Your customers speak German, Spanish, Italian... but what about your team? Only French. How can you handle these tickets without ruining customer relations by using Google Translate? 🤔
Multilingual customer service has become a major challenge for companies expanding internationally. But recruiting multilingual agents for each market is expensive. And juggling external translation tools is a monumental waste of time.
Good news: there is another way. An approach where your agents can handle any ticket, in any language, without leaving their work interface. Let's go! 🚀
Multilingual customer service is a company's ability to support its customers in their native language, regardless of the contact channel.
In plain English?
When a German customer writes to you in German, they receive a reply in German. Not a roughly translated message that reeks of robotics.
Characteristics of good multilingual support:
The challenge? Most customer service teams are not made up of polyglots. And that's normal: recruiting an agent who is fluent in five languages is mission impossible (or astronomically expensive).
Case in point:
An agent receives a ticket in Italian. Using the manual method, they must:
Result: 5 minutes lost. Multiply that by 20 multilingual tickets per day, and you have 1 hour and 40 minutes of productivity lost. Per agent. Per day.
International trade has never been so accessible. A French e-commerce store can sell in Germany, Spain, the Netherlands, and more with just a few clicks.
The figures speak for themselves:
📈 75% of consumers prefer to shop in their native language, even if they understand English.
💰 40% of customers refuse to buy from a website that is not in their language.
🚀 Multilingual companies have an average customer satisfaction rate that is 20% higher.
⏱️ Processing a ticket in a foreign language takes 2 to 3 times longer without the right tool.
🌍 Europe has 24 official languages: it is impossible to recruit an agent for each one.
The problem? Customer expectations are the same in every language. They want a quick, accurate response in flawless French (or German, or Spanish).
Hire agents who speak multiple languages. Simple on paper, complex in practice.
Advantages :
Disadvantages:
Google Translate, DeepL... Agents copy and paste to understand and respond.
Advantages :
Disadvantages:
The agent remains in their interface. Translation is done automatically, in both directions.
Advantages :
Disadvantages:
It is this third method that Klark has developed with the Translate feature.
No more juggling between tabs. The agent processes a ticket in German just as quickly as a ticket in French. The result: productivity is maintained, even in international markets.
A customer who receives a response in their own language, with the right tone, feels understood. A relationship of trust develops naturally.
Want to launch in Italy? No need to recruit an Italian-speaking team. Your current agents can handle it.
No more rough translations that sound unprofessional. Every message is tailored to the language and culture of the recipient.
Handling a ticket in a language you don't speak fluently can be stressful. With the right tool, agents can work calmly in their native language.
Your brand has a personality. It must shine through in all languages, not just in English.
A French agent can process a German ticket received at 8 a.m. without waiting for the German team (if it exists) to become available.
Google Translate, DeepL, Microsoft Translator...
These tools are excellent for understanding a text or translating a document. But they are not designed for customer service.
Problems :
Some ticketing tools offer built-in translation features.
Advantages :
Limits:
Tools such as Klark that combine generative AI and translation with an understanding of the customer service context.
Advantages :
Situation:
A French fashion boutique launches its website in Germany. Tickets arrive in German, but the CS team is 100% French-speaking.
Without a suitable solution:
Agents spend five minutes per ticket translating, understanding, writing, and re-translating. The queue is exploding. German customers are complaining about the slowness.
With Klark Translate:
The agent opens the German ticket. They immediately see a summary in French, the translation of the last message, and a suggested response ready to be sent in German. They validate or adjust it in French, and Klark translates it. Total time: the same as for a French ticket.
Situation:
A French SaaS startup has customers in Spain, Italy, and the Netherlands. Technical requests arrive in four different languages.
The challenge:
Technical issues require a detailed understanding. A poor translation can lead to an incorrect solution.
The solution:
With a tool that understands the context (ticket history, product involved, technical issue), the translation is accurate. The agent understands exactly what the problem is and can respond appropriately.
Situation:
A marketplace connects sellers and buyers from all over Europe. Disputes often involve parties who do not speak the same language.
Complexity:
The agent must understand both versions (Spanish buyer, German seller) and respond to both in their respective languages.
With a multilingual solution:
The agent works entirely in French. He understands both parties, writes his responses in French, and each recipient receives the message in their own language.
"Machine translation makes mistakes, my clients will receive gibberish."
False. Modern generative AI tools produce professional-quality translations. And above all, the agent remains in control: they can proofread, adjust, and validate before sending.
"My agents will lose their language skills."
The goal is not to replace existing language skills, but to enable all agents to handle all tickets. A bilingual agent remains valuable for complex cases.
"It's too expensive for our volume."
The calculation is simple: how much does 1 hour and 40 minutes of lost productivity per agent per day cost? How much does an unsatisfied customer who leaves for a competitor who responds in their language cost?
"Our customers will feel that it has been automatically translated."
With AI that adapts to brand tone and conversational context, the difference is undetectable. The customer receives a natural message, not a robotic translation.
Essential criteria:
Questions to ask before choosing:
Chatbots and AI assistants will be able to handle complex conversations in any language, with quality indistinguishable from that of a native speaker.
Beyond language, the tools will adapt to the cultural codes of each market (level of formality, local expressions, cultural references).
Call centers will be able to handle calls in any language thanks to real-time voice translation.
At Klark, we developed Translate to solve a real-world problem: enabling any agent to handle any ticket, in any language, without friction.
How it works in practice:
Klark automatically detects the language and suggests a ready-to-send response, already translated into the customer's language.
In this window, the agent sees:
He can read, understand, modify, and refine the suggested response. All of this in French (or in his native language).
Once validated, the response is sent to the customer in their language, with the right tone and wording.
What changes for the agent:
What changes for the customer:
Klark adapts to your brand's business rules and tone, and learns from your conversations to continuously improve. All of this can be deployed in minutes, without changing your tools or habits.
Your international customers deserve the same quality of service as your French-speaking customers. And your agents deserve tools that simplify their lives, not add extra steps.
Effective multilingual customer service isn't about recruiting an army of polyglots. It's about empowering every agent to handle every ticket, regardless of language. 🚀
About Klark
Klark is a generative AI platform that helps customer service agents respond faster, more accurately, without changing their tools or habits. Deployable in minutes, Klark is already used by over 50 brands and 2,000 agents.
