How to localize the chatbot for a global audience?

Customer service plays an important role in customer retention, but providing fast and reliable support often requires significant time and resources. Process automation helps companies reduce repetitive work while keeping support available outside regular business hours.

According to Salesforce, 89% of customers are more likely to make another purchase after a positive customer experience, while 84% expect companies to respond immediately when they make contact. The same research found that 79% consider customer service when making purchasing decisions.

Language is another important part of the customer experience. According to CSA Research, 40% of consumers will not buy from websites that are unavailable in their preferred language. Companies entering new markets therefore need to provide customer support that is accessible and appropriate for regional users.

Chatbots can help companies handle this demand by answering routine questions, guiding customers, and providing assistance at any time. According to Master of Code, chatbots can manage around 30% of customer support communication, reducing the number of repetitive requests that require direct human involvement.

For international companies, however, offering a chatbot in several languages requires more than translating individual responses. This article explains what chatbot localization involves, which requirements multilingual chatbots must meet, and how a translation management system can support the localization workflow.

What are chatbots?

Chatbots are software applications designed to simulate written or spoken conversations with users. Companies commonly use them to answer frequently asked questions, collect information, guide users through processes, and direct complex requests to human support agents.

Chatbots can be divided into three broad categories:

• Rule-based chatbots: Follow predefined rules, scripts, or decision trees. They are commonly used for frequently asked questions and structured customer support processes.

• AI-powered chatbots: Use natural language processing, machine learning, and language models to interpret requests and generate more flexible responses.

• Hybrid chatbots: Combine predefined workflows with AI-powered capabilities. They can provide approved answers for predictable requests while using AI to handle more complex or open-ended questions.

The continued growth of the chatbot market reflects their increasing use in customer service, sales, and other business processes. The global chatbot market was valued at $4.7 billion in 2022 and reached $5.7 billion in 2023.

Let’s dive into chatbot localization!

Chatbot localization is the process of adapting a chatbot’s content, terminology, conversational flows, formatting, and behavior to a specific language and market. It goes beyond translating individual messages because users may describe the same issue differently across languages and regions.

This is especially important in customer journeys involving sensitive or time-critical information. For example, a customer using an e-commerce platform or banking application may need an immediate answer about a payment, account, or delivery. Unclear wording, incorrect terminology, or an irrelevant response can increase frustration and lead the user to contact a human agent or leave the service.

A localized chatbot should reflect regional language conventions, customer expectations, product terminology, legal requirements, and local formats. A retail chatbot may also need to adapt campaign messages, public holiday references, seasonal offers, and product availability for each market.

Important requirements for multilingual chatbots include:

• using language, expressions, and conversational conventions appropriate to the target market

• applying approved company, product, and industry terminology

• adapting dates, times, currencies, numbers, addresses, and measurement units

• supporting language-specific user inputs, including spelling variations and regional terminology

• following applicable privacy, data protection, and customer communication requirements

• providing a clear path to a human support agent when the chatbot cannot resolve the request

To handle all these conditions, companies need a technical team, a chatbot solution/framework, and a translating team that can adapt content professionally.

Also, special attention should be paid to the TMS (translation management system), as it allows faster processing of the content translation and contains all the multilingual chatbot data in one place.

How can a TMS support chatbot localization?

As we mentioned at the start of this article, process automation is the “magic wand” that reduces businesses’ costs. Because of this, the translation management system is a necessary part of chatbot localization.

With it, the process will be smooth, safe, and take much less time. Let’s examine both options.

Without a translation management system, teams may need to export chatbot content manually, send files to translators, answer contextual questions through separate communication channels, review returned files, and upload completed translations into the chatbot platform. They must also maintain terminology, track updates, coordinate revisions, and ensure that each language uses the latest source content.

This process becomes increasingly difficult as the number of languages, translators, intents, and chatbot responses grows. Shared folders and spreadsheets can support smaller projects, but they often provide limited visibility into translation status, context, and content changes.

With a translation management system, teams can centralize multilingual chatbot content, automate file exchanges, provide linguistic context, and track translation progress in one workflow. The following LingoHub features support this process:

• Import and export chatbot content: LingoHub supports more than 40 file formats and allows teams to import content manually or synchronize it through repository integrations. Content can also be exported in XLIFF format when it needs to be shared with external translation tools or language providers.

Explore our available integrations.

• Connect workflows through the REST API: The LingoHub API can support custom integrations between localization workflows and chatbot systems. The exact implementation depends on the chatbot platform and its available APIs.

• Centralize translator collaboration: Translators, reviewers, and localization managers can work within the same environment. Permissions determine which workspaces, projects, languages, and content each participant can access.

• Apply AI translation and linguistic context: LINA, translation memories, glossaries, style guides, labels, screenshots, and segment descriptions provide translation suggestions and context for multilingual chatbot content. The appropriate level of human review depends on the content, language, and customer support risk.

• Automate quality checks: Quality checks identify potential issues involving terminology, whitespace, HTML markup, placeholders, punctuation, length, and formatting before content reaches production.

• Organize chatbot content: Separate projects, files, branches, and labels help teams structure content by chatbot, product, release, language, or use case and find relevant segments more easily.

LingoHub provides localization managers with visibility into multilingual content and workflow progress, while developers can connect localization with repositories, APIs, and software delivery processes. Translators and reviewers receive linguistic context, translation suggestions, and quality information directly within the editor.

Together, these capabilities help customer support, product, development, and localization teams coordinate multilingual chatbot content within one platform.

Whether you are a small business, rising star, industry leader, or enterprise, LingoHub has a solution to fit your business-specific needs.

Conclusion

Chatbot localization helps companies provide customer support that reflects the language, terminology, formats, and expectations of each target market. A reliable workflow should combine linguistic expertise, product context, technical integration, quality assurance, and a clear process for escalating unresolved requests to human support agents.

LingoHub helps teams centralize multilingual chatbot content, connect localization with development workflows, provide context to translators and AI, and identify potential quality issues before publication.

Try LingoHub for free or book a demo to discuss your chatbot localization workflow with our team.