How To Use Topic-Based Sentiment Analysis For Customer Insights
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What is topic-based sentiment analysis? Scope of topic-based sentiment analysis How does Topic Analysis work? How is topic-based sentiment analysis used in business models?
Overview You don’t have to be an expert in artificial intelligence to enjoy the benefits of machine learning techniques for better, customer-focussed, business decisions. Topic-based sentiment analysis is perfect for companies who want to take it slow and steady while extrapolating insights they want to derive from consumer comments, reviews, or even just news. You can do away with manual processing of data that can be both expensive as well as error-prone due to human bias and limitations, and switch to automated analysis of your data. This blog articulates how with a simple topic-based sentiment analysis model, you can discover customer insights for incremental benefits without investing too much money.
What is topic-based sentiment analysis? Topic-based sentiment analysis is a natural language processing (NLP) technique that is used to gain meaningful information from text data derived from various sources. This machine learning task identifies and extracts recurrent topics in a text by using sub-tasks such as named entity recognition (NER) and sentiment analysis. NER recognizes and extracts themes or “entities” from unstructured text data and classifies them into predefined categories. These categories can be names of persons, geo-locations, businesses, buildings, brands, medicines, diseases, or any number of categories that can be custom-fed into a machine learning model. The algorithm isolates each topic for its sentiment score by running it through a sentiment analysis process. In this way, an organization can protect its brand reputation by keeping a tab on public sentiment around the various facets of its business. When done at scale, topic analysis can help companies extract valuable business intelligence from large volumes of unstructured data from social media comments, news articles, emails, customer service chats, Voice of the Employee data, Voice of the Customer data, healthcare data, and any such source.
Scope of topic-based sentiment analysis Below are areas where companies can easily use topic analysis to gain valuable business intelligence. ● ● ● ● ● ● ● ●
Monitor brand reputation Knowledge Management Improve products & services Better customer support Market research Competitor analysis Employee nurturing Stock sentiment analysis
How does Topic Analysis work?
Why do we Need VoC Tools?
How is topic-based sentiment analysis used in business models? Topic-based sentiment analysis is used by businesses in manufacturing, finance, hospitality, healthcare, public service departments, etc. across the scope of market research, sales and advertising, knowledge management, and more. Below are real-world examples of how topic analysis has helped companies. ● ● ● ● ● ●
Automotive Manufacturing Banking & Finance Market Research Healthcare & Pharma Government Hospitality
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