The Challenge: Redefining Category Parameters to Match Consumer’s Mental Model
The alcohol beverage category in the Grocery channel had reached a critical inflection point. The lines between traditional segments—wine, beer, spirits, and hard seltzers—were blurring beyond recognition. Expanding category offerings and rapidly evolving consumer preferences created a retail environment of unprecedented complexity.
For one leading alcohol beverage manufacturer, the question was no longer if change was necessary, but how to drive that change with confidence and strategic clarity. The answer was through stronger shopper insights that connected the dots between disparate data sources to reveal the big picture.
For decades, traditional category management has leaned on two pillars: historical sales data and long-held assumptions about shopper behavior. But in reality, assumptions are a liability. They don’t win category captaincies, and they don’t unlock meaningful growth. The Client knew they needed to move beyond instinct and drill down to fundamental truths: How do shoppers actually navigate the aisle? Where do they get stuck? What category structure inherently matches the consumer’s own mental model? By building a single narrative from shopper insights, shopper research, and consumer decision trees, they could see the path to clarity.
The objective: to rationalize shelf flow and product clustering to drive higher category performance, backed by concrete evidence.
The Solution: A Synchronized Approach to Shopper Intelligence
Recognizing that such an ambitious aisle reinvention project would require a collaborative research approach, the Client identified a forward-thinking Grocery retail partner who shared their ambition for innovation. Together, they turned to VideoMining to pilot this shopper research project.
The solution was a synchronized approach that connected direct observation of in-store behavior with AI-powered analysis of decision-making patterns and consumer context cues. This methodology was powered by VideoMining’s new behavioral science platform, BehaviorSync™.
BehaviorSync™ harmonizes observed shopper behavior, purchase data, and consumer context into unified, actionable insights through AI-powered data synthesis. This platform innovates how behavioral research is synchronized to weave data between in-store actions, outcomes, and context into a cohesive view of shopping behaviors.
For this project, it wasn’t enough to uncover what shoppers do: we also needed to connect the why in a way that would support category-wide transformation.
BehaviorSync harmonizes disparate data sources to accurately pinpoint what shoppers do, and why they do it. For this project, 3 phases of market research delivered a cohesive and unified category structure.
VideoMining deployed patented, discreet AI sensors to observe the store environment organically—with no interruption to the authentic shopping experience. This established a crucial baseline, quantifying:
Shopper traffic patterns and dwell times
Engagement rates with specific segments
Trip metrics and category productivity
Friction points and missed opportunities
These measurements transformed observation into actionable shopper insights, creating a reliable foundation for the next phases of shopper research.
Observational research revealed what shoppers did; the next step was to understand why. VideoMining’s team of behavioral scientists deployed targeted surveys to capture contextual signals that allowed them to read between the lines.
The BehaviorSync™ platform integrated this reported data with the observational findings to build validated Consumer Decision Trees (CDTs), revealing:
The anchor attributes shoppers prioritize when making category decisions.
A category segmentation that matched shopper mental models, not legacy trade structures.
The "why" behind walk-aways: where cognitive expectations diverged from physical realities at the shelf.
This synchronized behavior provided the complete picture, quantifying the points of friction in the traditional category model and identifying product attributes that drive shopping decisions at the shelf. Critically, it elevated shopper research into predictive shopper insights and operational consumer decision trees.
The insights from Phases 1 and 2 were translated into a hypothesis-driven test design, implemented in select stores. VideoMining’s behavioral tracking measured the impact of new planograms and aisle configurations to identify winning attributes, along with necessary tweaks to course-correct towards better aisle productivity.
What happened next? For a full run down of the study impact,
.The alcohol beverage category is just one example where connected retail intelligence leads to meaningful impact. With BehaviorSync™, VideoMining’s technology is uniquely positioned to truly decode shopper behavior with unprecedented precision.
Are you ready to replace your assumptions with evidence? Discover how BehaviorSync™ can transform your category strategy.