M&A Wave Reaches Platforms as ProZ.com Buys TM-Town

Deal fever broke out in quarters not usually associated with big business. Translation community and translator-client matching portal ProZ.com acquired upstart and competitor TM-Town for an undisclosed amount.

Translators checking job postings online on April 13, 2016 must have been stopped in their tracks by the announcement that appeared on both portals. “ProZ.com to Acquire TM-Town.com” the ProZ.com website read; while TM-Town blog announced “TM-Town has joined the ProZ.com family.” And because the latter was a blog post, reactions were immediate.

One user feedback said the acquisition was ProZ.com’s way of eliminating the competition and that “TM-Town, even with its paid membership, looked like a sensible alternative” to ProZ.com adding, “now, I’m not so sure about that.”

ProZ.com and TM-Town are competitors in the translator-job-matching space, where freelancers and translation buyers get mutual access to each other. A glance at their UIs―or even the way they announced the acquisition―gives one an idea of how different the two portals are; and why any perceived merger may cause translators and clients pause if they had gotten used to either ProZ.com or TM-Town’s distinct UI.

“The criticism about the UI being outdated is valid. We do intend to update certain aspects of the interface”ProZ.com President Henry Dotterer

Slator reached out to ProZ.com President Henry Dotterer for more details on the deal.

The TM-Town acquisition brings ProZ.com’s total headcount to 21; and, per Dotterer, no office will close or transfer as a result. He said that the primary motivator for the acquisition was TM-Town’s “proprietary approach to matching” freelance translators with clients.

TM-Town’s NLP won’t replace ProZ’s manual profile review

Dotterer explained, “The TM-Town approach is essentially to use natural language processing to match translation providers and translation buyers on the basis of actual texts. The ProZ.com approach relies heavily on the review of profiles. Both approaches will continue to be needed and offered. A blended approach can also be imagined.”

As for concerns about TM-Town membership fees being imposed on free users or going up for existing paid subscribers, Dotterer said “membership options” on TM-Town will remain the same and they will reach out to customers first before they change anything.

Walmart of translator matching

TM-Town is your typical, modern, pastel-hued website. ProZ.com is not. One reaction to the acquisition described it as having an “ancient website design.” Dotterer defended the site, saying they have always tried to be the low-cost, no-frills, Walmart of translation job matching.

The same poster said he liked ProZ.com’s functionality, such as the feedback and fora; although he went on to say, “the design looks like it probably did when the site was first launched back in the 90s.”

Dotterer agreed that the Walmart approach “has its limits, and the criticism about the UI being outdated is valid. We do intend to update certain aspects of the interface to conform more closely with modern expectations.”

Without being specific as to what exactly he is looking for, Dotterer also said they are still on the lookout for more acquisitions.

He also remarked how the language services industry is in the middle of a productivity boom as disintermediation platforms come of age and become better at translator matching.

He thinks buyers “have not really considered, how much faster and better translators can work when they are assigned to jobs that require little or no research because what they need to know is already in their brains, translation memories, and even their own personally trained MT engines.”

Of course, taking out the middlemen (read: project manager, language service provider) has been the elusive goal of translation automation. So far, all attempts to do it at scale have yet to succeed.