A global cloud computing leader works with iMerit to improve its understanding of customer sentiment and preferences. With millions of users worldwide, the company needed to generate valuable insights from its customer reviews to enhance product and service offerings.
“With a precise approach of the iMerit team, we gained invaluable insights into customer preferences and pain points, allowing us to tailor our products and services more effectively.”
– VP of Customer Service

Problem
The challenges in this project were multifaceted, starting from the consolidation of sentiments tied to diverse aspects of the data and the precise definition and location of various elements within reviews. Achieving comprehensive sentiment analysis required a deep dive into nuanced expressions to fully comprehend the overarching sentiment directed toward specific attributes in the reviews.
Solution
iMerit’s approach included deploying a robust sentiment analysis ML model. High-accuracy data labeling was crucial for enhancing the model’s performance and precision, and the ML model underwent training on a diverse array of labeled data. Our teams, comprising skilled annotators, verified the model predictions for the refinement process that enhanced the overall performance.
Results
The collaborative effort between iMerit and the global technology company in entity tagging, aspect identification, and sentiment analysis led to an improved understanding of customer preferences and behaviors. The data annotation solution by iMerit empowered the company to leverage insights for strategic decision-making, enhancing customer satisfaction and informing future business strategies.
BOTTOM LINE IMPACT
95%
Data Annotation Accuracy
60k
Tasks executed
15%
Boost in Efficiency