Data has long since become the most important resource of the information society. They help companies analyze customer movements or support them in making decisions about new products and their marketing.
In times of comprehensive networking, data is generated in huge quantities and from various sources, from production to classic administration to social networks. If companies collect and analyze this data, they can launch targeted and personalized marketing campaigns on this basis - and largely automatically. This data-driven marketing is made possible by modern technologies such as cloud computing, real-time data processing and artificial intelligence.
However, data-driven marketing means more than just the use of technology. As a holistic concept, it has a lasting effect on the corporate culture and the entire value chain, which means that it fundamentally changes companies in case of doubt. This makes it all the more important to proceed thoroughly when implementing the concept. To this end, there are the following five steps that can be taken.
1. formulate business case
Companies need a business case in which they define at which points which data should support their decisions. Not all data helps with all decisions, which is why it is critical to concretely describe the use scenarios and knowledge expectations in advance. The next steps can be derived from the definition and use case.
2. focus on quality
The fact that data is available in large quantities might tempt us to pay little attention to its quality. But the opposite is necessary: Data-driven marketing can only be successful with data that is available in sufficient quality. Ensuring the right quantity and the necessary quality is therefore an indispensable step on the way to data-driven marketing.
The preparation of data includes the consolidation of master and customer data as well as the inclusion of additional information such as transaction data from ongoing business or external data from social networks. By providing "right data" or "smart data", the amount of data can be limited and the quality of the data improved. This increases the efficiency of its use.
3. provide the right technologies
Cloud-based databases can process large amounts of data quickly. But only artificial intelligence is capable of extracting new insights from it. Algorithms trained with machine learning, for example, are able to recognize correlations hidden to the human eye in large volumes of unstructured data very quickly and thus provide new insights for decision-making. Companies should start evaluating the use of AI as early as possible; the technology is mature and powerful enough for this.
4. build up competences
However, data-driven marketing is still a matter for specialists even when AI has already provided valuable assistance. For data-driven business models, every company needs the appropriate specialists: IT experts who collect and process data or model processes; data scientists who program and train algorithms; data specialists from the marketing department who ask the right questions of the data and draw the right conclusions from the AI-supported analyses. The technical expertise for these activities is usually already available; companies can build up the technical skills via internal training. In addition, companies increase the acceptance of data-driven business models and the use of modern technologies among their own staff through such internal solutions.
5. define pilot projects
If you have the necessary data in good quality and qualified employees, it is best to start with a small, manageable pilot project in data-driven marketing, for example with a single campaign. This allows companies to gain experience, build and adapt the necessary digital infrastructure, and sharpen internal expertise. All of this helps companies with further projects, which they should already plan for at the start so that they can roll out the proven technologies and methods for data analysis company-wide. After all, it's not just marketing that will benefit from the first experiences, but the entire company - all the way up to the boardroom.
"As well-intentioned as it is, classic customer care with its conventional methods is no longer nearly enough, because the relationship between companies and customers has changed radically," explains Uli Wolter, Managing Director at Macaw Germany. "Customer demands have grown massively and competition is fiercer than ever before. Companies would do well to rethink their attitude towards their customers: they need to put the customer at the heart of everything they do and develop a proper customer culture. Data-driven marketing is an essential tool for this."
The Digital service provider Macaw supports large enterprises with solutions and services in digital marketing and e-commerce, data and AI, cloud and integrated enterprise applications. Macaw specializes in software solutions from Microsoft and Sitecore.