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Twitter Migrates into Multilingual Markets
Posted by Nataly Kelly on October 13, 2009  in the following blogs: Translation and Localization, Web Globalization, Business Globalization, Best Practices
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Twitter announced last week that it would be making its site available in French, Italian, German, and Spanish (collectively known in the language services industry as "FIGS"). As countries in the northern hemisphere head into winter, is the blue bird migrating to other markets in search of a warm reception?

From a multilingual marketing perspective, Twitter currently pales in comparison to its social networking peers. Up until now, the Twitter utility has only been available to individuals who speak English and Japanese. In spite of its limited language appeal, Twitter managed to reach an impressive number of users throughout the world. In fact, as we reported before, many users took it upon themselves to translate their tweets into other languages, through Google's machine translation, quick turn-around human translation, and other means.

Adding more languages is an obvious and important step for Twitter to increase its global reach. However, is Twitter doing the right thing by expanding its multilingual presence with these particular languages? Website globalization practitioners often ask us which countries and languages they should target to maximize return on their translation spend. We recently released updated figures for total available audience (TAA) and online gross domestic product (e-GDP) for 30 top countries online.

We also recently divulged the 30 most important languages on the web, as ranked by their share of what we call the "world online wallet," or WOW factor. According to our ranking, Twitter has indeed chosen the best languages to maximize its return on investment (ROI) for translation efforts. After finishing with FIGS, Twitter will need to add Dutch, Simplified Chinese, Portuguese, and Korean into the mix to complete the Top 10 languages that will give them the most bang for their buck.

Like many social networking sites before it, Twitter has decided to go down the path of crowdsourced/collaborative/community translation (collectively known as "CT3") in order to get its site up and running in other languages as quickly as possible, in spite of the fact that it employs its own (albeit small) in-house translation team. However, in an interesting move, Twitter did not send out a broadcast message to try and get all of its users to participate in its translation effort. Instead, volunteer translators must first send a message to express their interest in participating.

By opting for the "you'll call us, we won't call you" route, Twitter accomplishes two things. First, it retains greater control over the translators involved in this CT3 initiative. Second, it minimizes potential backlash from the freelance translator community, which voiced a visible protest against LinkedIn earlier this year when the company sent out a message to try and determine how much interest users would have in a potential CT3 effort. We predicted in our December 2007 report, "Collaborative Translation," that companies should anticipate this type of push-back, and it looks like Twitter's actions will be helpful on this front.

What's next for social networking and CT3? We have both our binoculars and our microscopes focused on this trend. Throughout 2007 and 2008, we held multiple colloquia on this topic. We also documented the best practices for CT3 used by companies like Facebook, Microsoft, Plaxo, and Sun in our December 2008 report, "Translation of, for, and by the People." Since that time, we've observed several companies standing on the shoulders of these giants. We've also watched other businesses make unfortunate mistakes. In which camp will Twitter ultimately fall? It remains to be seen, but if its recent language choices and initial outreach strategies are any indication, we believe that the announcement about its planned migration into new languages and markets ultimately bodes well for the survival of this particular species.


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Keywords: Crowdsourced translation, Ethnic / domestic multicultural markets, Global branding, High-demand and low-demand languages, Language and market selection, Localization, Translation

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