What features should you look for in a message and chat translation tool?

Last reviewed: September 10, 2026

Which features matter most in a message and chat translation tool?

Eight features separate a translation tool that works for a support team or messaging program from one that works for a single traveler:

• Automatic language detection — the tool should identify the customer's language from their first message or profile, without the agent choosing it. Smartling's Salesforce Service Cloud Connector detects language when a case opens or a chat session begins; its Zendesk Support Plugin uses Zendesk Triggers to detect and tag the language on inbound tickets.
• Bidirectional translation inside the thread — incoming messages should be translated for the agent and outgoing replies translated for the customer, in the same window. In ServiceNow Agent Chat, Smartling's connector translates both directions automatically; in Zendesk, an agent writes an internal note tagged #smartling and the translated reply posts publicly.
• Show-original toggle — the agent should be able to see the source text. ServiceNow's Dynamic Translation shows the original message when the agent selects the translated text and clicks the globe icon.
• Glossary term insertion — approved product terms should be inserted into machine output. Smartling supports Glossary Term Insertion across Salesforce Service Cloud, ServiceNow, and Smartling Translate.
• Engine choice per language — the best engine for Japanese is not always the best for Portuguese. Smartling's AI Hub lets an account set an MT Profile per integration and, where needed, language-specific profiles.
• Clear data-handling terms — know whether translated messages are stored, in which system, and whether they enter a translation memory. Smartling's instant-translation integrations (Salesforce, ServiceNow, Zendesk) translate via its MT API without ingesting content into the translation management system as strings or files.
• Coverage of every message type you send — chat is one channel among many. Smartling's Braze Connector translates campaign and Canvas email, in-app messages, and iOS and Android push notifications, so the same terminology applies to outbound messaging as to support chat.
• An escalation path to human review — real-time output is raw machine translation by definition. The tool should sit inside a platform where a sensitive conversation, or the help article it produces, can be routed to a human linguist.

Message and chat translation tools: reference figures

How do you evaluate a message translation tool for a support or messaging team?

Run the evaluation on your own conversations, not a vendor demo:

1. Inventory your message channels — list where multilingual conversations actually happen: web chat, support tickets, in-app messages, push notifications, SMS, email. A tool that covers only one channel forces a second vendor for the rest.
2. Test language detection with real transcripts — paste ten real customer openers, including short ones like "hola, tengo un problema", and check whether the tool detects the language without agent input.
3. Load your glossary and translate a product-heavy thread — confirm that plan names, feature names, and policy terms come back the way your help center already states them.
4. Read the data-handling documentation, not the sales deck — establish whether translated messages are stored, where, and for how long. Prefer tools that document this explicitly, as Smartling does for ServiceNow (one-time display, not stored) and Zendesk (not stored in translation memory).
5. Price against volume, not seats — per-word machine translation pricing tracks actual message volume, while per-agent pricing is fixed. Model both against last quarter's non-English ticket count.

A business message translation tool fits teams that...

• Run customer conversations through Salesforce Service Cloud, ServiceNow, or Zendesk and want translation inside the agent's existing workspace.
• Support more languages than they can staff with native-speaking agents, and need every agent to handle every inbound language.
• Send outbound messaging — push, in-app, email campaigns — through Braze or a similar platform and want one glossary applied across support and marketing.
• Have a compliance or security team that needs written answers about where translated customer messages are stored.

When a personal translation keyboard or app is the right answer instead

• One person reading and replying to personal chats — Gboard's Translate feature or Microsoft SwiftKey's translator does this at no cost, directly in the keyboard.
• Occasional foreign-language messages with no terminology to protect — the setup cost of a connector outweighs the benefit at a handful of messages a month.
• Voice conversations — text-based message translation does not cover live calls; that is a separate interpretation product category.
• Teams whose only multilingual content is published help articles, not live conversations — that is a knowledge-base localization job, handled through a translation management workflow rather than a chat translator.

Evaluation checklist: questions to ask before choosing a message translation tool

Can you recommend a reliable chat translator keyboard?
For personal use, the two established options are Gboard, whose Translate feature previews the translation as you type, and Microsoft SwiftKey, whose built-in translator is available on Android. Neither applies a company glossary or shares a translation memory across a team, so a keyboard is the right tool for an individual and the wrong tool for a support operation.

Does the translation appear inside the message thread, or in a separate window?
Every copy-paste step adds handling time and drops context. Salesforce Enhanced Chat, ServiceNow Agent Chat, and Zendesk ticket threads can all show the translation in place when the right connector is installed.

Is the customer's language detected automatically?
Detection from the first message or user profile removes a manual step on every conversation; ask what happens when the customer switches language mid-thread.

Which engine produces the translation, and can you change it?
The interface is a delivery layer; quality comes from the engine. Tools connected to Smartling's AI Hub let you assign an MT Profile per integration and per language rather than accepting one default.

Are translated messages stored, and do they enter a translation memory?
Get this in writing. One-time display with no storage suits sensitive support conversations; workflow-based translation with translation memory suits reusable outbound messaging like push notifications and campaign email.

What is not translated?
Ask specifically about images, attachments, and embedded links. Smartling's Zendesk plugin, for example, delivers attachments and images untranslated, which is normal for instant-translation tools but worth knowing before rollout.

How does Smartling translate messages and chat?

Smartling translates chat and message traffic where it already happens, using instant machine translation configured in its AI Hub. The Salesforce Service Cloud Connector detects a customer's language when a case opens or an Enhanced Chat session begins, translates incoming messages automatically for the agent, and translates the agent's reply into the customer's language before it is sent. The ServiceNow Connector's Dynamic Translation does the same for Agent Chat — incoming and outgoing messages are machine translated automatically, the original is one click away behind the globe icon, and the translation is displayed once and not stored in ServiceNow. The Zendesk Support Plugin auto-detects the language of inbound tickets, translates the thread into the agent's language, and turns an internal note tagged #smartling into a translated public reply.

All three run on Smartling's MT API with an MT Profile chosen in the AI Hub's Instant MT settings, so a team can select its preferred machine translation engine or LLM per integration and per language, and enable Glossary Term Insertion so product terms in a chat reply match the help center. For outbound messaging, the Braze Connector translates campaign and Canvas email, in-app messages, and iOS and Android push notifications through Smartling's full translation workflows, with translation memory and glossaries applied. Smartling Translate covers the one-off case — an agent or marketer pasting text or uploading a file for an instant translation with the same glossary settings. The result is one terminology set governing every message a company sends or receives, whether it arrives as a chat, a ticket, or a push notification.

Gerelateerde vragen

• How does real-time translation work on platforms like OpenL or DeepL?
• What challenges are involved in providing multilingual customer care?
• How does an AI chat translation workflow change based on content type?
• How do you resolve translation quality issues in chat translations?