Customer Sentiment Analysis – Why It’s Important For Business Growth

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Customer Sentiment Analysis – Why It’s Important For Business Growth


Table of Content ● Understanding Customer Sentiment ● Why Customer Sentiment Analysis is Important ● How is Customer Sentiment Analysis Done?


Overview The best catalyst to boost your business growth efforts and increase your ROI is customer sentiment analysis. Whether you are a B2B company or a B2C, some of the best insights you can get to help you grow is by understanding the sentiment of your customers. It’s a given that companies must be data-driven to make sure that they are on track in pursuing their financial objectives and goals. Most companies emphasize data such as sales figures, total revenue, year-on-year growth, etc. but many overlook consumer sentiment insights derived from customer experience data. AI-enabled customer experience (CX) analytics bridges this gap. They give you a data-backed roadmap to optimize marketing and sales efforts, better products and services, and generate more revenue.


Understanding Customer Sentiment Customer sentiment is how consumers feel about their experience with a brand or product. People express these opinions and feelings in social media forums, review websites, surveys, user-generated videos on YouTube, customer care emails, and other ways. Machine learning algorithms automate the analysis of this data using tasks such as natural language processing (NLP) and semantic clustering. These tasks help extract aspects, entities, and sentiments from the data and classify them as positive, negative, or neutral. They also combine the sentiment scores of various aspects and give an overall sentiment of a brand or product.


Why Customer Sentiment Analysis is Important



How is Customer Sentiment Analysis Done? To understand how machine learning-based emotion mining works, let’s take a look under the hood and see how a sentiment analysis API processes data. Step 1: Gathering Data Step 2: Data Processing Step 3: Data Analysis Step 4: Data Visualization


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