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Monitor Brand And Product Sentiment In Customer Feedback With This API

Sentiment analysis is a branch of natural language processing that attempts to identify and extract subjective information from text or speech. It can be used to analyze customer feedback, social media posts, and even news articles.

Developers tailor applications as per their clients´ needs to scan text and scrape consumers´ sentiment about products and services.

Monitor Brand And Product Sentiment In Customer Feedback With This API

As you may know, companies have started to pay more attention to customer feedback. This is due to the fact that they want to know what customers think about their products, services, and brand, opinion that will then be used to improve their products, services, and brand, as well as to make sure that they are satisfying their customers’ needs. A reliable application for developers is Opinion Analysis API.

Sentiment analysis APIs are automated solutions to mine consumers´ feedback, that would be time-consuming and expensive to do it manually. This is because it involves reading through hundreds of customer reviews, and then analyzing each review individually to determine its sentiment (positive, negative or neutral). This opinion mining API can perform it more efficiently and effectively.

A sentiment analysis API identifies the emotions in feedback content by examining the use of words in the text, and then classifies them into categories such as joy, disgust, fear, etc.
Furthermore, since an API is a tool that connects two programs, a sentiment analysis API easily integrates into any business systems and processes. This way it`s possible to improve one´s products or services based on what customers like or dislike about them, as one can better understand the needs of one´s customers.

The sophisticated ML algorithms make it possible to scan the sentiment of people, and not only for commercial purposes, but also for agencies that survey the support or detraction towards political leaders, or to gauge the popularity of an organization or a decision maker. The use cases of this API are countless, and developers customize applications for their clients according to their expectations.

Sentiment analysis APIs analyzes text data, feedback and reviews on social media and websites like Amazon and eBay, and also monitor brand sentiment in real-time, which makes them ideal for businesses that want to stay up-to-date with their customers’ reactions. It´s the best way to identify any potential issues with one´s products or services before they become major problems. In addition, you will be able to see what customers like most about your brand, so as to focus marketing efforts on those aspects.

Go beyond sentiment with Opinion Analysis API to determine if a social post is a promoter, detractor, or indifferent suggestion. Discover what consumers think and feel about your brand and what you can do to strengthen the emotional connection with consumers.

To Get Started With This Sentiment Analysis API

Monitor Brand And Product Sentiment In Customer Feedback With This API

If you already count on a subscription on Zyla API Hub marketplace, just start using, connecting and managing APIs. Subscribe to Opinion Analysis API by simply clicking on the button “Start Trial”. Then meet the needed endpoint and simply provide the search reference. Make the API call by pressing the button “test endpoint” and see the results on display. The AI will process and retrieve an accurate report using this data.

Opinion Analysis API examines the input and processes the request using the resources available (AI and ML). In no time at all the application will retrieve an accurate response. The API has one endpoint to access the information: Analyzer, where you insert the opinión you need to analyze.

If the input is “id”: 1, “language”: “en”, “text”: “There´s place for improvement” in the endpoint, the response will look like this:

[ 
{ 
"id": "1", 
"predictions": 
[ { "probability": 1, 
"prediction": "Indifferent" } 
] 
}
Published inAPIApps, technologyTechnology
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