Bridging consumer and technical sensory perspective on characterization of skin care products
Podium 40
Presented by: Karine Desseille
Objective
This study seeks to address the gap of consumer language (semantics) and technical sensory language (syntax) in the characterization of personal care products, thus expediting formulation development through a predictive skin care ingredient selection.
It is important to gain the understanding of consumer perspectives using consumer-centric methods, albeit characterization of the sensory properties of products remains a cornerstone activity for sensory professionals.
Our objectives were: (1) Connecting and merging technical sensory with consumer perception, (2) Understand cross-cultural consumer perception, (3) Develop tool that allows predictive ingredient selection based on consumers’ desired sensory profile.
Methods
Twelve oil-in-water emulsifiers, were selected and used in same simple base formulation as emulsifier is a key ingredient to drive the initial sensory feel of skin care products. The consumers were based in either Singapore or France, thus providing insight into two prominent yet culturally opposing regions.
The study was conducted in three phases where 100 consumers from each region were recruited, screened and built the texture vocabulary using word association method; and thereafter rate the samples using rate-all-that-apply (RATA) methodology. Descriptive analysis (DA) using 16 trained panel from UK and Singapore, based on 21 sensory attributes across three stages, namely at pickup, rubbing in and after-feel, were used. The results from RATA were then compare with the results from descriptive analysis (DA) by trained panel.
Match-Sense-Matrix was developed to bridge consumer and technical sensory language; and examine their correlations. Similarity of sample configuration in the sensory space between RATA and DA was assessed by means of multiple factor analysis (MFA) and RV coefficients. In Sense, Principal Component analysis (PCA) to determine the sensory space of the products across the 17 attributes for at play stage.
Results
For the Singaporean consumer, the semantics has been established and contains 17 attributes at rubbing stage and 21 were defined for the after-feel attributes that allow the evaluation of emulsifiers during these two stages.
Similarly, the French consumer semantics has been established where it contains 21 in rubbing and 17 in and after-feel stage. There was a good agreement (RV>70%) for both consumer groups between the RATA and the DA results, which represented the consumer lexicon and technical sensory terms, respectively.
Discussion
Sensorial preference drivers for both the Singaporean and the French consumer were also highlighted. It was found that ‘fresh’/‘frais’ (in French) was a top preference driver for each consumer group. Based on the insights generated, the meaning of the word ‘fresh’ is quite similar for both groups, however there are variances in expectation, thus leading to a different oil-in-water emulsifier system being recommended to meet the optimal requirement of ‘fresh’ or ‘frais’ for the Singaporean and French consumer, respectively.
Another interesting attribute is ‘Rich’ for the Singaporean consumer and ‘Riche’ for the French consumer. These descriptors may indeed sound very similar, however they have different meanings to each group, thus resulting in various recommended emulsifier systems. This reinforces the importance of understanding the expectations of the consumer for whom the formulation is being created.
To exploit this valuable data to its full potential, the SenStories™ Selector tool has been developed, which enables predictive ingredient selection by allowing the user to discover oil-in-water emulsifier systems based on the consumer desired sensory
Conclusion
Apart from developing a consumer lexicon, the study also showed that RATA methodology using consumers result in very similar sample discrimination and configuration as DA with trained panelists, when evaluating emulsifiers.
This can also improve the collaboration between marketing and formulators in optimizing product development.
This SenStoriesTM methodology and the tool can be extended to another consumer region group to gain a deeper understanding of the associated consumer terms and expectation. Additionally, this can be complemented by a study on the impact others type of ingredient on the sensory during the rub out or afterfeel to start building a complete predictive model.
This study seeks to address the gap of consumer language (semantics) and technical sensory language (syntax) in the characterization of personal care products, thus expediting formulation development through a predictive skin care ingredient selection.
It is important to gain the understanding of consumer perspectives using consumer-centric methods, albeit characterization of the sensory properties of products remains a cornerstone activity for sensory professionals.
Our objectives were: (1) Connecting and merging technical sensory with consumer perception, (2) Understand cross-cultural consumer perception, (3) Develop tool that allows predictive ingredient selection based on consumers’ desired sensory profile.
Methods
Twelve oil-in-water emulsifiers, were selected and used in same simple base formulation as emulsifier is a key ingredient to drive the initial sensory feel of skin care products. The consumers were based in either Singapore or France, thus providing insight into two prominent yet culturally opposing regions.
The study was conducted in three phases where 100 consumers from each region were recruited, screened and built the texture vocabulary using word association method; and thereafter rate the samples using rate-all-that-apply (RATA) methodology. Descriptive analysis (DA) using 16 trained panel from UK and Singapore, based on 21 sensory attributes across three stages, namely at pickup, rubbing in and after-feel, were used. The results from RATA were then compare with the results from descriptive analysis (DA) by trained panel.
Match-Sense-Matrix was developed to bridge consumer and technical sensory language; and examine their correlations. Similarity of sample configuration in the sensory space between RATA and DA was assessed by means of multiple factor analysis (MFA) and RV coefficients. In Sense, Principal Component analysis (PCA) to determine the sensory space of the products across the 17 attributes for at play stage.
Results
For the Singaporean consumer, the semantics has been established and contains 17 attributes at rubbing stage and 21 were defined for the after-feel attributes that allow the evaluation of emulsifiers during these two stages.
Similarly, the French consumer semantics has been established where it contains 21 in rubbing and 17 in and after-feel stage. There was a good agreement (RV>70%) for both consumer groups between the RATA and the DA results, which represented the consumer lexicon and technical sensory terms, respectively.
Discussion
Sensorial preference drivers for both the Singaporean and the French consumer were also highlighted. It was found that ‘fresh’/‘frais’ (in French) was a top preference driver for each consumer group. Based on the insights generated, the meaning of the word ‘fresh’ is quite similar for both groups, however there are variances in expectation, thus leading to a different oil-in-water emulsifier system being recommended to meet the optimal requirement of ‘fresh’ or ‘frais’ for the Singaporean and French consumer, respectively.
Another interesting attribute is ‘Rich’ for the Singaporean consumer and ‘Riche’ for the French consumer. These descriptors may indeed sound very similar, however they have different meanings to each group, thus resulting in various recommended emulsifier systems. This reinforces the importance of understanding the expectations of the consumer for whom the formulation is being created.
To exploit this valuable data to its full potential, the SenStories™ Selector tool has been developed, which enables predictive ingredient selection by allowing the user to discover oil-in-water emulsifier systems based on the consumer desired sensory
Conclusion
Apart from developing a consumer lexicon, the study also showed that RATA methodology using consumers result in very similar sample discrimination and configuration as DA with trained panelists, when evaluating emulsifiers.
This can also improve the collaboration between marketing and formulators in optimizing product development.
This SenStoriesTM methodology and the tool can be extended to another consumer region group to gain a deeper understanding of the associated consumer terms and expectation. Additionally, this can be complemented by a study on the impact others type of ingredient on the sensory during the rub out or afterfeel to start building a complete predictive model.