 The global language services market size: ca bln US$  Market continues to grow: 6.23% (2014), 5.13% (2013), 12.17% (2012), 7.41% (2011)  Expected to reach 47 bln US$ by Source: CSA, 2014

 High fragmentation: most companies have below 10 employees  Only 500 companies have 50+ employees  100 top LSPs represent 12.8% of the market (2013)  Over LSPs* 3 Source: CSA, 2013/2014 LSP = Language Service Provider

4 Source: CSA 2014  Eastern Europe’s share of the market: % (ca. 0.9 bln US$) - to reach ca bln US$ by 2018  Top 20 LSPs cover 24% of the market  Only CZ, RU, PL private companies in Top 20  Moravia – leader by far

5 Source: CSA, 2013/14  Eastern Europe  Global market  Shares of top 5 above: 9.3%, 6.2%, 6.0%, 5.7%, 5.6%

6  Investors believe in companies that bring new approach to servicing translation buyers (Smartling, Gengo, Safaba) or bring good growth, operational efficiency  February 2015: Clarion Capital Partners, LLC (US private equity firm) has acquired a majority interest in Moravia  Moravia: - founded in 1990, Brno, Czech Republic mln US$ turnover in 2014, 850+ employees - the first localization company to achieve 100 mln US$ organically (private company)

7  October 2014: Argos acquires SH3 Inc. and rebrands to Argos Multilingual - Argos Translations (Kraków, Poland), founded Focus on translations for IT/software and life sciences - SH3 Inc. (Kansas City, USA), founded Translation supplier for the US industrial manufacturing sector - Before they cooperated for 15 years - About 100 staff all together  It seems to be the first acquisition of this type

8  April 2014: XTRF, developer of XTRF translation management system, attracted the first round of funding: - XTRF is based in Kraków, Poland - XTRF has grown 100% annually for the last few years - Experior Venture Fund provided ca. 1 mln euro for product and company development - Experior got a minority stake in the company

9  Wave of online translation companies (OTC) Like Gengo, OneHourTranslation, Tolingo, some based on close to crowdsourcing model  Client friendly workflow Go online -> get a quote instantly (cost calculators) -> pay in advance by credit card -> get your translation quickly (track the progress online)  Online localization platforms Like Transifex (a cloud-based localization platform) or Lokalise (apps, games or websites) – platforms (subscriptions) + can supply translation teams  OTCs start with focus on shorter, simpler jobs But then try to add premium services and reach also big clients  Will OTCs replace "traditional" LSPs? Will they cause the “Uber” effect?

10  Gengo introduced "performance transparency". They publish online raw data on customer satisfaction and first response time  MemSource: integration with "Gengo human translation engine" Source: Gengo website, 15 March 2015

11  Global resource competition Translation services can be done using linguists from anywhere in the world. It results in more competition and lower rates.  Levels of quality, "good enough" More clients started to accept several levels of quality – depending on type of content, markets needs and intended purpose.  Shortage of resources, scalability problems In certain areas of the market LSPs can not find enough resources to handle clients’ needs.  The technology impact on revenue: MT and platforms - MT is widely available. Volume of post-editing MT jobs increases. Often PEMT cannibalizes revenue from human translations. - The next wave of easier-to-implement software for translation management (such as Easyling, Memsource, XTM, Smartling, and Transifex). They help to decrease (or even eliminate) staff.

Questions? Grzegorz Wójcik, MAGIT