Yes, it is. Think of it this way. Have you ever got a message from someone, where you found it difficult to tell whether that person was joking or not? Definitely Yes!! So to avoid the confusion, brands today go for these “sentiment analysis” tools to measure and analyze their customers’ opinions and emotions towards the brand, it’s products, services, etc.
First of all, what exactly is Sentiment analysis?
Sentiment analysis (also known as opinion mining) is an automated process of understanding an opinion (usually a piece of text) whether it is positive, negative or neutral in real-time.
Sentiment analysis is extremely beneficial when it comes to social media. 92% of the businessmen still feel that social media has a significant impact on any kind of businesses these days. However, sentiment analysis enables the businesses to acquire an overview of the public opinion behind their agendas. Achieving perfection in analyzing the sentiments is a win-win situation for any organization.
Additionally, nowadays, businesses consider it to be an essential part of client service strategy and market research. Not only are you able to see what customers think of your products, but also of your competitors as well. The ability to extract data from these insights and understand your consumer attitudes is something that your organization can take advantage of.
With Konnect Insights’ “Sentiment Analysis” tool, you can analyze the tone, emotion and the intent behind each and every message and improve your customer experience. Konnect Insights’ Sentiment Analysis tool basically works on NLP (Natural Language Processing) which in simple terms means that it gives the software the ability to understand the human language, as it is commonly spoken amongst us.
Initially, the tool provides an accuracy of about 80%, but since it is based on ML (machine learning) it is definitely a quick learner, so whenever you change the sentiment of some particular conversation, the tool first learns from it, adapts it and then gets you accurate sentiments (about 85-90% now), if any such instance occurs again.
There can be several instances where the tool might find it difficult to understand conversations. Let’s, for example, take Hinglish (mix of Hindi and English) or sarcastic comments, in these cases; you can always change the sentiments of the conversations and help the tool accurately pick up the intent and emotion behind the conversation.
Once, you get your sentiment analysis right; you can always adjust your marketing strategies, get better and qualified leads, provide better customer services, focus on the quality of products and services and definitely boost your sales.Tags: Sentiment Analysis