Verified Authentic Review Based on 10 months of experience
Rating: 9 out of 10
IncentivizedUse Cases and Deployment Scope
How: We have several Influencer/Content Creator as our client and we use Google Cloud Natural Language API's text analysis feature to understand the sentiments of audience of the our client (Influencer/Content Creator).
We analyse thousands of comments of audiences/followers and provide the analysed data to influencers.
Problem Solve: Analysing thousants of comment manually is not possible and chances of human error is too high, Google Cloud Natural Language API is solving this issue so efficently.
Scope: We are planning to acrquire some other clients from different domain who needs such kind of result from raw data, like e-commerce mechant.
We analyse thousands of comments of audiences/followers and provide the analysed data to influencers.
Problem Solve: Analysing thousants of comment manually is not possible and chances of human error is too high, Google Cloud Natural Language API is solving this issue so efficently.
Scope: We are planning to acrquire some other clients from different domain who needs such kind of result from raw data, like e-commerce mechant.
Pros
- It's accuracy to translate source text into desired language.
- It provides final data without losing emotions of source/raw data
- It's efficiency is much better than Microsoft translator.
Cons
- Slight room of improvement in the implementation part.
Likelihood to Recommend
As I mentioned in the begining, we have some influence as our client, his engagement ratio was lesser than expected for good brand/promotion integration despite of good views. We analyzed the comments and share the final insights to the influencer, he made some recommended changes and now he has good engagement ratio. Based on out 8-9 months experience with Google Cloud Natural Language API, I don't find ay scenario which was not upto the mark.
M
Mo Irshad
Innovator in Marketing at Innova Solutions (501-1000 employees)
Vetted Review
2 years of experience