By Peggy Chen, CMO at SDL 

As marketers, we work in the economy of language and communication. It’s a powerful tool when it’s done right. However, as businesses continue to operate on a global scale, with not just different languages to speak to but a myriad of cultural nuances, this can be easily undermined with just a simple incorrect or misplaced word or phrase.  

Let’s take Heinz as an example: an advanced, successful global brand, that recently launched a new condiment. Whilst a welcome addition to the brand’s sauce selection for some consumers, others noticed the mishap for the wording for a dialect spoken by the Cree, a First Nations group in Canada and North America. Luckily Cree have a good sense of humour, however, given the dominance of Heinz around the world, it’s a mistake they can’t afford to make lightly.  

So, what do global brands do when trying to reach an ever-growing audience with lots of content that needs to be translated accurately for each market without causing a brand mishap?

The merging of machine learning and human optimisation can help marketers tackle this huge responsibility. 

The human touch to machine learning  

Content drives the customer journey. As a result, the amount of content the world produces and consumes will only continue to increase. Failing to deliver content in all customer languages results in a huge missed opportunity to generate more revenue. However, meeting the demand for translated content using only humans is physically impossible. Neural machine translation, a model where machines take a first stab and humans optimise the content, consistently delivers and can meet the scalability companies need. 

In the same way that computers have not replaced office workers, machines won’t replace linguists. Rather than using people’s time and effort for the entire translation process, shifting to a machine-first human optimised model changes the value of what linguists actually produce. It’s not words that become the measure of output, but the creativity, resonance and impact that a linguist can impart, much in the same way that top creative agencies are viewed.   

When trying to reach a global audience, the words themselves are cheaper than the context. These linguists who can deliver on the creativity and context are the partners that make translation truly successful and allow organisations to focus on other things.   

Taking on the omnimarket world  

It is not just the big brands that are going global – smaller, more agile e-commerce businesses are reaching a larger audience than ever through social media and creative online content campaigns. The internet and technology are powerful tools for business decision makers at companies of all sizes. However, with great power comes great responsibility.    

The implications of translation can ultimately have an impact on the way your brand is perceived. A brand can’t just translate its content word for word, the context has to be accurately delivered as well. Deciding which content to translate also has an impact on the business.  

Translation can be a bit of a “chicken and egg” scenario: does a company wait for sales to take off in a particular country or cultural niche before investing in contextual translations? Or invest in content translations first to build demand for sales? The amount of time it can take to make a decision gives local competitors an edge.    

By leveraging the machine-first human-optimised model, companies can then prioritise investments in smaller markets and expand multi-channel translation in established markets. This is a more efficient way to be everywhere at once rather than localising top tier content only for established markets, as many global businesses do today.   

A new era for translation   

Most industries have experienced disruption as a result of automation and advances in technology. What makes the translation industry see change more significant is the impact that it will have on global business and consumers as a whole.

We’re moving into an era where the question is not, “how can we translate this large volume of content?” But rather, “What can we do now that language is no longer a barrier to reaching customers?”  

This could manifest in two ways. First, that the localisation departments of today become obsolete because all departments will fold into the content supply chain. However, the problem here is it will force teams into silos, which makes it difficult to truly optimise the customer journey.  

The second more likely option is that the localisation department will reinvent itself as the main driver of an omnimarket strategy. They will analyse the data that comes from machines to align each department to capture the attention of every consumer in every market.  

The efficiency by which content can be created, translated and delivered changes the very definition of globalisation today – and this is a key indicator that the intelligent translation era is closer than you think.