Company
Global CPG Company
Date
Content
Entropik Team
A Case Study on Unlocking True Consumer Emotion in Product Testing
Introduction
In the highly competitive FMCG and personal care industry, product success depends not just on functionality, but on sensory experience and emotional resonance.
Fragrance, in particular, is one of the most complex elements to evaluate. Consumers often struggle to articulate what they feel, leading to gaps between stated feedback and actual perception.
A leading global consumer goods company partnered with Entropik to address this challenge. The objective was to evaluate a new fragrance formulation (ESA 67) and understand:
Emotional response during first exposure
Scent perception and associations
Distinctiveness and recall potential
Impact on purchase intent
To achieve this, the study combined diary-based qualitative research with Decode’s multimodal AI analytics.
Business Challenge
The brand needed to answer a critical question:
Does the new fragrance create a strong enough emotional and sensory impact to drive purchase?
Traditional research methods were insufficient because:
Consumers used generic descriptors such as “fresh” or “pleasant”
Feedback lacked clarity and specificity
Emotional signals were subtle and difficult to quantify
This created uncertainty around:
Product differentiation
Brand positioning
Market readiness
Research Methodology
The study leveraged a diary-style product testing approach enhanced with multimodal consumer analytics.
Approach
Blind product testing with 26 consumers
Diary-based feedback capturing real-time experiences
Multimodal data collection including:
Facial expressions
Voice tonality
Text sentiment
Why Multimodal Matters
Traditional methods rely heavily on what consumers say. However, emotional responses are often:
Subconscious
Difficult to verbalize
Influenced by social bias
Decode’s multimodal framework captures:
Unfiltered emotional signals through facial coding
Cognitive and emotional intensity through voice analysis
Conscious perception through language
This enables a holistic understanding of consumer experience.
Key Findings
1. High Acceptability, Low Differentiation
Consumers consistently described the fragrance as:
Gentle
Fresh
Floral and slightly fruity
While this indicates broad appeal, it revealed a significant limitation:
The fragrance lacked a distinctive identity.
Consumers struggled to:
Clearly define the scent
Associate it with a unique memory
Identify a dominant note
This reduced its ability to stand out in a competitive market.
2. Emotional Engagement Was Underestimated
Voice-only analysis suggested:
89% neutral emotion
3% positive emotion
However, multimodal analysis revealed:
23% positive emotion
72% neutral
5% negative
This indicates that:
Consumers were more positively engaged than traditional methods suggested.
Facial expressions and behavioral cues captured emotional signals that were not reflected in verbal responses.
3. Neutrality Masked Consumer Uncertainty
A dominant neutral response does not necessarily indicate satisfaction.
In this case, neutrality reflected:
Lack of strong emotional connection
Ambiguity in scent perception
Difficulty in categorization
Consumers described the fragrance as:
Pleasant but indistinct
Familiar yet undefined
This ambiguity directly impacted product recall and differentiation.
4. Weak Purchase Signals
Despite being acceptable, the fragrance failed to generate strong purchase intent.
Key reasons:
No clear olfactive identity
Low memorability
Limited emotional anchoring
As highlighted in the study:
Consumers appreciated the scent but did not feel compelled to choose it over alternatives
Critical Insight for Businesses
This case highlights a key principle in product development:
Consumer liking does not guarantee commercial success.
Products must deliver:
Distinctiveness
Emotional resonance
Clear sensory identity
Without these, even well-received products risk underperformance in the market.
Impact of Multimodal Insights
By integrating diary-based research with Decode’s AI capabilities, the brand was able to:
Uncover Hidden Emotional Signals
Identify positive engagement that was not captured through traditional feedback
Diagnose Product Weaknesses
Pinpoint lack of scent differentiation as the primary barrier
Improve Decision Confidence
Move from subjective interpretation to data-backed insights
Strategic Recommendations
Based on the findings, the brand identified clear optimization directions:
1. Strengthen Scent Signature
Introduce a dominant note to improve recall and differentiation
2. Enhance Emotional Anchoring
Create stronger associations to drive memory and preference
3. Balance Subtlety with Impact
Retain the gentle profile while increasing depth and character
Why This Matters for Enterprise Research Teams
For businesses in FMCG, beauty, and personal care, this case demonstrates:
Limitations of Traditional Research
Over-reliance on verbal feedback
Inability to capture subconscious responses
Risk of misinterpreting neutrality
Value of Multimodal Consumer Insights
Captures real emotional engagement
Reduces bias and ambiguity
Enables faster, more accurate product decisions
How Decode by Entropik Enables Better Product Decisions
Entropik’s Decode platform combines:
Text sentiment processing
to help enterprises:
Measure real consumer emotions at scale
Analyze product experience beyond stated feedback
Optimize formulations before market launch
Improve success rates of new product introductions
Conclusion
This case study reinforces a critical shift in market research:
Understanding consumers requires going beyond what they say to what they feel.
By integrating diary-based methodologies with multimodal AI, businesses can:
Identify hidden risks early
Enhance product differentiation
Build stronger consumer connections
For enterprise brands, this approach is no longer optional. It is essential for delivering products that succeed in increasingly competitive markets.
