"Man's inability to communicate is a result of his failure to listen effectively." - Carl Rogers
What is Machine Translation (MT)?
Machine translation eliminates the need for a human translator to translate large volumes of words. For instance, when we receive a text in German “Aller Anfang ist schwer”, our first step is to use a Bing/Google translator app to get a comprehensible answer. This can be a time consuming endeavor that can be made significantly quicker (and more accurately) thanks to machine translation.
Does Machine Translation Help?
The applications for Machine translation are innumerable:
- Customer / Employee feedback: Quickly translate feedback across geographical locations. This improves understanding within customer service/HR teams and assists development of high quality products, improved customer service, thereby converting to customer loyalty.
- Enhanced communication between and within organizatwons engaging in different spoken languages.
- Content Localization: User guides, manuals, warranties, Websites, etc. (e.g. eBay)
- Security: Government or Organizations can heighten security by translating communication that might be a threat.
Some companies currently using MT: Adobe, eBay, Facebook, Etsy, etc.
What is Text Analytics?
The Twitter platform best exemplifies Text Analytics, where they can analyze how certain keywords are being used by users over certain time or even in real time.
A screenshot of Trends Map using Twitter data
How Does Text Analytics (TA) Help?
Like Machine Translations, large organizations significantly benefit from Text Analytics. It works in conjunction with external social media or internal unstructured data, thereby providing opportunities to act in real time, such as generating buzz about an upcoming product launch.
In addition, all the engagements are measurable and provide enormous insights. The combination of Text, Sentiments, Location, etc. can provide extremely valuable insights into eco-systems comprising of 100s of products, 1000s of employees, millions of documents/correspondence and many millions of customers.
How Can the Power of Machine Translation & Text Analytics Be Combined to Create Opportunities?
Here are some scenarios:
- When organizations receive large volumes of customer feedback in English, German and Spanish:
- "Its difficult to use this product"
- "Ich kämpfe um dieses Produkt zu verwenden"
- "Lucho utilizar este producto"
- When organizations have a bulk of contracts with global customers and vendors:
- "los derechos exclusivos a reproducir"
- "Strafe als Entschädigung bei Zahlungsverzug"
- For enabling organizations to listen to the voice of the employees across the globe to incorporate their suggestions for improvements
- "Änderung Griff-Design"
- "El cambio de cantidad de ingredientes mejorará el sabor"
With the combined power of Translation and Text Analytics, organizations can generate value from insight generated through customer’s feedback and employee engagement at a global level. This data can help drive the next level of innovation or promote incremental improvements to products or services.
What Do Your Next Steps Look Like?
- Test run some of the Translators APIs/ Widgets. Start using Translator APIs from various providers. These can be used in the background during data storage or adding a widget. This allows users to decide when to translate.
- There are ways to convert speech to text and subsequently use the resultant information in analytics. This is particularly helpful while collecting automated surveys.
- Organizations use real-time translation to support customers worldwide from a single location, helping outsourced support, and saving cost.
- Identify and shortlist vendors who can provide both Text Analytics and Machine Translation.
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