creates existential fears. It should become clear, however, that AI will not replace and lay off employees, rather give them more time for new tasks.

By Daniela La Marca