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Free Webinar: From sensory and consumer data to product insights
Assess your panel performance, characterize your products, explore consumer liking, and uncover what drives preference.
With a new free software!

September 30th, 2026 | 16:30–18:00 CET

đź’» Virtual Training

DETAILS

Sensory and consumer studies generate a wealth of information, but turning these data into clear product insights often requires moving across multiple analyses, from checking panel performance to understanding consumer preferences and identifying what drives liking.

This free webinar will introduce a complete sensory and consumer data analysis workflow through a new free web application developed by SensElevation.

Using a practical dataset, we will follow the analytical journey step by step: evaluating sensory panel performance, characterizing products, analysing consumer liking, exploring differences in consumer preferences, and finally connecting sensory and consumer data through internal and external preference mapping.

At each stage, the focus will be on understanding which questions the analysis can answer, how to interpret the results, and how the different analyses work together to build a coherent understanding of products and consumer preferences.

The session will combine key methodological concepts with a hands-on demonstration of the application, showing how a complete sensory and consumer study can be explored within a single workflow.

After this training, participants will be able to:

âś“ Navigate a complete sensory and consumer data analysis workflow, from assessing data quality to understanding consumer preference

âś“ Evaluate sensory panel performance by examining discrimination, repeatability and agreement, and identify potential assessor or panel-level issues

âś“ Characterize products from sensory data, identify the attributes that differentiate them and interpret their sensory positioning

âś“ Analyse consumer liking data to compare product performance and understand how preferences vary across consumers

âś“ Explore consumer heterogeneity and identify groups of consumers with different preference patterns

âś“ Use internal preference mapping to explore the structure of consumer preferences and understand product positioning from liking data

âś“ Use external preference mapping to connect sensory characteristics with consumer liking and identify potential drivers of preference

âś“ Use the new SensElevation application independently to perform, visualize and interpret these analyses on their own sensory and consumer datasets

About the trainers

Dhirendra Singh Gehlot

Dhir has a research background in sensory science and psychophysics, with specialised master's degrees in food-choice determinants and in flavour and fragrance management, along with industry experience. He translates rigorous sensory and statistical methods into practical tools that turn test results into clear business decisions.
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Fabien Llobell, PhD

Founder of SensElevation and former Head of R&D at XLSTAT.

Fabien specializes in sensory, consumer, and market research methodologies. Throughout his career, he has contributed to the development of statistical methods and analytical tools used worldwide and regularly delivers consulting, training, and workshops for industry professionals and researchers.
TRAINING

Training catalogue

Access a unique training catalogue organised into five complementary families: sensory data analysis, statistics & data science, best practices, software, and advanced expertise, combining methodological rigour, innovative approaches, and immediate practical application using your preferred software.


These training programs include advanced and innovative methods designed to help you go further in the analysis and interpretation of your data.


All courses can be customized to fit your specific needs. Practical examples can be delivered using XLSTAT, SensElevation Free Software, JAMOVI, JASP, or R, depending on your preference. Artificial intelligence can also be integrated into the training sessions.

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Get the full training catalogue below:

Cours d'informatique
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