The Future of the Localization Industry

Don Shin headshot

Kajetan Malinowski

Kajetan Malinowski is senior director of Proposition Management for Lionbridge, and is responsible for Lionbridge’s product strategy and for developing an AI-enabled localization platform. Malinowski holds an MBA from UQAM /Warsaw School of Economics.

Don Shin headshot

Jaime Punishill

Jaime Punishill is chief marketing officer at Lionbridge, and is responsible for leading global marketing and proposition development efforts. He earned a bachelor of arts in history and political science from Stanford.


hat is the future of the localization industry? To understand where we’re headed, it is helpful to consider how we got here. When I started working in localization 14 years ago, things were a lot different. We worked on multi-month, behemoth projects. Success was measured by how “good” the translation was, as defined by its linguistic quality and technical compliance. Localization was totally divorced from business outcomes. It was like the old medical joke, “the operation was successful, but the patient died.”

Language service providers (LSPs) were treated like an extension of internal localization departments — a factory where the content was “processed.” Many business functions that are now critical started this way. For example, the early days of digital marketing were quite similar. Relegated to the sidelines, digital marketing teams were separate from the main marketing department. These “non-critical” functions tended to be underfunded and understaffed. They were not viewed as core or strategic to the business.

Time, of course, proved the old-line marketers wrong. Digital wasn’t a side show — it was to evolve into the prime acquisition channel for companies. Fast-forward to 2021, and we see that the pandemic has erased whatever resistance or sluggishness was left in companies towards digital channels. Digital transformation is now front and center as we’re living in a digital-first universe. The shift has forced companies to reevaluate their business practices and finally prioritize digital marketing strategies.

The rise of the multimarket digital experience

As the shutdowns that cascaded across the globe in 2020 proved, many companies were not ready for the digital-first universe. About ~10% of a brand’s digital content gets localized, and even fewer global companies provide a truly multilingual support experience across the full spectrum of their customer support channels, according to CSA Research’s “Localization Depth and Language Choice.”

The contrast between the physical and online worlds is stark. In person, you can operate in your native language and you are less aware of what is available in another physical location. Online shoppers can see exactly what’s available but are often faced with content that is not in their native language. Language remains the ultimate frontier of the frictionless customer journey.

Leaders know what others have just discovered: to be effective, localization has to stop being just about words, or a mere afterthought. It must incorporate meaning, comprehension and emotion, the key drivers that motivate consumers to act.

Innovative digital teams are more attuned to the rising significance of language, cultural adaptation, and the targeting of market-specific buying patterns — but they still struggle with an internal culture and process that focuses on the physical world first and the digital world second. Many marketing teams still undervalue internationalization, and operate inefficient content supply chains that optimize for their host country or language, and not for the content’s use in multiple markets simultaneously. Couple that with the continued focus on process and linguistic purity by most localization teams, and you realize that the go-to-market and localization teams can’t be further apart.

In 2021, even more businesses will move to a digital-first approach. This shift will bring exciting changes that have profound implications for the localization industry. As a result, the localization industry will be able to take its rightful place at the strategic table as a key component of every company’s multichannel experience. Both companies and LSPs that embrace this shift will gain a competitive edge over slower-moving competitors, ushering in a new age of digital experience and accelerating international growth.

Turning the corner: An explosion of content and the dawn of AI

While digital tactics, processes and best practices are slowly taking over, the digital world is getting infinitely more complicated. Video. Mobile. Social. User-generated content. Email. SMS. Augmented reality. Along with the explosion of channels and media, an exponential increase in velocity and volumes stresses the system. There are no more 12-month campaigns and launches. Years-long initiatives turned to months to weeks and now, mere days. The amount of content generated every year is growing exponentially. Nearly 90% of the world’s data was created in the 24 months prior to a 2018 Forbes study — no doubt the last 24 months have seen similar meteoric growth. Generating fresh, relevant content is the lifeblood of demand generation; it increasingly separates digital winners and losers. Leaders realize that to sustain a constant, ever-growing flow of content, they must change the way they create, and localize that content to meet the needs of the buyers in their target markets.

Localization teams are responding. First, there was an emphasis on transactional efficiency, connectivity and the simplicity of the localization technology stack. This has given rise to next-gen computer-assisted translation (CAT) and translation management system (TMS) tools. Today, companies increasingly expect LSPs to integrate and automate localization processes as part of the localization service.

Transactional speed and efficiency are just parts of the problem. With growing demands, greater volumes and shorter turnaround times, translation cost-cutting measures are the next tactic teams turn to. The long-awaited potential of machine translation (MT) provided a new glimmer of hope in 2017 with the introduction of neural machine translation. Neural MT’s quantum leap in performance should unlock the next wave of efficiency while increasing the quality of MT for many more languages, making it applicable to use cases that were not previously considered. Substantial advancements in the use of neural networks and artificial intelligence drove this breakthrough, and both rely on large quantities of high-quality language data–a new focus for innovative localization teams.

The 25-year journey of the localization industry has seen amazing transformations and progress. We are just starting to unlock the real value creation in this industry. The next stage of evolution will capitalize on insights and analysis about language, tone, sentiment, readability, accessibility, and buyer journey impact. In our work we see signs of transformation coming from early adopters.

Change #1: Augmented translation arrives

In the years to come, digital experiences will displace in-store experiences evermore. As a result, their current relationship will become inverted, with in-store experiences relegated to supporting digital experiences going forward. This shift started long before the pandemic, but it’s the post-COVID reality that will normalize it. Apple understood that dynamic and completely redesigned their retail experiences, turning them into digital-powered showroom experiences. That is the path that many brands will follow in the digital-first, multichannel world. Knowing when to deliver content, in which language and through which channel will be an essential part of the multimarket, competitive equation for 2021 and beyond.

MT was the first use of AI in our industry, and AI is about to drastically transform the way translators operate in the years to come. Their focus will gradually shift from translating source content to correcting and augmenting machine-generated translations. They will add relevant context and fill in language or market-specific gaps in the translated narrative. There will also be other applications of AI that further improve translator efficiency. These applications include type-ahead functions, do-not-translate blockers, inline readability highlights, the detection of biased or offensive terms, and the autocorrection of words that will ensure adherence to terminology glossaries or brand style guides. It won’t be long before natural-language content generation — powered by language prediction models like Generative Pre-trained Transformer 3 (GPT3) — is incorporated into the translation process as well.

Most industry discussion about the impact of AI focuses on MT and translators, but we believe AI’s influence will be far greater on the broader localization process. AI will unleash an explosion of content to be localized and generate a significant growth in the marketplace.

Change #2: Augmenting localization end-to-end

The notion that localization teams, and their LSP partners, will morph into global content production teams is not new — CSA Research mentioned it, for example, in June 2020’s “The Future of Language Services.” Without scalable AI, it wasn’t possible, but that future has arrived. Taking advantage of these new capabilities requires businesses to rethink how content or experiences are produced. Naturally, a focus on internationalization best practices is central to this strategy. Many localization teams still operate in organizations that haven’t optimized their people, process, and technology to the multimarket world they operate in. The digital-first universe that was thrust upon organizations in 2020 makes this deficiency even more pronounced. How can AI be harnessed beyond translation?

In agile software development, there is a notion called “shift left.” Many things done late in the development cycle can be done much earlier, adding speed and efficiency while improving quality. For example, a coder will write both her code and test cases at the same time, a process that used to be done by two people at separate points in the process. In localization workflows, the shift left has started. Take many of the quality processes created to ensure good translation, executed after the translator returns the work. What if those same quality measures could be applied to the source content before the content is translated? What if the search engine optimization (SEO) terms often applied after the fact, were instead maintained in a data repository and applied to the translation process in flight? Both of those examples are real and in limited use today, and both are enabled by the broad category of AI disciplines.

Change #3: Unleashing a torrent of “good enough” content

The most important question facing large scale retailers, technology companies, travel and hospitality brands is, “What is good enough quality?” as measured by end-user acceptance. Many localization professionals are stuck in a pedantic universe that only cares about perfect translations, despite reams of evidence that most users will accept many less-than-perfect translations just to get the 90+% of content never localized into a zone they can understand.

There are two main governors creating the content gap-cost, and the persistent belief that only perfect quality will do. Soon, innovators won’t choose which content is going to be localized. Instead, they will target 100% localization for all markets and optimize their budgets by choosing different quality and service levels based on the necessary demands of the content by use case. Not every piece of content needs white glove treatment. Well-trained and managed MT is proven to handle vast amounts of content from the bottom of the content pyramid. Adding on increasing amounts of human attention and experience takes you from the bottom of the pyramid to the top.

Together, the AI-driven content journey and an understanding of “good enough” quality needs will enable firms to quickly shift from localizing 10% of their digital content to localizing 90% of it. This will bring a frictionless path to purchase, unlock forgone revenue and improve their customer’s experience in all channels

Change #4: Marketing and localization functions will merge

We expect more and more marketing organizations to take on the localization remit from product and development teams. Why? Increasingly, marketing teams are responsible for brand, growth, customer experience, onboarding, and digital transformation. None of those things can be done successfully for a multimarket organization without mastering the multilingual, multicultural, multichannel, and multi-buyer journey differences that exist in today’s world.

Marketing teams are more customer-centric, more data-driven, and more agile than other business units because they have had to be these things to survive digital transformation. This change is already starting in some of the organizations that have been leaders in localization, and we expect many other companies to follow suit. As new content journeys emerge and reimagined definitions of quality take hold, the logic of creating one single global content and customer experience team to support the multimarket strategy of globally minded organizations will become obvious to many.

Figure 1: Volume and quality drive different quality levels and production processes. Source: Lionbridge.

The multimarket content journey for today’s multichannel experience

As marketing and localization teams come together to reimagine how they create content and experiences, they will rethink their process from end-to-end, incorporating these new AI-driven insights at each stage of the process. What is needed is a construct that connects all parts of the content cycle and is engineered to drive and support business outcomes (see Figure 2).

Figure 2: Most important stages of content life cycle.

The first two phases — content planning and content authoring — are closely related to the last phase, content performance. These three phases are centered around marketing optimization activities and wrap around the ones focused on localization. Each phase is important and constitutes an essential part of the journey:

1. Content planning. Centered around the planning of content marketing activities and the budgeting of those activities, this stage is where organizations set their content strategy and indicative budgets for creation and localization, using a matrix of buyer profiles, market dynamics, and growth objectives.

2. Content authoring. During this phase, companies craft content that aligns with their content strategy goals. They are aided by insights into where they have content gaps relative to what buyers are looking for, how to best author that content to have the greatest discoverability in search engines and tagged to best support personalization and recommendation tools. Altogether, these things maximize customer engagement and reduce friction on the paths to purchase.

3. Content ingestion. Once content is authored in the CMS or deposited in the digital asset management system, it will be auto-ingested by the localization platform of the organization or their LSP. This is more than just a workflow automation; leaders will recognize the opportunity to tag all content so that they can identify the content for domain, language, persona, readability, offensive terms and inclusive language, brand fit, and other dimensions. This sets the stage for the best way to transform the content into the target state.

4. Content conversion. In recent years, content types have multiplied, increasing process complexity. There are limits to what can be done with content in its original form, necessitating its conversion to text for further transformation and enrichment. Every content conversion poses risks of data loss or formatting breakage. This phase ensures content fidelity during the extraction process.

5. Content transformation. In the old localization model, this is where most of the effort, and hopefully value, was expended and created. But as you can see, the new content journey uses preprocessing and content analysis to make this step purely about the translation or transcreation of the content into multiple languages and its adaptation to different locales. Content can be assessed and targeted for different quality levels and process flows can be matched by need. Content will be matched with the best-fit linguists and other transformation agents. And with improved MT, better integration of MT and productivity enhancements such as type ahead, the efficiency of linguists will improve as well.

6. Content enhancement. More video, audio, and interactive modules are being created than ever before, and the content enhancement stage reflects the rapid increase in non-word work. This includes things like formatting and layout changes to adapt content to local requirements and specificities. Of course, this stage will encompass additional quality — and other linguistic analysis steps — to ensure it’s on brand, on point, at quality, on target and fit for purpose. Because so much analysis has been shifted to the authoring stage, this new linguistic quality stage will be more automated, with exceptions made only for additional human review.

7. Content delivery. Once the content has passed all the gates at the last stage, it will be auto routed back to the appropriate client system. At this stage, content gets published on the target medium directly via the CMS or digital asset management system.

8. Content performance. This is one of the most important steps. It’s at this stage that companies assess the performance of their content by measuring key performance indicators, such as conversion rates, visits and engagement. The key enabler to this was the addition of tagging early in the process. Content performance closes the whole cycle and feeds into the first step of the cycle, content planning, while providing valuable information. Importantly, tracking and assessing whether content should have been localized at all will reshape how multimarket content strategy is conceived and executed.

A fully implemented content journey approach will deliver valuable insights to brands that are seeking to establish engagement and a lasting relationship with their consumers. By working in tandem, marketing and localization teams can harness the power of AI-driven insights to make informed choices and answer key questions such as:

  • Which content should be localized?
  • How can a piece of content be improved to make it more localizable and impactful?
  • Which content is easier to read for which audience?
  • What content will have the most impact?
  • How can one assure that content is on brand, in voice, isn’t offensive, and is appropriate for the market in question?

AI content intelligence helps combine SEO, language and content research into one seamless process that empowers demand gen and engagement teams to craft content that is insightful, that resonates with their readers and that translates well. Pre-analysis will lead to better-informed decisions about whether the content should be localized, de-biased, edited or rewritten for a market to maximize impact for those buyers and their unique path to purchase.

Whether digital or analog, content has always been essential to brand, customer engagement, persuasion, and conversion. An AI-powered content workflow will amplify content. Closing the yawning gap between the quantity of source and target market content, and the connection of localization work to measurable outcomes, will elevate localization to the strategic table. AI will enable localization teams to attack both of those issues in concert with their partners in marketing and customer experience.

There has never been a more exciting time in the localization business. No longer an afterthought, today, localization is front and center.


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