The technology of automated text creation is still new for many people. We are often asked about the experiences of our customers and their use cases. We took this demand as an opportunity to ask our customer Pascal Baumgartner from Shirtracer a few questions.
Please introduce yourself and tell us something about your work at Shirtracer.
My name is Pascal Baumgartner and I work as Online Marketing Manager for the content department at Shirtracer GmbH and therefore also for the text automation for our product texts. We print textiles such as T-shirts, hoodies, bags or baby bodies and are constantly expanding our product portfolio. We exist already for about ten years, currently our focus is on sales via the German Amazon Marketplace.
You already came across AX Semantics during your studies – how did it come about?
I studied technical journalism at the TH Nuremberg. Since I had been personally interested in the subject of robot journalism for quite some time and considered the field to be underestimated, I decided to write my bachelor thesis on it. The title of my thesis was “Robot Journalism – How the Jobs of Journalists Will Change” and since there was hardly any specialist literature at the time, I conducted many expert interviews – including with AX Semantics.
What problem did you want to solve when you started with AX Semantics at Shirtracer?
Our motivated graphics team develops new designs every day, so that we also upload new products to the marketplaces every day. Each design is offered on different raw products in different sizes and colours – each variant counts as a separate product, so that the number of products (number of designs * number of products) is multiplied. Manual texting of the products would be far too resource-intensive and therefore not possible. Automated text generation enables us to create an individual description for each product and upload it directly with the product.
How well does AX Semantics work under Amazon’s specifications?
We are currently in the middle of the test and start phase. Amazon has limitations at every place that can contain text. Since the number of characters in the maintained product data does not always match, we are currently not able to solve everything 100 percent optimally. We will closely monitor the effects of the new texts in the near future, but we are already seeing a positive trend.
What are your next steps?
Analyses and evaluations provide us with valuable information about our customers. We want to automatically incorporate this information into the texts in line with the product in order to improve visibility and offer our customers added value. Internationalization is also on the agenda. We already have many orders from abroad and of course would like to provide our customers with texts in the local language. Parallel to this, we are currently developing a concept for a new B2B platform (dropshirt.de) and a shop for customizable running shirts.
Who would you recommend AX Semantics to?
In the area of e-commerce AX Semantics is definitely worthwhile for any company with a large number of products. In the field of journalism, the software is particularly interesting for online portals with recurring content, which differ only in their data content, such as sports, weather or financial reporting.
Hey, I am Lisa! I love writing and I have been writing for almost my whole life. As a child, I started writing short stories for kids. I finished my practical semester in 2011, and since then I have been fascinated by the large field of successful texting for the web. While working as an online editor, I wrote texts for many years and trained the text robot of AX Semantics to write even more texts. Today, as an online marketing manager at AX Semantics, I continue my passion for writing about the new possibilities in content creation through automated text generation.