The Intelligent Translation Era – Breathing Life Back into Brands

Jun 17, 2019


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Article ImageMarketers face an uphill battle with so many tools in the marketing stack—especially when it feels like everything needs to be prioritized equally. For global companies, it’s even more challenging considering all the content that needs to be translated accurately for each market. And when it comes to content translation, it’s simply not as easy as plugging your words into Google translate and hoping for the best.

How many times have we heard brands apologizing for their offensive campaigns by saying they “missed the mark?” Their campaigns weren’t intended to offend, but the intention is not what matters—it’s perception. In 2019, missing the mark due to poor content translation is not an option. CNN recently published a story about how a health department-run campaign encouraging measles vaccinations in the Orthodox Jewish community in New York went wrong because the Yiddish translation was so sloppy. This is just one example of a valiant effort and significant investment wasted—thwarted by something preventable.

For brands trying to reach an ever-growing multicultural audience, let alone global brands, the merging of machine learning and human optimization can help marketers tackle this huge responsibility.

Machine-first, Human-optimized

The companies that survive and thrive today have prioritized adaptability and transformation to meet changing customer needs. Content drives the customer journey, and as a result, the amount of content the world produces and consumes will continue increasing. Failing to deliver content in all customer languages results in a huge missed opportunity to generate more revenue. However, with neural machine translation consistently delivering better and better results, a model where machines take the first stab and humans optimize the content can deliver the required scalability.

In the same way that computers have not replaced office workers, machines won’t replace linguists. Rather than using humans’ time and effort for a soup-to-nuts translation process, shifting to a machine-first human-optimized model changes the value of what linguists actually produce. In other words, linguists get to be measured on the quality (creativity, resonance, impact, etc.) rather than the quantity of the words they can churn out—they become cultural linguists.

When trying to reach a multicultural 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 organizations to focus on other things.

Keeping Up with an Omnimarket World

It is not just the big brands that are going global these days—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, but with great power comes great responsibility.

As we become more multicultural and multilingual, the implications of translation can ultimately have an impact on the way your brand is perceived. Nobody is going to applaud a brand just for making an effort to translate its content, the context has to be right, too.

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.

The solution is leveraging the machine-first human-optimized model to prioritize investments in un-established markets and expand multi-channel translation footprint in established markets—so becoming not just global but omnimarket (accessible across every target market). This is a more efficient way to be everywhere at once rather than localizing top-tier content only for established markets, as many global businesses do today.

A New Era for Translation

Having a huge arsenal of translated content is great, but without taking context into consideration before pushing it out to the public, the content could ultimately be useless. At best, it would be disregarded. At worst, it could cause a brand to suffer severe reputation damage.

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

There are two ways this future could unfold. First, the localization departments of today could become obsolete because all departments will fold into the content supply chain. The problem in this scenario is that everyone would still be working in silos, which makes it difficult to truly optimize the customer journey.

The second possibility, which is far more likely, is that the localization department will reinvent itself as the main driver of an omnimarket strategy. They will exist to analyze the data that comes from machines and use that data to align disparate departments to capture the attention of every consumer in every market. Essentially, the localizers of today will become the omnimarketers of tomorrow.

Time will tell which model will ultimately win out in the end. But one thing is certain: the intelligent translation era is closer than you think.


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