ABSTRACT
The developments in big data are changing analytics. There are three major developments underlying these changes. First, new data types and specifically non-structured data are being analyzed. Traditional data analysts typically do not always have the skills to analyze these data, as totally new methods are required. Further, new data may require more computer science techniques. Second, in this new big data and digital environment, new challenges and questions arise. An important challenge, for example, is how to evaluate investments in new online advertising tools such as search engine advertising and affiliates. Third, new analytical techniques are being developed that can account for the huge continuous data inflow. As a consequence, a total new playing field for analysts has unfolded. This implies that traditional analysts have to adapt to these new circumstances and have to understand and be able to apply these new techniques. Fortunately, some of these big data analytics still use some of the classics as discussed in Chapter 4.1. However, some techniques are rather new and are not included in the statistical toolkit of traditional analysts. In this chapter we aim to
discuss seven new big data analyses. These big data analyses are a combination of new techniques, specific marketing applications and specific types of data. Not all of them involve very sophisticated models. In Table 4.2.1 we provide an overview of seven new big data analytical areas, their importance for marketing decisions at the market, brand, or customer level and the statistical methods they use, and we will go on to discuss each of these areas in more detail.
