Global Beverage Manufacturer
Finding the levers that move beverage sales across channels
At a glance
Customer Label
Global beverage manufacturer
Who This Is For
Research & insights teams, Category management
Industry / Team
CPG & Retail
Mavera use cases
Causal modeling
Field observation analysis
Cross-channel insights
Key outcomes
•Identified 6 causal drivers of purchase behavior
•Unified insights across 4 retail channels
•Created repeatable framework for market expansion
Context
With beverage sales happening across increasingly fragmented touchpoints—from traditional drive-thru to mobile apps and third-party delivery—this manufacturer needed a unified understanding of what actually drives purchase decisions in each environment.
The Challenge
The team had rich observational data from field research and transactional data from retail partners, but no way to establish causal relationships between environmental factors and sales outcomes. Each channel was analyzed in isolation, making it impossible to identify universal drivers or allocate resources confidently.
Why They Turned to Mavera
Traditional analytics couldn't separate correlation from causation, and qualitative research alone couldn't quantify impact. The team needed a platform that could integrate observational and behavioral data to reveal true cause-and-effect relationships across channels.
What They Did with Mavera
The team used Mavera to analyze field observations alongside point-of-sale data across drive-thru, kiosk, app, and delivery channels. They mapped environmental variables, promotional tactics, product placement, and service elements to actual purchase behavior, running causal inference models to isolate true drivers from noise.
Key Insights
•Six P's of Influence: Product visibility, Promotional clarity, Placement logic, Pace of service, Personalization cues, and Price transparency emerged as the six causal drivers across all channels
•Channel-specific amplification: While all six factors mattered everywhere, their relative impact varied by channel—app experiences were 3x more sensitive to personalization, while drive-thru was dominated by pace and placement
•Compound effects: Two or more P's working in concert created non-linear sales lift, revealing optimal combinations for each channel type
•Universal framework: The same causal structure applied across 12 markets, enabling scalable optimization
Impact
The Six P's framework became the foundation for retail environment optimization across markets. Category teams now use Mavera to test interventions before rollout, predict channel-specific impact, and allocate trade spend based on proven causal drivers rather than historical patterns. The approach has been adopted across three beverage categories and is being extended to food products.
Why This Matters
Most retail organizations are drowning in data but starving for causal understanding. This case shows how combining observational rigor with behavioral data—when analyzed through a causal lens—can transform fragmented insights into a unified, actionable framework that scales across channels and markets.
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