Successful campaigns are usually defined as a holistic scenario. Could AI now be used to populate campaigns with relevant content? But how is AI even capable of this? What must it learn first? In fact, AI approaches an optimized solution step by step and through continuous training.
In order for artificial intelligence to make marketing increasingly more efficient, it must achieve some ambitious goals:
So will the delivery of marketing content to customers be fully automated in the future? There is a lot of potential in AI, but at least for now, it still makes sense to provide a structure and thus the framework for the marketing measure manually and then have AI fill campaigns with content - i.e. precisely tailored marketing content - at an individual customer level.
An intelligent marketing tool not only sends e-mails, but also learns from the recipient reactions: Which link was clicked on? Which topics are of interest to the recipient - follow-up e-mails are then adapted accordingly.
Landing pages can be created and controlled individually - e.g. for different product group combinations. This way, readers only receive the information about the product group they are interested in. The communication is targeted and customers receive customized content with high added value.
Automated tools simplify marketing management
In order to select content that fits perfectly, you need customer data from various sources, which are available in a tool for marketing automation. In combination with behavioural data - also stored in the marketing automation tool - individual characteristics and needs - and thus tailor-made content - can be determined at customer level.
With modern tools for marketing automation, the specific interests of the customers can be identified relatively easily. For example, if a customer clicks on a link to a fashion label, this signals an interest in fashion. If the customer repeats this more often in a certain time window, the marketing tool automatically assigns the interest "fashion trends" to him or her. The AI, in turn, logically incorporates this insight into the determination of the optimal marketing content. Learning the AI step by step is important and unavoidable: the decisive information is collected step by step.
As the number of marketing campaigns increases, so do the interactions with customers. This in turn generates more data that is used by the AI for personalisation. It is therefore a repetitive process that continuously improves knowledge about the customer and personalisation. The aim is to address the customer in an increasingly personal and satisfying way. The fundamental concern to put the customer in the centre of attention, with all his interests and needs, is thus successfully implemented.
Let us take a closer look at this process: A "young AI" has only a few data available - such an AI is first trained by data scientists. These data scientists identify customer master data and behavioural information from other systems and "feed" it to the AI to make it learn.
Social media channels play a special role in the "training". These channels have been connected to marketing automation tools for a relatively long time. Technically, this information can also be linked very easily to customer master data. However, restrictions result from data protection regulations.
In marketing automation, a learning process takes place through customer reactions
Standardised solutions for marketing automation collect data from other systems such as customer master data from a CRM solution (CRM = customer relationship management) or clicks from a web shop. The marketing solution then bundles this data into a so-called 360° customer profile - looking at and knowing the customer from all angles.
So what are the tasks of employees in this marketing automation process? The integration of all available data is the central point. Therefore, employees with integration expertise and understanding are indispensable. To the same extent you need data scientists for the development of the AI part and content managers for the creation of the marketing content. The hand-in-hand nature of this development process is quite a complex task - but it ultimately contains an enormous potential for improvement accompanied by a significant simplification of the work processes. Equally exciting is the paradigm shift and change for marketing departments that our approach brings with it:
This paradigm shift has the potential to significantly streamline existing processes and reduce costs. In addition, marketing content can be tailored more precisely to customer needs, which promises higher sales. It is worthwhile to work with an AI now and to set out together on the road to the future.