Beyond Chatbots: A Case Study for AI In Customer Service

Today’s edition of the Augmented Advantage is co-authored with ONTEC AI, a leading provider of Augmented Intelligence solutions that empower teams to securely access, share, and grow their organizational expertise.

Hi there,

Look, I get it. When you hear "AI in customer service," you instantly think chatbots. Those little pop-ups everywhere asking "How can I help you today?"

And yes, chatbots can be great - I've built plenty myself. But the thing is, while everyone's obsessing over making chatbots be more reliable and take over more tasks (which is hard), real money is been made when customer service AI works behind the scenes. No flashy interfaces, no "we have a chatbot" announcements. Just more profit on autopilot.

Today, I'm teaming up with Christian Casari from ONTEC to show you exactly how this works. We'll show you how Sunny Cars, one of Europe's leading car rental companies, is leveraging AI in their customer service - without a single chatbot in sight.

Let's dive in!

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Case Study Context

First, some context.

Sunny Cars isn't your typical car rental company. They don't own a single car. Instead, they work with local rental companies in over 120 countries, packaging their offerings into all-inclusive deals that take the headache out of car rental. Founded in 1991 and grown to a team size of about 160 employees they are a great example of an SME that makes a global impact (and even more so today with AI).

The challenge they faced is that every day, their inbox gets flooded with customer emails.

Every type of query you can imagine:

• "I had to cancel my trip..."

• "My flight was delayed and I missed the pickup..."

• "I accidentally double-booked the car..."

• "I have a question about a charge on my credit card..."

• "Unfortunately, I damaged the car..."

Interestingly, less than 0.8% of all incoming emails actually contained real complaints that Sunny Cars had to deal with. Most emails were what they called "white noise" - stuff that needed proper filing and forwarding, but not necessarily active processing.

Yet their highly qualified customer service team was spending hours just reading and categorizing these emails manually.

And here's where it gets tricky: This process is a bottleneck because it can’t scale. When Sunny Cars wants to grow, they have difficulties finding more skilled customer service staff in today's job market. Plus, spending a ton of money on people just sorting emails instead of solving complex issues isn' really making sense either.

That's exactly where AI comes in. Not to replace, but to supercharge the customer service team.

Here's how they did it:

The 3 AI Workflows Behind the Scenes

Instead of building yet another chatbot, Sunny Cars implemented three "invisible" AI solutions that really moved the needle:

1. Smart Classification System

Every incoming email gets automatically sorted into specific categories like "credit card charge," "damage report," or "refund request." The cool part is that after some initial training hiccups (more on that in a minute), their AI now correctly categorizes over 90% of all emails.

Those hours spent just sorting emails? Gone. Only 10% of the emails need manual sorting while all others are forwarded to the right department or downstream process instantly.

Think about it: When an urgent damage claim comes in, it no longer sits in a general inbox waiting to be discovered - it gets flagged and routed immediately.

2. Auto-Summarization Engine

Ever received a 5-paragraph email that could've been three sentences? The customer service team was dealing with this all day. Now, AI automatically creates a TL;DR for each email and adds it to the top of it.

This was a game-changer for follow-ups. Instead of agents having to re-read entire email threads (sometimes going back weeks), they get an instant overview of what happened. If a customer now asks "What's the status of my case from last week?" whatever agent is currently working on this sees the whole story instantly. No more "Let me look into this and get back to you."

3. Smart Prioritization System

This one's subtle but powerful. The AI analyzes the tone and urgency of each email. A polite "Just wondering about my deposit..." gets handled differently than "THIS IS UNACCEPTABLE!!!".

Before, an angry customer email could sit unnoticed in the inbox while agents worked through tickets in chronological order. Now, truly urgent cases bubble up automatically. Combined with the classification system, this means high-priority issues like damage claims get immediate attention, while non-urgent inquiries get handled efficiently in batches. This is crucial for maintaining that 0.8% complaint rate.

Bear in mind, all of this happened:

• Without changing a single customer-facing process. Customers still write emails like they always did. They still get personal responses from real humans. The only difference is how quickly and efficiently these responses now come.

• Without building a single agentic system. All AI helpers above are built based on pretty straightforward AI workflows - which means shorter implementation time, less technical complexity, and the ability to bring human augmentation in as needed. It’s easy to imagine though how AI agents could help bring this to the next level - for example autonomously pulling together information from different systems to help write a draft response.

For Sunny Cars, this meant they could grow their business without the usual growing pains in customer service. More rentals no longer automatically meant more support staff.

Instead, their existing team could focus on what they do best: solving complex customer issues and delivering great service.

Data Privacy

As you can imagine, with Sunny Cars being a German company and involving a significant amount of sensitive customer data, this project demanded the highest standards of data privacy and security. As a tech-agnostic solution provider based in Austria, the ONTEC team was specifically chosen for their expertise in handling complex and sensitive customer data, ensuring end-to-end GDPR compliance.

Conclusion

What we love about this case study is how it completely flips the script on "AI in customer service." While everyone else is debating whether chatbots should sound more human or handle more complex queries, Sunny Cars just went ahead and solved real problems behind the scenes – focused on driving customer excellence AND profitability.

The key takeaways here are pretty clear:

1. Some of the most valuable AI use cases might never be seen by your customers

2. Start with the actual pain points your team faces, not with what AI can theoretically do

3. You don't need complex AI agents or fully automated solutions to drive real impact

4. Often the best AI is the one that helps humans do their jobs better, not replace them entirely.

So next time someone tells you "We need a chatbot", maybe ask them this: What if we first looked at all the manual work happening behind the scenes? That's often where the real opportunity lies - and a perfect entry point to even more advanced solutions.

Keep innovating (invisibly)!

See you next Friday,
Tobias & Christian

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