The La-La Land of Translation Marketplaces

On April 10, 2017, the New York Times published an article, “The Gig Economy’s False Promise“, pointing out that cheap and convenient online marketplaces flourish at the expense of the people who will never earn enough to make a living.

The promises Silicon Valley makes about the gig economy can sound appealing. Its digital technology lets workers become entrepreneurs, we are told, freed from the drudgery of 9-to-5 jobs. Students, parents and others can make extra cash in their free time while pursuing their passions, maybe starting a thriving small business.

In reality, there is no utopia at companies like Uber, Lyft, Instacart and Handy, whose workers are often manipulated into working long hours for low wages while continually chasing the next ride or task. These companies have discovered they can harness advances in software and behavioral sciences to old-fashioned worker exploitation, according to a growing body of evidence, because employees lack the basic protections of American law.

It was Tina Brown, former editor of Vanity Fair and The New Yorker, who brought the concept of gig economy to the general attention in an article published in The Daily Beast in 2009, when the effects of the financial crisis started to affect the most vulnerable categories of workers. Brown’s article opened with what at first read like a depressing statement:

No one I know has a job anymore. They’ve got gigs.

Gigs are a bunch of free-floating projects, consultancies, part-time bits and pieces people stitch together to make a living. Tina Brown used a slang term coined in the 1920s by jazz musicians and extended its meaning to the act of combining multiple skills, talents and abilities to generate a decent income.

Companies like Uber, Lyft, and Upworks may have been disrupting other sectors, but they have nothing to teach to the freelancing economy and the translation and localisation industry. Nowadays translation projects start with one buyer, who then reaches out to different vendors – sometimes located in different countries. These, in turn, split their portion of the project and subcontract it to several other smaller vendors. The smaller vendors split their assignment into even smaller chunks and hand them off to freelance translators. The role of most players within a translation/localisation project ends up being a gig. The more skills you have and the more tools you can use, the more gigs you get. Technology development has contributed significantly to this work model.

I stumbled on a translation marketplace for the first time in 1995 – Aquarius (still online today). For 60 Dutch guilders (more or less €30), you could sign up as a freelance translator and hope to be contacted by potential customers. At that time, Aquarius was doing what the various professional associations should have done, i.e. promote online the work of translators. According to the website, Aquarius has now a database of “55599 translators, 8677 interpreters, 8846 subtitlers, 2811 multilingual copywriters, 1251 localisation engineers, 1782 multilingual DTP specialists from 139 countries.

In 1999 ProZ.com was launched. Today the website boasts over 300,000 professional translators and translation companies, and calls itself “the leading source of translation jobs and translation work for freelancers.” After ProZ came TranslatorsCafé.com, Hyperlingo, and many, many others. Companies like Unbabel and Gengo also have their own marketplaces, just like SmartCAT and MateCAT.

Last year, ProZ.com threw down the technological gauntlet with the acquisition of TM-Town, a translation platform that helps translators put their translation memories and glossaries to good use, i.e. to find new clients. Translators sign up and upload their translation memories, which will be used by TM-Town’s search engine (called Nakōdo, the Japanese word for matchmaker) to match freelancers with clients in need of a translation.

The Big Question: Is a marketplace the right place for a freelance translator, a language service provider and, in general, a translation buyer?

Spotlight on the freelance translator: Suppose you sign up as a freelance translator on a translation marketplace where already thousands of others are marketing services like yours. How do you distinguish yourself from the competition? Quality? We all offer that. Rates? Certifications? Are you willing to upload your translation memories? Do you expect to find long-term projects or short-term translation gigs? How do you verify that your new-found client is a prompt payer? Joining a translation marketplace might be a good idea in the beginning (for example, to get in touch with a wide community of peers and discover some ins and outs about the translation world, get your first translation jobs if you’re lucky), but it’s not going to be the final solution to your marketing activities.

Spotlight on the language service provider: Agencies usually turn to translation marketplaces when they want to pay low rates or when they are looking for translators with language combinations that are not in their database. But, as an LSP, how do you make sure that you’re going to choose the right vendor? Are translation memories, certifications and third-party ratings going to be a sufficient guarantee? Wouldn’t you prefer to put some time and effort in building a database with translators whose skills and specialisations you have verified and rated? Can a translation marketplace be your only HR source?

Spotlight on the translation buyer:  If you need a one-off translation, a translation marketplace might offer a quick and cheap solution. If on the other hand, your company needs to invest regularly in translation, the best thing you can do is either turn to a language service provider or create your own pool of freelance translators who work in line with your company’s communication strategy.

Online translation marketplaces are a practical solution in few instances, but a stopgap in the long run: It’s more likely that you’ll be in control of your translation needs/services just like a sailor is in control of the weather.