A public transport client faced a challenge in integrating qualitative and quantitative data from passenger surveys. While numerical metrics like satisfaction scores were straightforward to analyse, open-text feedback required advanced techniques to extract actionable insights.

We began by auditing survey data and categorizing inputs. Quantitative data was cleaned and standardized, while qualitative responses underwent text analysis using Power BI and analysis techniques to identify sentiment, recurring themes, and key trends in passenger feedback.

Key metrics and themes were aligned with stakeholder priorities, such as service reliability and cleanliness. This guided the design of a Power BI dashboard that seamlessly combined numerical insights with an understanding of overarching passenger sentiment.

Stakeholders’ priorities, such as service reliability and cleanliness, guided the design of a Power BI dashboard that merged numerical insights with visualized text analytics. This provided a unified view, enabling both granular metric tracking and an understanding of overarching passenger sentiment.

To support long-term use of the dashboard, we trained the client’s team.

The solution led to significant improvements in data integration and visibility. By crossing qualitative and quantitative data, the client uncovered new insights into passenger needs and priorities. The unified system enhanced decision-making, allowing the client to address measurable KPIs while understanding the nuances of passenger concerns, ultimately improving service quality and satisfaction.