Data-driven marketing is an aspect of online marketing based on the analysis of customer data. The findings from these analyses are used to improve sales and increase brand awareness and reach. This includes demographic data as well as behavioral information, for example buying behavior. The data sets used include demographic data as well as user data, which, for example, record the behaviour of customers on websites. Data-driven marketing cannot be compared with Programmatic Marketing, which is based on the fully automatic purchase of advertising space. However, data-driven marketing tools can support this form of marketing.
Data-driven marketing has emerged through the influence of various developments in sales, customer care, and Online Marketing. In the past, Customer Relationship Management, [ERP ERP systems and BI solutions were used as tools for decision-making at different levels. Employees and managers were able to access a large data base in order to optimize business processes and make informed decisions. The focus was on dealing with resources and improving the operating result.
Data-driven marketing goes a step further and refers to insights from large datasets that are relevant to the marketing and perception of the brand or the product. Customer data in the form of demographic, behavioral or voluntarily provided information such as questionnaires or online surveys help marketers improve campaigns and improve customer care in the long term. The size of the company does not play a major role here, as even small companies can already benefit from data-driven marketing with the appropriate tools.
The goal of data-driven marketing is to provide decision-makers with an up-to-date picture of customer behavior so that trends, changes in purchasing behavior or a changed perception of the brand can be quickly recognized. Ultimately, the method should result in higher sales figures, higher traffic or the improvement of other predefined KPIs. In an overarching sense, it is about a long-term customer relationship, understanding the customer and responding promptly to trends and markets in order to remain competitive.
For marketing based on data, it is essential to collect customer data based on which marketing strategies can be developed. The needs, wishes, and expectations of the customers can be anticipated in this way. The past and current behavior of customers may make it possible to predict future purchase behavior.
At the same time, it is intended to achieve a competitive advantage and significantly improve the efficience of campaigns with regard to their ROI Value. According to a survey by Adobe, data-driven campaigns should have three times the Conversion Rate compared to traditional campaigns without a data-based background.
Key elements of data-driven marketing:
In addition to this selection of tools, free web analytics tools such as Google Analytics can also be used for data-driven marketing. The data from Google Analytics can be used for targeting or remarketing with Google AdWords, for example. It is also possible, for example, to specifically advertise anonymous user IDs.
Against the background of the ever-increasing amount of data, the nature of the data is an important prerequisite for the success of Data-Driven Marketing. The more data, the more difficult the evaluation. For instance, Big Data uses a variety of sources. The data gets sorted according to different aspects in Data Warehouses.
The question is, which of this data is usable for sales and customer care? An important challenge in data-driven marketing is therefore the association of relevant data, so that insights can be gained which are useful to the marketing department. Successful data-driven marketing depends on smart data and appropriate tools.
In addition to the properties, procurement is a sensitive issue. Privacy and data protection must be guaranteed. Moreover, customers want a transparent, authentic dialogue when they provide their data. They also would like to be able to change the personal data stored about them. However, this is only possible in the rarest cases. Once collected, companies often treat such data as secrets. This results in distrust of the company.
Another problem is the rationalization of information. Customer data is turning into numbers and is increasingly not being associated to actual people. Companies that want to understand their customers must also perceive the people with all their facets behind such data. Data-driven marketing must not become an automatism that loses sight of the fact that the customer should be the focus of attention rather than profit maximization or simply the reduction of marketing expenses.Brands and products live through emotions which are an important identification feature for customers.