AI in marketing: From the user to the personality

We are permanently online and leaving a digital footprint. How digital marketing benefits from data.

AI in marketing: From the user to the personality

Brands today have a number of ways to collect and analyze user data and to design marketing measures in line with these. The dream of many companies of bringing tailor-made advertising messages to potential customers is getting closer and closer to reality. Thanks to intelligent targeting – which uses algorithms to understand the user’s advertising environment, consolidate data and create behavior patterns – the user, who appears anonymous at first glance, becomes a personality with a character and a face. What can artificial intelligence do in marketing? Three examples of the application of AI in digital marketing.

Hyper targeting for a digital footprint

The majority of today’s customers pass by many digital touchpoints on their way to purchasing a product or ordering a service, leaving behind exciting and increasingly complex data for the advertising industry. These data can come from private end devices or professional devices and provide information about many characteristics of the user. The merging of data from different sources is the goal of modern targeting.

In addition to the typical socio-demographic data, such as age, gender and location, data strands such as the time of day of a transaction, type of end device or average shopping cart value can also be used to map user behavior. Even short data strands allow further derivations and can be used to form patterns. The more data available, the more targeted the supply of consumers with relevant content.

The potential customer benefits from this type of targeting just as much as the company. A customer’s digital footprint also indicates which phase of the purchase decision process they are currently in (awareness, consideration, decision). Advertising material can be placed accordingly. The more data that can be merged, the better the AI system understands the user, his situation and his environment.

Understand advertising environments better

Through a contextual analysis of the customer journey, algorithms are also able to classify and understand advertising environments. Advertising content finds, for example, the right editorial environment in this way. Advertising timing can then be optimized. To achieve this, the AI systems analyze the behavior of countless users in the background and classify websites and their content. Based on existing data, the technology recognizes and evaluates whether the advertising content environment can be qualified as “brand-safe”. Even personalized homepages can be equipped with AI and thus individually adapted to suit each user.

Through forms of artificial intelligence, content marketing also has more and more possibilities to react to different situations in an agile way. Amazon provides a simple example: the customer is provided with a further product portfolio based on purchase decisions already made. The customer feels understood and less annoyed, since the advertising messages are more likely to match his tastes and interests, which makes the purchasing experience more positive. This opens up new opportunities for marketers to stage their own campaigns.

Creating automated content with data

Information is the basis for algorithms to continuously improve and learn new things. Similar to when the human brain learns vocabulary, large amounts of data help a “self-learning” system to achieve ever greater precision and added value. It is already possible to generate content from data. “Are you an experienced semi-professional and therefore regularly perform manual tasks? With the Bosch PST 18 Li cordless jigsaw master every task with ease. This is a high-quality and reliable partner…” – this is what an artificially generated text excerpt from an online shop sounds like. What reads as if it has been typed by a human hand in fact comes from the company uNaice and was produced with the aid of the software as a service solution from AX Semantics. Of course, this is not possible entirely without human help. The AI application for content production is an interplay between man and machine.

To generate a very large number of different texts in a short space of time, a corresponding amount of product and customer data on the potential buyer groups is required. The algorithm processes these data and translates them into target group- and channel-specific text according to the trained specifications for semantics and language style. The automated creation of content is an enormous help for online shop operators, for example, to create SEO-optimized product descriptions in the shortest space of time. It is also possible to update several texts simultaneously at the push of a button. Another milestone and proof that artificial intelligence optimizes the possibilities of digital marketing.

The future depends on data

Artificial intelligence thrives on data. So it is no surprise that the USA plays a leading role in this area. Almost 40 percent of all AI start-ups are located here. According to the results of the recent study “Artificial Intelligence – A Strategy for European Start-ups” by Roland Berger, Europe comes in second place, at 22 percent, even ahead of China. For marketers, the future remains exciting and will probably also depend on how intensively data may be used for marketing purposes. After all, it is data that allow companies to give their own customers a face, to better understand them and to reach them in a targeted way.