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Case Study

Scaling Multilingual Support for European E-commerce Platform with AI-Powered Translation

The client is a fast-growing e-commerce company operating across Europe, offering a wide selection of electronics and quick delivery. The store receives a high volume of live chat inquiries daily, ranging from order status checks to return requests.
icon Challenge

Scaling multilingual support without scaling language teams

As demand grew across Germany, Spain, the Netherlands, and Norway, the client needed to extend the capabilities of its existing English-speaking team, rather than replace agents or build separate native-speaking teams for each market.

01

Fast native-language support

Customers expected quick responses in their own language without delays from language-specific routing.

02

Consistent quality across markets

The client needed the same service standards across regions without increasing staffing complexity or costs.

03

Seamless workflow integration

The solution had to fit the existing support stack without adding manual translation steps for agents.

icon OPERATING MODEL

One team, multiple languages

Customers write in their preferred language while agents continue working in English. AI automatically detects and translates incoming messages, then translates agent responses back into the customer’s language.

The entire operation runs through one shared queue, with no manual translation or language switching required from agents.

Step-by-step implementation

01

Needs analysis and scoping

  • Prioritized German, Spanish, Dutch, and Norwegian
  • Selected high-volume intents: tracking, returns, payments
  • Mapped chat workflows and integration requirements
02

AI translation integration

  • Integrated translation into the existing support platform
  • Enabled automatic language detection
  • Automated translation routing with no agent switching
03

Pilot and testing

  • Tested localized real-world scenarios
  • Agents responded in English while AI handled translation
  • Reviewed tone, clarity, and accuracy across languages
04

Quality assurance

  • Trained agents to write for accurate translation
  • Added native-language fallback for edge cases
  • Introduced translation logs for ongoing QA
icon Results

Lower costs, stronger multilingual performance

A centralized multilingual support model reduced operating costs while improving response speed, agent productivity, and customer satisfaction across languages.

34%

lower language support costs within the first 3 months

91-94%

CSAT maintained across all supported languages

23%

faster first response times for non-English chats

18%

more chats handled per agent through centralized workflows

OPERATIONAL IMPROVEMENT

  • 100% of incoming chats handled through one shared queue, regardless of language

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