12 May 2026
How a leading heritage platform transformed fragmented social listening into a unified framework for understanding cultural moments, enabling their marketing team to launch 12+ targeted campaigns with confidence, while reducing manual analysis time by 60%.
The Challenge
The marketing team was operating in a vacuum. They had intuitions about what messaging might resonate, but no data to validate them.
The insights team—just two people covering international markets—was already stretched thin with ongoing NPS and CSAT analysis.
Without understanding the sentiment, language, and framing people used around cultural moments—especially across different markets—they faced a critical bottleneck.
We had intuitions about what would work, but no data to back them up. Without understanding how people actually talked about these moments across our markets, we were flying blind.
Marketing Lead
Manual Social Listening Across Fragmented Platforms — Collecting data from Twitter, Reddit, and Facebook manually across eight markets was time-consuming and error-prone. Synthesizing findings into reliable themes took weeks of internal effort.
Risk of Tone-Deaf or Culturally Insensitive Campaigns — Without understanding audience sentiment and regional nuances, campaigns risked missing the mark or offending audiences—particularly around sensitive cultural moments.
No Learning Framework Across Moments — Each cultural moment was analyzed in isolation. Insights from International Women’s Day didn’t inform strategy for Mother’s Day or regional holidays, leaving patterns undiscovered.
The Solution
Rather than hire additional staff or build social listening in-house, the organization partnered with an insights platform to create a repeatable, programmatic framework for analyzing cultural moments. The approach unified three disconnected workflows:
Relative Insight scrapes social data from Twitter, Facebook, and Reddit, eliminating manual collection. Data flows directly from source platforms into a unified analysis engine, removing the need for analysts to manually tag or organize raw conversational data.
Rather than manually categorizing responses, the platform identifies dominant themes, sentiment patterns, and regional variations automatically. The team identifies which cultural moments have natural links to heritage versus those requiring more creative framing.
After analyzing the first cultural moment (International Women’s Day), the process became standardized. Subsequent moments (Mother’s Day, Father’s Day, State of Origin, World Cup, Euros) could be analyzed following the same framework, with decreasing time investment.
Why This Worked
The transformation was enabled by shifting from manual data work to automated analysis. Rather than analysts spending weeks collecting and synthesizing, the platform handled the repetitive work, freeing the insights team to focus on strategic interpretation: What does this sentiment mean for our brand? How should we frame our messaging? What regional differences matter?
A critical learning emerged during the first moment: the team realized they needed metadata context (which thread or conversation a comment came from) to avoid skewing findings. If all UK-based sentiment came from a single cynical Reddit thread, the data would be misleading. This insight was built into the process for all subsequent analyses.
The Results
Moments Planned
A full year of cultural moments strategically mapped and ready for campaign execution.
Time Saved
60% reduction in manual data collection and synthesis per moment after first iteration.
Markets Covered
Insights across all international markets enabling region-specific campaign strategy.
This is fantastic for anomaly detection. It’s pointing us to what’s new and what’s different. So much more robust, so much deeper than what we had before.
Director of Customer Experience
- Reduced Campaign Risk: Marketing decisions are now grounded in data about how audiences actually talk, not internal assumptions. Tone-deaf campaigns are avoided before launch.
- Regional Differentiation: The team discovered that Mother’s Day messaging that works in Australia differs significantly from Canada—data-driven localization is now standard practice.
- Cross-Market Learning: Insights from one moment inform strategy for the next. The team built institutional knowledge about which types of cultural moments drive acquisition versus engagement.
- Team Capacity Freed: With outsourced social listening, the two-person insights team maintained their ongoing NPS and CSAT work while adding 12+ moments per year to their output.
