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Triangulated unsolicited user feedback with internal survey findings
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Identified gaps in perception between survey and review data
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Reinforced strategic decisions with data-driven validation
CLIENT CHALLENGES
- A SaaS company wanted to assess user satisfaction in a competitive and evolving market
- Internal surveys captured general sentiment and feature feedback, but lacked unbiased, real-world perspective
- The goal was to validate internal insights, uncover blind spots and enhance the roadmap for product development and customer experience improvements
OUR APPROACH
- Step 1: Data collection and processing
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Extracted five years’ worth of publicly available online product reviews
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Cleaned and structured data using natural language processing (NLP) techniques for further analysis
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- Step 2: Sentiment and theme analysis
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Applied lexicon-based techniques such as VADER and SentiWordNet to classify sentiment as positive, neutral or negative
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Used topic modelling (LDA) to extract core themes to identify key drivers of satisfaction and dissatisfaction
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- Step 3: Survey validation
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Conducted a short follow-up survey to cross-reference top issues and validate sentiment proportions
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Compared insights from online reviews with survey responses to assess alignment and misalignment
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IMPACT DELIVERED
- Validated alignment between internal survey insights and external review sentiment
- Identified critical areas such as “performance reliability” and “customisation options” requiring product improvement
- Equipped stakeholders with clear, triangulated insights to prioritise user experience enhancements
- Supported data-driven decisions in roadmap planning, reducing reliance on single-source feedback
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