Speak the same language as your customers: AI translation made easy

It’s nice to have friends in distant places, but you’ll get much more out of your time with them if you can understand each other. 

Brands have a similar problem when they expand to new territories. Research indicates that 76% of ecommerce customers buy more if they’re browsing products in their own languages, while up to 40% won’t buy from websites that aren’t using their language. 

You can work as hard as you like on your digital content, researching demographics, personalizing, and refining your voice for the specific demands of the market landscape, but if you can’t make yourself understood by customers that speak a different language, that effort could all be for nothing. 

Long story short: In a global marketplace, translation can make a huge difference to ecommerce margins. But if you aren’t providing translated text, or if there’s friction with your translation experience, it’s likely that customers will turn to a competitor’s site where the shopping journey is easier. 

But languages are complex and constantly evolving, and translation can be a minefield of misunderstanding. While there’s no shortage of tools to convert your text into different languages, finding the words to capture exactly the meaning and cultural nuance that you need can be challenging. 

The good news is, brands can leverage technology to make that job easier. In particular, we can now apply artificial intelligence (AI) tools to address translation challenges, and increase the precision and impact of our translated text.

In this post we’re going to look more closely at AI translation, and how you can use it to produce multilingual content at scale. 

Translation defined

In the context of digital marketing, speaking your customer’s language (or languages) means applying a translation process to the text content that you publish to your digital channels. 

Traditional translation software, also referred to as machine translation software, typically relies on a series of predefined, rules-based algorithms and static vocabulary databases to automate the conversion of one language to another. 

However, traditional machine translations are limited to the predefined capabilities of the software, with limited memory, and they can struggle to take contextual variables into account when converting between languages. 

That means they can’t always capture emerging linguistic trends, grammatical nuances, idioms, and ambiguities, or any of the countless variables that influence language every day. And, while machine translations might generate technically accurate translations, they can struggle to produce natural phrasing or to match the conversational style that many organizations cultivate for their brand voice.

That’s where AI translation can make a difference. 

AI language translation

Where conventional translation technology is built on predefined rules with limited datasets, AI-supported translation technology leverages neural networks and machine learning to manage exponentially larger amounts of data, and continually improves and adapts — essentially, mimicking the functionality of human brains. 

Modern AI translation systems use transformer architectures, a type of neural network that enables them to understand language at a semantic and syntactic level, and to apply contextual understanding to the translation process. Rather than converting word-by-word, sentence-by-sentence, or even paragraph-by-paragraph, AI translation can deal with content holistically, and adapt to emerging data points, like cultural context or local terminology, in order to better capture meaning.

This results in translations that sound more human-like, consistent, and brand-aligned. For example, a traditional engine might translate, “It’s raining cats and dogs,” literally, while an AI model would recognize it as an idiom and offer an equivalent in the target language.

This approach results in highly naturalistic translations that are not only generated quickly and accurately, but that emulate the styles and tones of human translation and keep pace with evolving linguistic trends and nuances. 

And for content teams that are seeking to scale, the computing power behind AI translation also means that it can handle conversion to multiple languages at the same time. 

Ultimately, AI translation is not just about speed and accuracy, but about delivering meaningful, audience-aware communication that resonates across cultures.

Translation vs. localization 

It’s worth pointing out the difference between translation and localization. Here’s a good rule of thumb: translation is about content and localization is about context. 

While translation concerns the conversion of text (or speech) from one language to another, localization refers to the broader adjustment of that content to meet the needs and preferences of a specific regional audience. Localization could include the promotion of certain products popular in a given region, for example, or a focus on certain types of marketing campaigns. That process could be well supported by translation, which would be directly focused on the conversion of the text content for that region. 

In that sense, while translation is frequently part of localization, it isn’t always critical to it. You could, for example, have an audience made up of speakers of two different languages — say, English and Spanish speakers in the Southwest United States — but who otherwise share the same behaviors and preferences. 

AI vs. human expertise

It’s also important to remember that AI language translation isn’t about replacing human translation expertise or removing human creativity from content creation. That’s also true for the localization process, where human expertise and understanding of regional differences and nuance is needed more than ever. 

With that in mind, AI tools have the most impact when they’re helping brands maximize the value of their human experts. By speeding up the translation workflow, and boosting its accuracy, AI allows human translators and editors to spend less time intervening manually, and more time on review, where they can refine and optimize content, and add the spark that keeps customers interested and engaged. 

Multilingual content challenges

What kind of problems are AI translation technologies solving for brands, editors, and digital marketing teams? Let’s dive in.

Maintaining brand consistency

Digital content is your brand’s voice. It defines your presence on the market and your relationship with your customers. When you translate content, it can be difficult to ensure that the translated version is saying exactly what you need it to say, while maintaining the tone and consistency of your brand voice for your overseas audiences. Eventually, that loss of control can fragment your message, and confuse customers. 

Capturing linguistic nuance 

Every language has unique idioms, expressions, nuances, and ambiguities that don’t convert directly into another language. In these instances, it can be difficult to capture meaning; conventional translation software may err toward a more literal interpretation of the text, producing an odd or flat-out incorrect translation. 

Workflow integration 

It can be difficult to integrate the translation process with content publication. Written content often changes significantly from drafting to publication, and may even need to be updated after publication. Brands that publish a large amount of content, or that have busy publication schedules, may find it difficult to apply translations efficiently, and end up sending files back and forth between stakeholders for conversion and review. 

Scaling translations 

When brands need to publish content in multiple languages, or produce a greater volume of content, it can be difficult to scale their translation process. Scaling necessarily increases the burden of translation; brands need to be able to maintain the quality and integrity of an expanded translation process in order to maintain the accuracy and consistency of their voice. 

Technology integration

There may be compatibility problems when integrating third-party translation tools with the wider tech stack, while many legacy content management systems (CMSes) restrict (or do not permit) third-party plugins. In these cases, brands may have to develop complex workarounds to facilitate even simple translations, including manually copying and pasting translated text between different apps. 

The advantages of AI translation

AI tools not only help brands address the translation challenges outlined above, but boost the performance of their text content in several ways. 

Enhanced user experiences 

Since AI language models can leverage vast volumes of data to power their translations, they’re much more effective at not only producing accurate translations, but capturing cultural nuance and the idiomatic use of language. The smoother and more effective your translations, the more enjoyable the overall digital experience for users — and the greater the likelihood that they’ll convert. 

Accessibility

It’s worth noting that translations aren’t just a means to drive engagement and conversions — they’re also critical for the accessibility of your website. Effective AI translation opens your content up to different kinds of users, and ensures that you’re catering to diverse audiences. This is all the more important in light of recent regulatory changes, such as the EU’s Accessibility Act, which requires, for example, brands to add alt text to image content. 

Search visibility

AI translation boosts your SEO performance in the locations that you’re publishing. Not only will it help you capture relevant keywords, your translated text will sound more natural, increasing its relevance and utility to search engines addressing queries in those languages. AI tools can also help you automate the addition of translated metadata to your content (such as alt text descriptions for images), increasing the likelihood that your pages appear in rich results. 

Continual improvement

The relationships that brands build with their customers are always evolving to meet the demands of new technologies, new market trends, new preferences, and so on. To that end, AI translation contributes to a brand’s efforts to create a culture of continual improvement, allowing marketing teams to find new ways to talk about their products, and refine their message to maximize the impact of content. 

Transcreation 

Brands that equip themselves with AI translation tools are not only capable of translation, but transcreation — that is, the creation of completely new content in different languages. AI translation can help brands spin up specific new content pieces — blogs, product pages, campaigns — quickly, in order to capitalize on region-specific opportunities, such as Black Friday (the day after Thanksgiving in the U.S.), or the U.K.’s Boxing Day (the day after Christmas Day). 

Cost effectiveness

The integration of AI tools is a value-adding strategy. AI can speed up existing translation workflows, which, critically, empowers brands to scale quickly to meet new demands. While initial investment in AI technology may be necessary, over time it can help brands reduce their marketing spend. 

Integrate translation AI with Contentful

The global digital landscape is crowded and competitive — marketing teams need reliable, accessible, accurate translation tools, which don’t limit their creative flexibility or freedom. 

That’s where Contentful comes in, putting an array of powerful AI tools at your fingertips — including our native AI Actions feature. 

Contentful’s AI Actions streamlines every aspect of content creation, editing, and management in order to help brands scale effortlessly. The feature includes automated translation and localization, with options to convert text into multiple languages at the click of a button. No more sending files and documents between different users, or copying and pasting between apps — you can execute your entire translation process in seconds, from the comfort of the CMS. 

Our AI tools also go far beyond translation and localization. Contentful empowers marketing teams and other nontechnical users to automate content publication and content personalization at scale, without developer intervention — and, in doing so, continue delivering new digital content experiences without compromising their brand voices. 

You can explore those features yourself: check out our AI Actions demos to get started. 

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