In order to truly understand your voice of the customer (VoC) data, you need to get the most granular insights from comments, reviews, surveys, social media posts, video blogs, and other sources. This is only possible with aspect-based sentiment analysis (ABSA).
Aspect-based sentiment analysis identifies all the semantic threads in the gathered data. It calculates the sentiment for each and every aspect that is defined for that industry- hospitality/healthcare/education, etc. Aspects may be price, location, food, drinks, convenience, and so on.
Whether it’s Twitter sentiment analysis or emotion analysis for surveys, ABSA lays bare the most comprehensive findings. These insights are vital for a number of functions such as brand monitoring, competitor comparison, product enhancements, increased efficiency, employee engagement programs, consumer engagement, etc.
Pena Global provides key business consultation and corporate training to organizations so they are equipped with the right tactics for improved efficiency and better success ratios. The customer needed a comprehensive sentiment analysis solution for a project they had with AARP (American Association of Retired Persons). AARP were designing a new diet program for people over the age of 50 and wanted to know the details of the opinions that people had about different existing diet programs like Weight Watchers or apps like MyFitnessPal.
Repustate created a customized aspect-based sentiment analysis model for AARP. The model read survey responses and Twitter data to analyse sentiment in aspects such as money, convenience, recipes, results, and motivation. It analysed the most common words and phrases people used in their comments via Twitter sentiment analysis and used semantic techniques to find correlations between them. Through aspect sentiment analysis, it discovered several interesting insights that helped AARP create the ideal diet program for older people.
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