Automation is key to operational and economic efficiency. But when machine translation does not pick up on cultural subtleties, contextual references, and colloquialisms expressed in comments and reviews, we have to ask if it really serves its purpose. Employing a solution that uses translations in its algorithm gives inaccurate results precisely for this reason - it cannot discover the nuances of the language it’s translating. This article takes a look at the importance of a multilingual sentiment analysis solution that analyses the Voice of the Customer (VoC) in the native language, without having to resort to translations.

2. Multilingual Sentiment
Analysis For Customer
Insights

3. Table of Content
● Why we need multilingual sentiment analysis
● Language And The Challenge Of Translation
● How does Repustate perform Sentiment Analysis in 23
Languages?
● What is Voice of the Customer?

4. Overview
Automation is key to operational and economic efficiency. But when
machine translation does not pick up on cultural subtleties,
contextual references, and colloquialisms expressed in comments
and reviews, we have to ask if it really serves its purpose. Employing
a solution that uses translations in its algorithm gives inaccurate
results precisely for this reason - it cannot discover the nuances of
the language it’s translating. This article takes a look at the
importance of a multilingual sentiment analysis solution that
analyses the Voice of the Customer (VoC) in the native language,
without having to resort to translations.

5. Why we need multilingual sentiment
analysis
English is the global language of business, but it is not the native language of
a majority of the world’s customers. In fact, only 13% of the world speaks
English. What about the other 87% of consumers? Businesses value the
feedback of all their customers so that they can cater to all of them
regardless of their geography and language. After all, the main goal of
businesses is to acquire new customers, and keep the ones they already
have. Companies thus need to understand the feelings and opinions of their
customers, even if they express them in their native language. Although
great in theory, this is difficult for most marketers since the manual analysis
of each comment and review is not only time-consuming but also a very
expensive task in the long run. It is not a sustainable model.

6. Language And The Challenge Of Translation
Translation is the process of transferring words or text from one
language into another. Sounds simple right? Wrong. Due to the
complexities of language in general, and the specific differences
between various languages, translation is rarely a word-for-word
transfer from say English to Italian, or vice versa. Translations must deal
with contrasts between basic linguistic building blocks such as
grammar, syntax, semantics, lexicons, morphology, and even tonality in
the case of languages like Mandarin, Thai and Punjabi. Add in all the
various literary devices that people use such as idioms, sarcasm and
slang, and it’s easy to see that trying to accurately capture the intended
meaning of a text through translation can be a daunting task.

7. How does Repustate perform Sentiment
Analysis in 23 Languages?

9. What is Voice of the Customer?
Voice of the customer, or VoC is the practice of analyzing customer
feedback to improve your product, solution, or service. VoC is typically
gauged by utilizing customer survey tools and feedback systems. Most
companies understand the importance of customer feedback analysis and
how it can supercharge your customer experience efforts, but a lot of
organizations are relying on archaic methods to extract the data they need
to better understand what their customers are trying to say. Marketing
departments, PR agencies, and even some automated social media listening
tools, often use automated, machine translators like Google and Amazon to
change foreign language text into English to conduct sentiment analysis on
the text. One major disadvantage of machine translation is its inability to
pick up on cultural nuances, contextual content clues, and local slang. This
results in content that can feel mechanical, stilted and full of errors

10. Thank you!
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