Depending on who you are, whether a localization department manager on the buyer side or a language services provider (LSP) trying to Jedi-mind-trick your client into spending money on localization for Korean, the arguments used will be different. Nevermind the desired outcome is the same for both categories – spend more on localization in order to reach more consumers and grow your brand or product.
Before venturing into any discussion about how to prove the ROI of localization, let’s talk about metrics – it’s knowing what your company’s (or client’s, if you’re an LSP) key performance metrics are, which helps you build a case around proving how localization affects them.
Here are a few examples of metrics companies track in order to prove localization ROI:
Example of how the insertion of Korean localization one year after launch of other markets propelled sales in Korea for the game developer Charlie Oscar. Source: Sergei Klimov, Gamasutra
Learn to track the data that matters and the magic formula will come to you naturally. Even better, when you’re facing a situation where you don’t have any historical data on localization you can draw conclusions from – see how others have been doing it. While their product and services are specific, you can at least get an approximation of localization ROI.
Events dedicated to localization, such as the 40th edition of Localization World held in Estoril, are a good way to take the pulse of our industry. While most of the discussions inevitably center around the usual suspects - machine translation or globalization, to name just a couple - every once in a full moon, a hidden, wholly unexpected gem makes an appearance on center stage.
In this episode of Globally Speaking, Joel Sahleen, a Globalization Architect at Domo, talks about driving localization for a major BI platform and how the right data can prove ROI. Learn how localization can be similar to the "chicken and egg" scenario and how a "wall of shame" can help resolve localization issues. […]
As of November 2022, everybody in the language industry is talking about ChatGPT. It is an undeniable trend firmly occupying the minds of many. New implementation scenarios and use cases for ChatGPT emerge daily, and GPT-4 has just been released. But will it stay as hyped in the next five years, or will it become as normal as Machine Translation (MT) for us?
The present report is the culmination of over 65 interviews with different companies as well as a separate survey Nimdzi conducted among localization and translation managers. It is is aimed at buyers of language services who are interested in benchmarking their own efforts or in learning how other companies tackle similar challenges or who are simply curious about what others in their position are doing.