Customer analytics as a source of competitive advantage

Deregulations, visibility of information over Internet and globalization are widely considered to be positive things, which trigger fast pace of economic development for the modern society. However, in many cases, exactly for the same reason, they destroy competitive advantage and companies start searching for opportunities to gain it. Taking into account increased information processing power and amount of collected data over the last couple of decades, companies are considering if it is worth to invest in customer analytics to gain competitive advantage. Therefore, the business world is questioning an ability of customer analytics to provide competitive advantage. Moreover, a sustainability of such an advantage is also questioned. In this thesis the resource-based view was applied to five cases to analyze how exactly customer analytics contributes to competitive advantage. The system theory was used to analyze the differences in a context where a technology is applied in order to analyze compatibility between organization resources and technology. In addition, a survey on customer analytics was studied to find a relationship between improved performance (across dimensions as: sales growth, time to market and customer retention) and analytical capability. Customer analytics can contribute to competitive advantage across three dimensions: increased bargaining power, improved effectiveness and improved efficiency of marketing capability. However, a sustainability of this advantage with analytics is doubtful. If analytics is complemented with other unique resources of the company such as scale advantage or access to unique data, then it is sustainable. Case studies suggest that each step of maturity requires more and more intangible organizational resources. So that if benefits from analytics were increasing with maturity, then the company which is able to innovate fast with analytics would sustain an advantage. However, this is not the case. The results show that sales improvement diminishes with analytics maturity over time. The decrease of perceived sales expansion might refer to the fact that there is a limit of the ability of the market and the company to grow at some point. Time to market improvement does not correlate significant with maturity (except for public services). This could be explained by a different perception to what it relates to. Profit-making organizations tend to associate time to market with products that bring profits and they tend to exclude extra services (e.g. information availability on their website). In addition, retention is improving with analytics maturity for products, public services and resource industries. The insignificance of financial services could be explained by the nature of the business and the level of regulation. Another interesting finding concerns the relationship between data driven decision making and soft driven decision making (e.g. intuition and experience). There is a significant positive correlation between data driven decision making and soft driven decision making. It rejects an existence of the scientific literature assumption that data driven decision making leads to decrease of soft driven decision making. The survey part of this research was limited to only three outcome variables: retention, time to market and sales improvement. The future research should also investigate the impact of maturity on other outcome variables such as cost improvement, process innovation, organization innovation, etc.