We have all been there and done that! Picked up our phone or tablet, whichever is more easily accessible and dashed off a tweet, comment or review on whichever product/service caught our fancy, or maybe not!


Before the social media age rolled in, businesses were mostly not aware of the widespread consumer opinion about their product/service and were to a large extent not bothered about what they to say. But, a simple tweet, a like, a comment and a retweet changed all of that!

In the context of businesses, a sentiment is at its core, the feeling that users, consumers, vendors, partners or employees have towards a particular brand, company, product or service. Sentiment Analysis is collating and analyzing data in order to find out attitude, opinions, feelings or emotions hidden within the data. Now, these sentiments could be negative or positive. Sentiment Analysis uses natural language processing (NLP), text analysis and computational linguistics to identify and extract information.

For example, Sentiment Analysis algorithms could look for words that carry a positive or negative overtone through keywords. If a business can use a Sentiment Analysis API, it could easily analyze trends, customer sentiments and product popularity through webpages, blog posts, reviews, comments, likes, tweets and more.

Pretty nifty, especially for consumer facing businesses!

Combined with advances in Big Data, it’s a powerful way of gauging customer experience and engagement. By assessingsentiment in real time, businesses can get insights on brand impressions people have and any potential problems looming. The data can give companies an understanding on how their brands are perceived vis-à-vis competitors and take corrective measures to ensure competitive standing.

Today, with message boards and review sites like Epinions and Yelp, mushrooming, businesses need to keep an ear out for what is being discussed about them and proactively take steps to correct any wrongs.

Case in point, the infamous American Apparel tweet that was the target of negative backlash by its customers. Their Hurrican Sandy Sale was in bad taste and left even their loyal customers shocked. And it created an uproar on Twitter.


This was an example of swift and severe backlash to something the company tweeted about. In today’s age, consumers are not shy of airing their opinions, likes and dislikes to the world. Used prudently, opinion analysis can help in vastly improving customer experiences, prospecting new customers and in faster decisions.

There are a host of sentiment analysis products in the market today from heavyweights like IBM (that offers Social Media Analytics software on a SaaS model) and SAS to many open-source Sentiment Analysis API’s.

So, you know you love your customers. Go on; find out if they love you back!

I would love to hear your thoughts. Share them below!

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