The Messenger was inspired by the uncovering of Facebook selling private chat records to companies like Netflix and Amazon (Newton 2018). Such chat records can be of great length and I assumed that the companies use algorithms to extract useful information from such text messages. I was curious how much information an algorithm could derive from a chat between a friend of mine and me. The Google-developed Cloud Natural Language API served as a reference algorithm for the analysis. It provides different types of unstructured text analysis including sentiment, entity, and syntax analysis as well as content classification. Inspired by the Facebook Ads Interests list discovered in The Advertiser, I chose to run an entity analysis on my chat to identify dates, persons, contact information, organizations, locations, events, products, and media types. Surprisingly the produced results consisted of almost 90% noise (wrong predictions). However, it was still possible to assume the personal address, profession, and country of origin of my friend from the results. The Messenger helped to create knowledge on machine learning-based APIs and text entity analysis. It could be potentially helpful for data analyzation if the precision can be increased.