Social listening has become a default tool for understanding customer sentiment—but it captures only a narrow slice of the real conversation. Product reviews, app store feedback, and long-form consumer narratives often contain far richer insight, yet remain underutilized due to scale, complexity, and analysis cost.

This session presents a real-world case study from a corporate communications and data intelligence team that moved beyond traditional social and media monitoring to analyze thousands of online product reviews using generative AI. By applying advanced natural language processing and thematic clustering, the team transformed unstructured review data into quantifiable product insights in hours rather than days.

Attendees will learn how AI can surface pain points, strengths, and mixed sentiment at scale—enabling faster, evidence-backed decision-making for product, brand, and reputation strategy. The session reframes online reviews not as anecdotal noise, but as a high-signal source of actionable intelligence.

Target audience
• Corporate communications and public relations leaders
• Brand, reputation, and risk advisory professionals
• Product marketing and product strategy teams
• Customer insights and data intelligence teams
• Digital analytics and AI leaders

Key takeaways
• Why social listening alone provides an incomplete view of customer reality
• The strategic value of online reviews as a product intelligence signal
• Using AI to extract themes, pain points, and mixed sentiment from large review datasets
• Quantifying qualitative product feedback to support data-driven decisions
• Delivering fast, cost-effective insight without large research budgets

Session format
• Case study–driven presentation
• Anonymized examples of review data, thematic clustering, and sentiment breakdowns
• Discussion on integrating AI-driven review analysis into existing insight workflows
• Audience Q&A

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

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

Delivery notes
• Suitable for communications, PR, brand analytics, product marketing, and AI tracks
• Designed for both executive and practitioner audiences
• Fully anonymized content with no client, product, or platform disclosure required

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

Relevant conference types
• Public relations and corporate communications conferences
• Brand, reputation, and risk management events
• Product marketing and customer insights forums
• Data, AI, and applied analytics conferences