So, your business is growing. That’s great news! But it also means your customer base is starting to look a lot more global. You’re no longer just answering questions from down the street; you’re getting tickets from all over the world. And those customers expect you to help them in their own language. It's not just a nice-to-have anymore, it's a basic expectation.
For years, helpdesks have tried to solve this with a feature called "dynamic content." On paper, it sounds pretty clever: a system of placeholders that serves up pre-translated bits of text to deliver localized messages. In reality, anyone who has managed this knows it can quickly turn into a tangled web of manual updates and inconsistent support.
This guide will walk you through what dynamic content is, how it works in platforms you probably use, and why its limitations often create more work than they save. Most importantly, we'll look at a more modern, AI-driven way to offer multilingual support that's actually scalable and responsive.
What is dynamic content?
In customer support, dynamic content is basically a feature that lets you create reusable blocks of text that change automatically based on a customer's language. Think of it as a set of smart templates. Your helpdesk uses them to "speak" your customer's language without an agent having to copy and paste from Google Translate.
The system uses placeholders. For instance, you could create a placeholder like "{{dc.shipping_info}}" to pop into your macros, triggers, and automated emails. When a customer from France submits a ticket, your helpdesk sees their language is set to French and automatically swaps that placeholder with the French version of your shipping info you already wrote.
Platforms like Zendesk are pretty well known for this feature. The setup involves creating a "default variant" (usually in English) and then painstakingly adding a separate "variant" for every single language you need to support. It's definitely a step up from having no system at all, but it’s far from a perfect fix.
The old-school approach to multilingual support
Legacy helpdesks have been using rule-based systems to juggle multiple languages for a while. The specifics can differ, but the core idea is always the same: you manually map out every possible translation and then hope the system picks the right one at the right time.
Rule-based placeholders in Zendesk and ServiceNow
The most common method involves a support manager or admin setting up every piece of dynamic content one by one. They create an item, write the default text in English, and then start the tedious task of adding translated "variants" for Spanish, German, Japanese, or whatever other languages they support. This usually involves exporting giant spreadsheets of text, emailing them over to a translation agency, and then importing them back into the system.
Agents then try to use these placeholders in their canned responses and automated workflows, trusting the system to match the right variant to the user's language setting. The main takeaway here is that it's a completely manual and proactive job. If you want to localize a message, you have to guess you'll need it and build the variant ahead of time. There’s no room for nuance or spontaneous issues.
Conditional content blocks in other platforms
Other platforms, like Dynamics 365, use something called conditional content blocks. Instead of simple placeholders, you build "IF/THEN" rules that show a different block of text based on certain criteria. For example, "IF the customer's country is 'United Kingdom', THEN show the UK-specific return policy."
This approach can turn into a technical mess, fast. It often depends on data entered by the user, which is never consistent. A customer might type "UK," "United Kingdom," or "U.K.," and you'd need a separate rule for each one to get it right. To make a system like this remotely reliable, you usually have to pull in a developer to help clean up messy data and customize things.
The hidden problems of dynamic content
While dynamic content looks practical on the surface, its manual nature creates some serious headaches that only show up once you start to grow.
The scalability and maintenance nightmare
When you only support two or three languages, managing a few dozen placeholders is doable. But what happens when you expand into ten new markets? Or when you launch a new product with its own set of support policies?
Suddenly, the number of dynamic content items explodes. A tiny update to your return policy might mean hunting down and editing dozens of individual variants. The process is slow, boring, and practically designed for human error. It's incredibly easy to miss one variant, which leads to customers getting outdated or contradictory information. Before you know it, managing your library of "dynamic" content feels like a full-time job.
Inconsistent quality and hidden costs
The workflow itself causes issues. When you have to export text, send it to a translation agency, wait for it, and then re-import it, you create delays and a disconnect. It's almost impossible to maintain a consistent brand voice when different translators are working on isolated snippets without seeing the full conversation.
On top of that, this feature often costs extra. Platforms like ServiceNow make you buy their "Dynamic Translation" feature as a paid add-on. And you still have to pay for the third-party translation service. This creates multiple layers of costs that are hard to track and predict.
The rigid, robotic approach
The biggest weakness of traditional dynamic content is that it isn’t really "dynamic." It's just a system of static, pre-written text blocks. It can't adapt to the specifics of a customer's question or answer anything you haven't already written a variant for.
This leads to a robotic and unhelpful experience. The system isn't smart; it's just swapping one piece of static text for another. When a customer has a unique problem, a pre-written placeholder is more likely to make them angry than to actually help.
The modern alternative: AI-powered support
Instead of getting tangled in a web of manual placeholders, modern AI offers a much cleaner and more effective solution. The whole idea shifts from manually managing translated snippets to using an intelligent tool that generates accurate, context-aware responses on the fly.
Unify all knowledge, not just a few approved snippets
A tool like eesel AI doesn't rely on pre-written variants. Instead, it connects to all of your knowledge sources, your help center, past support tickets, and even your internal docs in places like Confluence or Google Docs, to build a complete picture of your business.
The advantage here is huge. The AI automatically learns your brand voice, common solutions, and technical details from the thousands of conversations you've already had. It can answer an almost unlimited range of questions in any language, not just the few you’ve had time to create placeholders for.
Go live in minutes, not months
Forget about the weeks or months it takes to build a traditional dynamic content library. With eesel AI, the setup is incredibly simple and self-serve. You can connect your helpdesk with a single click, and the AI starts learning from your existing knowledge right away. You don't have to manually create, translate, and import hundreds of variants. From day one, the AI detects the customer's language and generates a useful response from its unified knowledge base.
Combine smart automation with human control
An AI-powered approach gives you more options than just full automation. For teams that want to keep a person in the loop, the eesel AI Copilot can draft replies for agents right inside the helpdesk. It suggests accurate, localized responses, helping agents answer tickets faster while still having the final say on quality.
Beyond just answering questions, the AI can also handle complex tasks. It can automatically tag tickets by language, route them to the right teams, or escalate issues based on customer sentiment. This frees up your team from hours of manual sorting and triage.
| Feature | Traditional Dynamic Content | The eesel AI Approach |
|---|---|---|
| Setup | Manual creation of hundreds of variants | One-click integration, learns automatically |
| Knowledge Source | Pre-written, static text snippets | Entire knowledge base & past tickets |
| Maintenance | High; requires constant manual updates | Low; AI stays current as knowledge evolves |
| Flexibility | Rigid; inserts pre-defined text | Truly dynamic; generates contextual replies |
| Scalability | Poor; difficult to manage with more languages | Excellent; scales effortlessly to new languages |
A look at pricing models
The cost of supporting multiple languages can vary a lot depending on the platform and method you choose.
-
Zendesk: The dynamic content feature is only available on their "Support Professional" plan and higher. This means you’re often forced to upgrade to a more expensive tier just for a basic localization tool, even if you don't need the other bells and whistles.
-
ServiceNow: Their "Dynamic Translation" tool is a separately licensed product. So, you have to pay ServiceNow for the feature, and then you also have to pay a third-party service like Google Translate or IBM for the actual translations. This creates two separate, and often unpredictable, bills.
-
eesel AI: The pricing is straightforward. Plans are based on the number of AI interactions, not how many tickets you resolve. This keeps your costs predictable, so you're not penalized for being efficient. All the core products, including the powerful multilingual features, are included in every plan.
Move beyond placeholders
The old method of providing multiple language support with dynamic content was a necessary but clunky solution to a hard problem. While it was better than nothing, the rule-based approach is manual, inflexible, and just doesn't work for modern, global businesses.
Modern AI platforms like eesel AI offer a much smarter and more efficient solution. By unifying all of your existing knowledge and generating contextual replies on the fly, you can finally move beyond static placeholders and deliver genuinely helpful and dynamic support in any language.
Ready to ditch the manual placeholder management for good? See how eesel AI can transform your global customer service in minutes. You can book a demo or start your free trial today.
Frequently asked questions
Traditional dynamic content involves manually creating pre-translated text blocks (variants) for each language. These placeholders are then inserted into macros, triggers, and automated emails, with the system swapping them out based on the customer's language setting.
As a business expands to more languages and products, the number of variants explodes, making maintenance a nightmare. Updates become slow, error-prone, and maintaining consistent quality across numerous manual translations becomes nearly impossible.
AI solutions, like eesel AI, connect to all your knowledge sources to dynamically generate context-aware responses in any language, rather than relying on static, pre-written snippets. This approach is highly scalable and adapts to unique customer questions.
No, setting up an AI solution like eesel AI is typically fast and self-serve, often taking minutes instead of months. It integrates with your existing helpdesk and immediately starts learning from your current knowledge base without manual variant creation.
Yes, AI tools can be configured for various levels of automation. For instance, the eesel AI Copilot drafts localized responses directly within the helpdesk, allowing agents to review and approve them, ensuring human quality control.
Traditional dynamic content often requires expensive software upgrades and additional fees for third-party translation services, leading to unpredictable costs. AI solutions typically offer straightforward pricing based on interactions, including all multilingual features without hidden fees.
