Originally a journalist and editor, I came into touch with online content while working as a freelancer editor for aexea. Out of the need to produce mass-content for e-commerce and shops, the idea arose to automate parts of the content production. What startet out as an experimental project in text-spinning advanced further and further, until it became the “Automatisierte Texterstellung” – a software environment with its own script-language, capable of deriving and inferring logical statements from product datasets and using them to generate a slim-taylored text about the product.

While designing and developing a tool for automated text-generation, I've had quite a few glances at customer databases. Those ranged from lean hardfacts-databases to ancient publishing-driven cms-related databases, and they all had their flaws and advantages for my application.

Since I strongly believe that solutions for automated text creation are on the rise, and will become even more popular in the future, I want to give you an insight into the things I learned about the relationship between data and language. I want to share my experience in making data talk and give you an insight into how a proper database can help you create convincing and user-friendly content.