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A multimethod study on how SaaS-businesses can utilize cohort analysis to improve marketing decision-making

Written by G. Fridell, S. C. Chafjiri

Paper category

Master Thesis

Subject

Business Administration>Marketing & Sales

Year

2020

Abstract

Thesis: The value of information in decision-making As described in Chapter 1.6, one of the aspects to be analyzed is how GetAccept's access to information changes, so as to incorporate group analysis into its marketing decisions. The reason is the logical assumption that more information should be useful for decision making. However, this logical hypothesis is also supported by academic evidence. In their article on the impact of data-driven decision-making on company performance, Brynjolfsson et al. (2011) pointed out that Blackwell's (1953) pioneering work laid the foundation for modern theories about the value of information. One of Blackwell’s contributions to the field is to prove that if one acts better under one imperfect information set than another (ie "more information"), then rational decision makers should get higher expected returns . From this perspective, Brynjolfsson et al. (2011) pointed out that improved information will always improve company performance at least slightly. Blackwell's theory is of course theoretical, which is why it can be argued that conclusions do not always apply to practice. However, Porat & Haas (1969) studied the phenomenon of the influence of information on decision-making and concluded that in practice, more information does lead to more accurate goal setting and decision-making levels. Of course, it can be disputed that the increase in the amount of information does not always lead to better decisions. For example, in the case of information overload, when the decision maker receives more information than its processing capacity (Milford & Perry, 1977), the quality of decision-making is likely to decline (Speier, Valacich, & Vessey, 1999). However, it is difficult to argue that the fact that a collection of information about a phenomenon emerges from nothing, such as with the help of group analysis, constitutes an information overload. Therefore, in the context of this research, the theory suggests that gaining access to more information does usually lead to improved decision-making, strategy or otherwise. In addition, in a strategic environment, it is generally believed that information leads to better decision-making (for example, by increasing competitive advantage), as described by famous authors Michael Porter and VictorMillar (1985). 2.2 Marketing decision-making process As described in Chapter 1.6, one aspect to be analyzed is how to join the group analysis to affect the marketing decision-making process of GetAccept. The goal is that if improvements in the process can be observed, it can be said that GetAccept's decision-making has improved. However, to carry out such analysis correctly and draw such conclusions, it is necessary to understand the marketing decision-making process 2.3 The importance of data-driven decision-making in marketing Since the focus of this study is to evaluate the benefits of cohort analysis in a marketing environment, it is important to understand the value that such data-driven methods can provide to organizations. JieLu et al. (2019) pointed out that in order to overcome the challenges in the era of big data, researchers and practitioners have emphasized the importance of making data-supported decisions. The famous marketing writer George S. Day (2010) is an example. He said that “the first contributor to an outstanding growth record is deep market insight and vision.” Eric Schmier, former CEO and executive chairman of Google Te (2014) said that you should “bet on technical insight, not market research.” In addition, Johnson et al. (2019) emphasized the benefits of using data to drive specific decisions in marketing. The author points out that by analyzing large amounts of data, marketers can make useful inferences about customers and competitors, such as a better understanding of their costs, sales potential, and emerging market opportunities. Brynjolfsson et al. further confirmed this. (2011) Through a quantitative study of more than 170 listed companies, it was found that companies that adopted data-driven decision-making showed higher productivity and market value than companies that did not adopt data-driven decision-making. Jeffery (2010) further emphasized the importance of data-driven marketing by pointing out that managers increasingly need to (1) prove that their marketing expenditures are reasonable, (2) demonstrate the value they create for the company, and (3) learn from Fundamentally improve marketing performance. Jeffery believes that a key to achieving this goal in marketing is to understand some basic indicators, such as churn rate, customer satisfaction, profit, return, and customer lifetime value. Further explanations of these metrics can be found in Chapter 3.3. 2.4 Prerequisites for efficient data-driven marketing decisions. As described in Chapter 1.4, organizations differ in several aspects, and similarly, their ability to effectively use data in decision-making is also different. Therefore, in order to achieve the purpose of this research, it is important to determine which organizational prerequisites may exist in order to effectively use methods such as cohort analysis in marketing decisions. Johnson et al. (2019), LaValle et al. (2011), and Wedel & Kannan (2016) all describe their belief that the organization (in the case of Johnson et al. and Wedel & Kannan, the marketing organization) becomes the most important part of the journey of data Aspect-driven. Although these views are different, they all recognize two different prerequisites for success in this process: (1) support and advocate for the management of data and analysis, and (2) build on information sharing and evidence-based Company culture. Read Less