We teach managers how to find and extract the important marketing data from the noise of the abundance of data surrounding you! We teach you to create and measure metrics that truly allow you to explore what is working in marketing in your firm and what isn’t! And we teach you how to employ analytics in practice in a simple way, using just Excel!

In the fast-paced market conditions, where competition is fierce, rate of technology-change wild and consumers empowered and unpredictable, it has become more crucial than ever to understand the trade-offs between elements that are driving business performance. While data availability is overwhelming, managers are struggling in analyzing the increasing amount of information they have. Never before did managers have this much information on customers, partners and competition at disposal to make informed, smarter decisions; yet they are more than ever criticized about the lack of actionable insights that derive from it. McKinsey Consulting predicted that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions. Even for managers who have IT specialists and computer scientists in their team, the understanding of which data inputs are required and what outputs could and should be expected makes the essence of decision-making. The quest to find sustainable advantages to satisfy customers better than competition requires an understanding of how different aspects of marketing investment can be tight together, how to evaluate the current potential and future contribution of each customer and how to reap the advantage from customer relationships and social media investments.

This course aims to teach basic skills in marketing decision-making based on a systematic analytical approach to harnessing data that help managers to increase the effectiveness of marketing decisions. The course is tailored towards managers who are not trained as computer engineers but rather as business professionals who have to use data to improve marketing decision-making in their everyday tasks (e.g. deciding which customer segments should be targeted, how to evaluate the potential costs versus return-on-investing in different marketing activities e.g. from online or offline campaigns, or testing how to develop a new product and improve the existing one). We use an “Explain-Show-Do-Practice” approach to teaching that encompasses explanations in the lectures followed up by a combination of class discussion, case study analysis and practical hands-on exercises with practice datasets in Excel. We do not go deeply into the statistics and mathematics behind the methods used in the academic models behind the tools, but rather provide you with an understanding of what the model could be used for, intuitively how it works and which data do you need to have as an input and how to evaluate the output that you would get from the software. We use an add-on module in Excel to make this course highly relevant and applicable to manager’s actual decision-making.

INTENDED AUDIENCE:

This executive course is designed for:

• Executives who are in traditional leadership/management positions - of business units, products and functions - who need to understand how to better leverage data  to improve business performance.
• Executives who already have expertise in analytics, but whose roles and projects are becoming increasingly strategic so they need to develop further strategic skills.

  Our classroom experience shows it is beneficial to team up the two groups of executives above to teach them how to bridge the gap between analytics and startegy. Therefore, the course can both to managers without extensive marketing background as well as to those who work on marketing issues on a daily base. The highest impact of learning is achieved when concepts are discussed and practiced across the whole company in interdepartmental teams consisting of managers with diverse background: analytics, finance, accounting, operations and marketing, and the class would benefit from interactions and contributions from different backgrounds.

  This course would be suited for students who have basic skills and knowledge in business administration. No advanced understanding of mathematics or econometrics is necessary for this course, but the basic understanding of statistics (at an undergraduate business studies level) is beneficial for following the course. Basic knowledge and use of Microsoft Excel program is preferable, because most excercises are linked to Excel. Advanced data science and computer programing skills are not needed for this course (albeit we provide insights for more advanced students in supplemental materials which are linked to programming in R and machine learning algorithms).