Meister and Lokalise: how to double customer satisfaction by localizing your apps
"Looked into at least 6 translation platforms, Lokalise is the best"
"Looked into at least 6 translation platforms, Lokalise is the best"
Meister is a SaaS company located in Munich, Vienna, and Seattle. With more than 50 employees, they've been developing agile and smart apps for more than 10 years. Their most popular products are MindMeister and MeisterTask, which allow users to visualize and manage their ideas in a collaborative environment.
MindMeister was launched in 2007 and is the world-leading mind mapping solution. Used by close to 14 million people globally with 1 billion+ ideas generated worldwide.
MeisterTask is an intuitive and collaborative task management solution. Users can turn ideas generated in MindMeister into action, and bring team projects to fruition.
Managing translations for 10 languages across 2 web and 4 mobile apps can be challenging without a translation platform. Initially, Meister had their own translation system developed internally. However, when they started developing their second web app called MeisterTask, they had decided to implement one of Lokalise's competitors.
Adding and tagging screenshots, managing glossaries, collaborating with translators became hard on that platform. In addition, dealing with the errors they had in their system made Meister consider other translation platforms.
One of Meister's iOS developers had worked on another project with Lokalise, and he recommended it to them. Once Meister team gave Lokalise a try, they realized that this was the perfect translation management platform they had been looking for.
Uploading and tagging screenshots is one of the features that Meister enjoy the most. It allows them to easily provide context for the translators and improve the quality of their translations. Built-in project chat, customizable notifications, a wide variety of integrations — they all contribute to providing better quality translations.
Features that Meister enjoys the most: