The idea of designing creative advertising banners, captivating headlines, and trying to receive as many likes as possible for social media postings is increasingly giving way to a tough, data-driven mentality in marketing. “If you can't measure it, you can't improve it”, the management guru Peter Drucker once said. And indeed, the shift in the customer journey and the associated development towards digital marketing channels brought with it a decisive factor – measurability! Marketing has changed, and it will continue to change, but what does that mean for required job skills in marketing?
Many companies are convinced that good marketing decisions must be based on data. Therefore, IT solutions and marketing technologies are constantly being further developed to satisfy the increasing demand for usage and behavioral data as well as their analysis options for marketing purposes. And exactly for that reason, modern marketing managers find themselves often in a project management role between marketing conception, analysis, and IT.
So, if you are striving for a career in marketing, depending on the position you are aiming for, you should bring to the job basic know-how in the four fundamental data disciplines. Consider that:
2. Data validation requires standard analysis tools (e.g., Google or Adobe Analytics) as well as database techniques (e.g., SQL, Python)
3. Data analysis requires understanding of analytical / statistical procedures and scripting languages (e.g., Python and regression analysis)
4. Data visualization requires data storytelling and tools for data visualization (e.g., Tableau, Google Data Studio, Excel)
Depending on the job position, a more in-depth skill set is required in the various disciplines. However, rest assured that a basic understanding of all disciplines in data-based marketing is necessary to meet the expectations of today’s organizations in response to the rapid development of marketing technology.
The most important marketing job profiles can be classified as follows regarding marketing conception and data/tech skills:
- Brand Managers deal with strategic campaign planning and brand communication, and therefore require a certain amount of technical know-how in the operational implementation of planned advertising measures within the MarTech tools.
- UX Designers must continuously improve creatives as well as plan and optimize A / B testing etc., meaning it must be decided which measures are dynamic and / or can be personalized. This in turn requires a basic technical understanding to determine what is feasible and what is not. With a good understanding of data analysis, the measures can be assessed and further optimized.
- Marketing Managers must coordinate campaigns both internally and with external agencies. This requires communication at eye level and certain analytical knowledge of metrics and KPIs so that the success of the advertising measures can be assessed.
- Social Media Managers must know how to use analysis tools of social networks and understand data collection, data validation and interpretation of the data, since it is part of the basic knowledge in social media management.
- Performance Marketing Managers should have general knowledge in all four data disciplines. In addition to the planning and controlling of marketing campaigns, there should be know-how in the collection and validation of performance data as well as an understanding of the subsequent visualization and interpretation of the results.
The integration of new technologies and platforms into marketing is vital to reach target groups effectively and measurably. Hence, regardless of whether you are a beginner or an experienced marketing professional, you should continuously develop tech and data skills. Particularly, graduates and young professionals, however, should not underestimate these requirements needed and universities must face the big task of taking current technical conditions into account in marketing. In fact, due to the rapid development of the industry, it is crucial that universities motivate their marketing students to continuously develop their data and technology skills, besides encouraging them to deal intensively with IT and analytics topics.
By Daniela La Marca