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How You Can Organize Reviews Across Platforms to Understand How Your Customers Feel and Optimize Your Offerings

Portfolio Companies
Having in place a customer feedback program can be of immense benefit for any brand. However, you must gear up for the challenges of conducting sentiment analysis in this era of big data. While the data will be there for harvesting, the problem associated with big data will become more pronounced in the post-COVID-19 world.

Data that flows freely can be a combination of structured, semi-structured and unstructured, which is why analyzing this data can pose challenges. The volume of data we expect in the post-COVID-19 world will not be easy for humans to analyze and utilize effectively, and we'll need to integrate artificial intelligence (AI) to help. 

However, in sentiment analysis using product review data, you can deploy Natural Language Processing and computational linguistics to study emotions in subjective information. To find out what customers say and feel about their products or services, brands have always resorted to online reviews.  

Fortunately, sites like Capterra, G2Crowd and Trustpilot have made this relatively easy. They collect public reviews about different products. You can also use the avenue created by e-commerce stores such as Amazon and eBay to gather reviews people leave about their experiences with your product. 

These reviews are mostly unstructured and without employing AI, you end up expending hours of man labor to make sense of the data. Social media presents another opportunity for you to gather the thoughts of people about your product.

The fact that these platforms are free does not make them very reliable for this purpose. The comments may lack authenticity, so you may find it difficult to analyze these comments into positive, negative or neutral.

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