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Success Stories Understanding customer attitudes with sentiment analysis for a fast-food industry giant

Understanding customer attitudes with sentiment analysis for a fast-food industry giant

Customer reviews were there. The insight was not.

A leading global fast-food brand wanted to analyse and understand customer reviews about their products and services - to identify issues and improve overall customer experience. The data existed: tens of thousands of reviews across online channels, stores and categories. But it was unstructured, sitting in multiple sources, and there was no systematic way to understand what customers were actually saying - which products were generating negative feedback, which stores were underperforming, how sentiment was trending over time. Manual review of customer feedback at this scale was not feasible.

End-to-end sentiment analysis. A dashboard that tells the story.

One51 designed an end-to-end solution using Azure Cognitive Services for sentiment classification and NLP analysis of customer reviews. The pipeline connected review data from multiple channels, applied sentiment classification and entity extraction to identify products, services, stores and themes, and delivered the results in an interactive Power BI dashboard. The dashboard enabled filtering by time, store, channel and category - allowing the marketing and operations teams to understand exactly where their customers were satisfied and where they needed to act.

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  • Sentiment classified

    Across all channels, stores, categories and time periods

  • Word cloud

    Identifying the most common issues raised by customers automatically

  • Actionable

    Insights enabling targeted improvement by store, product and channel

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