My First Time Explaining Customer Service to Herr Schmidt – And Why It Was Harder Than I Thought

Okay, so here’s the thing. I’ve been in Germany for six months now, working as a translator for a small software company. It’s great work, but honestly? The biggest challenge hasn’t been mastering German grammar (though ich schlafe immer noch schlecht when I try to wrestle with the cases!). It’s been trying to explain things – specifically, how artificial intelligence is changing customer service – for this TELC B1.2 writing task.

The Assignment: “Wie KI die Kundenbetreuung verbessert”

My professor gave us a prompt: “Erklären Sie, wie KI die Kundenbetreuung verbessert.” (Explain how AI improves customer service.) It sounded simple enough. I figured, ‘Okay, I’ll write about chatbots and self-service portals. Easy!’ Turns out, it’s a lot more complicated than just listing the features. And that’s partly why I’m writing this – to try and make sense of what I’ve learned and to share my struggles, hopefully with others who are in a similar boat.

My First Attempt – A Disaster in Deutsch

I started by drafting something…well, let’s just say it wasn’t brilliant. I wrote about how AI could answer frequently asked questions and reduce wait times. It was all very technical-sounding, like something out of an industry report. Then, my supervisor, Herr Schmidt (a wonderfully grumpy but kind man), read it and said: “Das ist zu abstrakt! (That’s too abstract!)” He pointed to a sentence that used “Effizienzsteigerung” – efficiency improvement – and just shook his head.

He then proceeded to give me an example. “Imagine,” he said, gesturing with his hands, “a customer calls about their Rechnung (bill). Instead of waiting on hold for twenty minutes listening to elevator music, the AI instantly pulls up the account, identifies the problem – maybe there was a typo in the amount – and offers a solution directly. Das ist praktisch! (That’s practical!)”

I realized then I’d been completely focused on jargon instead of actually explaining it in a way a normal person would understand.

Real-World Examples: Talking to Customers (and My Colleagues)

After Herr Schmidt’s critique, I started paying closer attention to real customer interactions. My colleague, Lena, works in the support department. She told me about a situation where they were using an AI system for order inquiries.

“Ein Kunde schrieb uns eine E-Mail,” she explained, “fragens: ‘Wo ist meine Lieferung?’ (A customer emailed us asking: ‘Where is my delivery?’). The AI immediately checked the tracking information and sent him an automated update with the new estimated delivery date. It saved me at least fifteen minutes!” She said it was a huge help, especially during peak periods when they were swamped.

I also overheard a conversation between Lena and a frustrated customer who couldn’t find the answer to their question on the company website. Lena patiently walked him through the process, but afterwards she explained how an AI-powered chatbot could have instantly provided the information. “Wenn wir eine KI hätten, hätte alles schneller funktioniert!” (If we had an AI, everything would have worked faster!).

Key Phrases and Vocabulary for Telc B1.2

Here’s some useful vocabulary I’ve picked up that might be helpful for this task:

• Kundenbetreuung: Customer Service
• Chatbot: Ein Computerprogramm, das Gespräche führt (A computer program that conducts conversations) – “Wir haben einen Chatbot auf der Website.” (“We have a chatbot on the website.”)
• Selbstbedienungsportale: Self-service portals – “Die Kunden können sich über das Portal selbst helfen.” (“Customers can help themselves through the portal.”)
• Häufig gestellte Fragen (FAQ): Frequently Asked Questions – “Das FAQ beantwortet die meisten Fragen unserer Kunden.” (“The FAQ answers most of our customers’ questions.”)
• Rechnung: Bill/Invoice
• Lieferung: Delivery
• Tracking-Informationen: Tracking Information – “Die KI überprüft automatisch die Tracking-Informationen.” (“The AI automatically checks the tracking information.”)

My Second Draft – A Little Bit Better

This time, I tried a different approach. I focused on using clear, simple language and relating it to everyday experiences. I wrote about how AI can make customer service more convenient, faster, and efficient – but without sounding like a robot!

Here’s a short paragraph from my revised draft: “Kundenbetreuung mit KI ist nicht nur schneller. Stellen Sie sich vor, Sie haben ein Problem mit Ihrem Laptop. Anstatt lange am Telefon zu sitzen und einen freundlichen Mitarbeiter zu warten, kann eine KI Ihnen sofort helfen. Die KI kann Ihre Probleme erkennen, Lösungen anbieten und sogar Ihren Laptop reparieren – ohne dass Sie überhaupt sprechen müssen! Das ist wirklich nützlich. (That’s really useful.)”

Final Thoughts & Learning Points

The biggest lesson I’ve learned is that clear communication is key. It’s not enough to simply know the technical details of AI; you need to be able to explain it in a way that others can understand. And, honestly, sometimes just talking through examples and asking questions – like Herr Schmidt did – makes everything much clearer. Ich muss noch üben! (I still need to practice!).

For anyone taking the Telc B1.2 writing exam on this topic, focus on using real-world examples, practical vocabulary, and clear, simple sentences. Don’t just list features; tell a story about how AI improves customer service. And don’t be afraid to ask for help – like I did!