Market Research giants have claimed that the market intelligence space as we have known it for decades is changing, giving rise to increasing industry specialisation. There are more independent voices than ever before that command respect in their industries owing to their comprehensive and insightful research. The IT industry has R “Ray” Wang, for example. And like any other profitable and organised industry, the language market has its very own Konstantin Dranch who specialises in localisation market research. Tune in to keep up with the changing trends.
How is research important to buyers and sellers of language services?
Unlike let’s say the IT industry, the translation market is very fragmented. There are hundreds of translation companies that provide services at different service levels and prices. So if you are buyer of language services, industry research helps you create a localisation strategy and identify the major players and key practices of the industry. It also helps you source better by helping you understand what questions to ask your translation vendor.
The kind of research that I do is also useful to sellers of language services. It primarily helps companies benchmark against competition and keep up with the best practices. It also helps companies take critical decisions about what kind of a business to build, whom to sell to, how to package, etc. Industry data can also help in data-driven decision making when stakeholders of a company cannot find common ground. For example, if a company wants to expand but its directors are torn between let’s say transcreation and subtitling, they can use industry data to come to a definitive conclusion. Of course, there are entrepreneurs who like to go with their gut feeling, but for those who don’t, industry data is crucial.
In one of your online articles, you have spoken passionately about Big Data and the increasing demand for Indian language translations. Could you tell us more about it?
That article was based on the volume of translation done at Memsource, which is a provider of cloud-based translation technology. Cloud platforms are taking over individual CAT tool installations used by companies and since all the translations get stored on the cloud, a lot of data is being aggregated which can be exploited for AI. So from such data, we saw that Hindi and Marathi have grown in demand. But in terms of Big Data, the relative volume of Indian translations is still low. But if we undertake another research like we did for the Memsource article, we would surely see that Indian translations have gone up even more since the last time we researched.
We know that eCommerce companies look to break from their traditional markets and enter regional markets in India. How do they stand to benefit from Big Data?
Ecommerce companies probably don’t know about this kind of research vis-à-vis the translation industry. They use other economic indicators such as purchasing power, PCI, number of internet users, etc. They may not even have access to Big Data research. But if this research is presented to them, it will serve as another definitive signal that other eCommerce companies are using language solutions and if they want to be in this marketplace early and establish a presence before it becomes too competitive, the time is now.
Since we are on the topic of eCommerce, what is the importance of user generated content?
It’s very straightforward: if you have an online shop, user content helps you sell. But user generated content is actually a challenge for translation companies. Since it is generated spontaneously, it cannot be translated by human translators. The role of translation companies is to set up a machine translation engine for their client that translates user generated content more accurately. For example, eBay has an internal machine translation department that translates their entire product catalogue.
As an independent researcher, how do you see the market changing in terms of technology adoption?
I would say there a few main trends. One of the most important trends is the integration of the company’s translation tools with buyer systems. This is done using APIs and is particularly important when the source content is dynamic. Take an eCommerce website, for instance. It may be updated 20 times a day. Integration makes it easier to translate and manage this type of content. As for buyers, they are adopting good translation management systems of their own and many have started using cloud technologies. Lastly, translation is becoming more and more embedded in other systems. Normal platforms for content and technical writing are becoming more supportive of multilingual translations.
The Common Sense Advisory’s “Can’t Read, Won’t Buy” survey was very interesting. Are there any similar patterns emerging from your research?
Voice Video Localisation is a big change. When Netflix and their competitors want to expand in a region or a country, they get everything localised. The one thing people will never buy unless it’s localised is TV content, right? In Russia, for example, people won’t watch a movie unless it’s fully dubbed. So Voice Video Localisation is a great example of how localisation helps companies. It’s more like “Can’t understand the movie, won’t watch it.”