Our Analysts' Insights

User-generated content (UGC) has garnered a lot of attention due to the challenges it poses for localization, such as an abundance of spelling errors, the extent to which its meaning depends on context, a lack of consistency, and time sensitivity. But even as enterprises and language service providers (LSPs) struggle to deal with it, another type of generated content has been quietly swelling into a looming tsunami: machine-generated content (MGC). Today, increasing quantities of content appear ...

It’s almost impossible to open one’s email or social media feed without skimming one or more messages entreating the reader to “follow the path to digital transformation” or to “recognize how artificial intelligence (AI) is changing digital transformation.” But how much attention should LSPs pay to what’s going on in this area? CSA Research recently launched an initiative to find out. In the meantime, here’s what our preliminary results show.

I have an interest in 19th-century sporting newspapers and would like to have them in digital form. Unfortunately, these newspapers used almost microscopic fonts, the type was often heavily worn, and their paper has degraded over time. Despite these problems, humans usually don’t have any trouble reading them, but optical character recognition (OCR) is another matter.

Moving content from one support knowledge base (KB) to another is hard enough in one language, let alone in two or more. In our recent interviews with 36 global firms about how they create and manage multilingual support content, KB migration elicited the most spirited discussions. Here are five pieces of advice from our research to improve the chances that your next migration initiative will go as smoothly as possible in one language or many.

Translation technology has reached an inflection point, swept up in the big trends affecting every industry: big data, cloud computing, and artificial intelligence (AI). Language platforms are being renovated or replaced as enterprise buyers and innovative language service providers seek to align their language systems with the rest of their technology stacks. Dated monolithic translation management systems (TMSes) are giving way to microservice- and cloud-based architectures, with machine learn...

Chatbots are rapidly becoming ubiquitous in marketing and support. The potential for brands to interact with customers using natural language – and perhaps a bit of personality – without needing an army of paid human agents is driving major investment from enterprises. Tech giants – from Google to Facebook and IBM and Weibo to Microsoft – have started a virtual race to dominate this field. However, what is missing in this picture so far is serious attention to multilingual needs. Amazon, App...

Speech-enabled search allows people to access information much faster than they can through typing– particularly in languages such as Chinese, Hindi, and Japanese – and especially when fingers and eyes are occupied with driving or making equipment repairs.Customer expectations are already shifting as people take for granted the ability to give voice instructions to Alexa, Cortana, Siri, and their local equivalents Why shouldn’t they be able to do the same as they place product orders through ...

Intel founder and former CEO Andy Grove wrote that, “Measurement against a standard makes you think through WHY the results were what they were.” Business-savvy organizations live by this dictum. They monitor various datapoints and develop key performance indicators (KPIs) – assessable values that show whether a company is meeting its strategic business objectives.

In addition to weighty issues related to privacy, data security, and transparency, global content is what brought Facebook CEO Mark Zuckerberg face-to-face with 44 members of the U.S. Senate this week. At the heart of the discussion was how the company plans to police harmful material while at the same time avoiding censorship.

Last year, CSA Research investigated 137 languages with measurable internet activity to identify those with the top online economic potential. We divided languages into four tiers based on the share of the “world online wallet” they commanded. This examination revealed that as internet penetration, populations, and GDP rise, the number of tongues needed to reach a given percentage of the market also increases and the mix changes. Recently, we used economic, population, and technology forecasts...