Companies, now more than ever, recognize the value of patent analysis in contribution to their competitive and business intelligence. In highly competitive technology oriented industries, this IP (Intellectual Property) -based intelligence has gained increasing awareness over the past decades (Rivette & Kline, 2000). As technologies have become more and more complicated over the years, inventions nowadays are often described by a vast amount (sometimes thousands) of patents (Kur & Dreier, 2013). In order to convert this ever-growing database of patents into actionable intelligence, automated technologies for patent analysis have been developed. Furthermore, also tools capable of text mining for technology mapping came to the market. The output of these mapping tools represent the technological content of a certain set of patents in a map that borrows its appearance from cartography (Trippe, 2015). By doing this, huge amounts of patent records (up to millions) can be analysed, clustered based on their technological content and represented in an easy to interpret manner. This all can be done in a fraction of the time it would take to do this manually. The question raised however, what the quality of automated patent mapping is and how can it be used as a source of competitive or business intelligence?