Analysing User Sentiment with Machine Learning
An important aspect of social listening is consumer sentiment analysis. In order to develop and offer products, businesses must pay close attention to the voice of the customer (VoC) to uncover customer satisfaction and decipher their preferences. Offering customers what they genuinely want rather than what companies believe they need, is something product managers must consider in order to build a strong product roadmap. Online review sites are one effective way to obtaining customer feedback on products. However, manually analysing this unstructured data can be challenging and time consuming.
Pain Points/The Opportunity
Product teams sometimes get wrapped up in day-to-day duties and neglect listening to what the consumer is saying. They are unable to collect customer experience, satisfaction, or loyalty data, to improve products and services, or lower churn rates. Moreover, some businesses don’t even get product feedback since they don’t have a feedback loop system in place. As a result, they continue to operate in the dark, failing to recognize customer needs. This is where sentiment analysis comes in to the picture with the help of ML models and deep neural networks.