1marketMarketing is highly digital nowadays and has its hands full with data and measurable target group reactions. The challenge the industry faces, however, is to channel the flood of data, to filter out the essentials, and to draw the right conclusions from them. That’s why systems and algorithms are needed.

Data-driven marketing, Big Data and Artificial Intelligence (AI) help us to master the flood of data and to work successfully with it:

  • Data-driven marketing means using insights from data as the basis for marketing decisions. In practice, it is mainly used in connection with automated, targeted and personalized campaigns - be it via display advertising, social media, messenger or email – and usually provided by the systems. For example, the opening (or non-opening) of an email, the click on an advertising banner or the visit of a landing page can be triggers for subsequent automation routes. If we create an interface to our CRM system, we can even include additional customer data. It goes without saying that all this must be done in accordance with GDPR. Used responsibly, data-driven marketing undoubtedly offers great potential: making sure that messages have a high relevance for the recipient, corresponding with the interests, behavior and decision phases of the respective customer journey. This works not only well in the consumer sector but with business decision makers, who appreciate not to be overwhelmed with irrelevant information.

  • Big Data not only means "a lot of data", but rather data of a different quality that provides a new view on situations that wasn’t possible to get with conventional data and analysis methods. The difference can be compared with the transition from photography to film: did the photo provide a detailed, but static information about the depicted image, the moving image now adds the temporal dimension and dynamics. Big Data typically differs from traditional data by the three ‘Vs’:
    1. Volume: the sheer mass of data that breaks the processing capabilities of traditional systems.
    2. Variety: heterogeneity of data, which may include unstructured raw data, voice recordings, images, videos, streams, etc.
    3. Velocity: with big data, speed is often critical, right down to real-time analytics and reactions in real-time.

    Usually, a special IT infrastructure must be set up, own analysis methods developed, interfaces to the data sources and the reporting system created, as well as ideally also a visualization software, in order to be able to use such mass data.

    For marketing, Big Data is especially interesting in the following areas:
    1. To uncover new customer potential by using many different data sources, e.g. even customer data from the internet;
    2. Analysis of past and forecasting of future customer behavior, e.g. through data mining and the statistical twin method;
    3. Automation and personalization along the customer journey up to 1:1 marketing distances, e. g. by cross-touchpoint tracking.

  • Artificial intelligence (AI) is a replica of human perception and decision-making, so that machines learn to work on and solve problems independently. But this is actually nothing new: AI systems have been researched since the 1960s. Today, however, Big Data - both the presence and processability of mass data - provides the prerequisite to deploy AI on a broad basis. AI is experiencing a downright boom with big data right now and has found its way into all kind of areas of life when regarded as being useful. In marketing, for instance, AI helps dealing with large amounts of data that are constantly changing but must be processed continuously. For example, we can categorize customer reviews with the help of text analysis, have routine queries processed, train chatbots in customer dialogue or even purify and systematize product datasets with the help of AI. If there is an initial problem with the assignment, the AI is getting "smarter" with each additional input and relieves us of routine work, so that we can focus on the more important work - the creative tasks in marketing.


The data and systems help us, so to speak, to get to know each customer better and better, to anticipate their wishes, to address them and to serve them perfectly.

By Daniela La Marca