Leveraging AI and Localization When Creating Marketing Materials for the Life Sciences Industry
Artificial intelligence has infiltrated our personal and professional lives at scale; from our smartphones and virtual home assistants to our computers, vehicles, and televisions. It’s common to send voice commands to our Alexa, Siri, or Google Assistant without thinking about it. These machines use what is known as Natural Language Processing (NLP) to understand what we ask and complete that task.
NLP is the driving force behind machine translation; a commonly used tool within the translation industry to increase productivity and reduce costs. Recent advancements in both Natural Language Processing and Artificial Intelligence have improved the quality of machine translations, which has been beneficial for brands creating marketing material when entering new markets.
However, marketing content isn’t a one-size-fits-all solution. That’s because marketing requires personalization to resonate with its target audience while convincing them to convert. This can pose a huge challenge when brands span their marketing efforts across multiple cultures, regions, and languages.
After all, how can you create personalized content that will be effective across multiple locales, when everyone speaks different languages and dialects?
So while helpful in some aspects, we don’t recommend relying only on machine translation as a method when developing life science translations. Instead, you’ll need to incorporate experienced linguists for the most accurate and detailed content.
Understanding the Different Subsets of Artificial Intelligence in Language Learning
It’s important to understand the different elements of artificial intelligence before incorporating them into your localization strategy. The terms Natural Language Processing, Machine Learning, and Artificial Intelligence are sometimes used interchangeably, but all have different definitions.
Artificial Intelligence is an umbrella term to describe the development of computer systems to perform tasks that have previously required humans to complete. Natural Language Processing, Machine Translation, and Machine Learning are subsets of Artificial Intelligence.
Natural Language Processing
An application that gives machines the ability to read and interpret human language. NLP allows computers to comprehend and make sense of written and spoken text and perform speech recognition, sentiment analysis, and text summarization. Simply put, NLP uses Artificial Intelligence to translate between a computer and human language.
A system that gives machines the ability to learn and improve without having to be programmed directly by a human. Machine learning works to improve Natural Language Processing as it continuously improves more accurate results.
Computer systems that use Natural Language Processing and Machine Learning to produce translations without human assistance.
Machine Translation and Your Life Science Localization Strategy
Machine translation and localization are two powerful tools that, when leveraged properly, can create high-quality translations. That’s because these two processes are on the opposite side of the spectrum from each other- machine translation is powered by data, and localization utilizes humans to address cultural nuances that a machine cannot possibly understand.
Combine this with the fact that marketing content requires a specific type of messaging, and it’s easy to see that there’s no one perfect solution for merging localization and machine translation together. To utilize both effectively, there’s a need for a language service provider to come and leverage machine translation with your specific localization needs.
That’s where Language Intelligence comes in.
While the need of every project differs based on its overall goals, there are specific details in every project that we use to ensure high-quality, accurate translations.
Every time you work with us, we will keep a file of all translated words and phrases so we can use them in subsequent projects. This means when you have projects that use terms that have already been translated, they won’t need to be translated again and you’ll benefit from cost savings and a faster turnaround time.
Before you start your project, we’ll create a glossary of brand-specific terms and commonly used phrases for the linguist to look over. They will translate this glossary, and use this glossary in any other future projects, ensuring consistency across all your life science marketing materials.
Two-Step Human Translation and Edit
Every linguist we use at Language Intelligence has explicit experience translating and localizing marketing materials for the life sciences industry. They are familiar with the intricacies that come with these highly-regulated, technical content types and can translate and localize without compromising the meaning of the content. Additionally, each linguist is an in-country, native speaker of the target language, which provides up-to-date linguistic accuracy.
After the content goes through your translation memory, it will follow a two-step translation and localization process. One linguist will translate and localize the material with the parameters set in your glossary, and another linguist will edit the content. Having more than one linguist work on your material ensures high quality and accuracy.
Leveraging Technology and Localization From Start to Finish
Optimal translations require a mix of both machine-based technology and human-focused localization. Our team at Language Intelligence can make this happen for you - our expertise with machine translation combined with our cultural understanding and analysis will result in the highest-quality translatable content. We make sure to combine these elements from the start of our localization process, so we can provide you with a wide range of both human and machine solutions to meet your needs.
Interested in chatting further about merging artificial intelligence and localization to reach your life science marketing goals? Contact us today and we’ll get the conversation started.