Mystery shopper programs generate some of the richest customer experience data available—detailed, observational, and deeply contextual. Yet the very verbosity that makes this feedback valuable also makes it difficult to analyze at scale. Traditional manual coding approaches are time-consuming, inconsistent under tight timelines, and often limit how deeply analysts can explore open-ended responses.

This session presents a real-world case study from a customer experience research and advisory organization that adopted generative AI to accelerate and deepen analysis of mystery shopper feedback. Attendees will learn how AI was used to surface sentiment, themes, and mixed signals within narrative reports, enabling faster turnaround while preserving analytical rigor.

The session explores how qualitative CX data can be transformed from a reporting burden into a strategic asset—delivering richer insight, stronger client storytelling, and more actionable recommendations.

Target audience
• Customer experience (CX) and customer insights leaders
• Market research and advisory firms
• Retail, hospitality, and service operations leaders
• Analytics, data science, and insight teams
• Digital transformation leaders working with qualitative data

Key takeaways
• Why verbatim mystery shopper feedback becomes a bottleneck at scale
• Limitations of traditional manual coding under tight client timelines
• Using generative AI to extract sentiment, themes, and mixed signals from verbose narratives
• Capturing subtle “nuggets” of insight often missed in top-line summaries
• Delivering faster, deeper, and more consistent insights to client stakeholders

Session format
• Case study–driven presentation
• Anonymized examples of verbatim feedback, sentiment splits, and thematic summaries
• Discussion on integrating AI into existing CX research workflows
• Audience Q&A

Preferred session duration
• 30 minutes (conference breakout)
• 45 minutes (with Q&A)
• 60 minutes (extended discussion or applied workshop)

Technical requirements
• Projector or large display
• HDMI or USB-C connection
• Internet access optional (not required for core delivery)

Delivery notes
• Suitable for CX, market research, analytics, and digital transformation tracks
• Designed for both practitioner and leadership audiences
• Content is fully anonymized with no client identification or proprietary disclosure

First public delivery
• Suitable for first public delivery as an anonymized real-world case study

Relevant conference types
• Customer experience and customer insights conferences
• Market research and analytics events
• Retail, hospitality, and service-industry forums
• Data, AI, and applied analytics conferences