A technology startup specializing in AI-driven software solutions sought to enhance its customer service capabilities by automating the analysis of customer feedback.

Challenges:

• The company faced an overwhelming amount of unstructured customer feedback from multiple sources, such as emails, social media, and product reviews, and lacked an efficient way to analyze and extract valuable insights.
• The goal was to identify recurring issues and improve customer satisfaction by understanding customer sentiment and needs.

Solution:

Quanois implemented a Natural Language Processing (NLP) model to process and analyze customer feedback in real time.

• Data Engineering:

  We created robust data pipelines to collect, clean, and structure feedback data from various sources, ensuring it was ready for analysis.

• Advanced Analytics:

  We applied sentiment analysis to identify common pain points and measure customer satisfaction trends, enabling the company to make data-driven decisions.

• Results:

  • Reduced customer service response times by 35%.
  • Increased customer satisfaction scores by 20%.
  • Provided actionable insights that helped improve product features and customer support processes.