New York

Dr Hal MacFie

Consultant in Sensory & Consumer Science

Hal MacFie Training Services
Company Registration No: 7864651
Company Address: 43 Manor Road
Keynsham, Bristol BS31 1RB, UK
Contact Tel: (44) 0117 9863590

About Us!

Hands on Consumer Driven Product Optimization

Three one-day workshops designed to give you the knowledge practice and tools to analyse consumer test data and to optimise the sensory properties of foods, beverages, personal products.

Hal MacFie and Anne Hasted

21 to 23 March 2018
Venue:Microtek Labs
180 Maiden Lane
New York, NY 10038

Course Organiser
Hal MacFie
For details and registration e-mail:


Dr. Hal MacFie is a statistician by training, with an international reputation in the areas of product assessment and consumer research. Author of over 100 scientific publications and three books, he was Head of Consumer Science at the Institute of Food Research, Reading England, before becoming Director of the Institute. Dr. MacFie is now an independent consultant, Visiting Professor at Reading and Nottingham Universities and European Editor of Food Quality and Preference.

Anne Hasted began her career as an academic statistician at Reading University, but now runs Qi Statistics Ltd offering statistical training, software and consultancy support to research and industry. She has wide training and consultancy experience in both sensory and consumer research and has an international reputation for “user friendly” training.

Day 1 is designed to take you through the key methods that we use in consumer science and explain how they work and how they are applied to consumer data. Emphasis is given to the practical decision making that is made after each analysis. Participants will apply the methods to real life data using XLSTAT routines and will be guided by the written solutions that are a unique feature of Hal MacFie Training. These solutions give you the possibility to pick up the notes after 6 months or a year and remind yourself how a technique works and then apply it to your own data.

Deliverables: Theory, application and analysis experience in Principal Components (with rotation), Correspondence Analysis, Quadratic regression and inspection of response surfaces and the XLSTAT PREFMAP module applied to a single liking variable, Partial Least Squares and Pathway Analysis.

Day 2 Segmentation, Mapping and Portfolio optimisation
Segmentation Masterclass: This will give attendees a unique perspective: understanding and experience with the three main segmentation algorithms. Practical guidance on selecting the correct algorithm for the task, selecting the optimum cluster set, testing for stability will be given.
The key question with clusters is to identify any predominant characteristics of the membership and we will show a variety of approaches for this.

Deliverables: AHC, KMEANS and Latent Class Segmentation. Cluster Diagnostics and stability testing. Demographic and Psychographic analyses.
Preference Mapping: The workings of the XLSTAT Preference Mapping module will be described, and its application to overall means, segment means and individual scores demonstrated. Product prototype selection and reverse regression to predict the sensory properties of a prototype will be followed by a new section exploring how to integrate the open- ended question responses into the decision making process.. In some categories Preference Mapping on consumer measures are gradually replacing sensory panel scores and a short section will exemplify this approach. Finally an assessment of the role and validity of internal, external and probabilistic models in this application will be discussed
Deliverables: External Preference mapping, Reverse Regression, Using open ended comments, Optimising product portfolios across segments and markets. Comparing internal and external models.

Day 3 afternoon Concept optimisation and Product matching. Many concept trials ask multiple questions including sensory about one or more concepts. How can we examine segmentation in the response to a single concept? Which concepts do we select for further development?
Deliverables: Factor Analysis and Segmentation on question batteries
Typically consumer scientists are asked to supply a product that not only matches sensory expectations but enhances the emotional response and reinforces the Brand. We describe PLS on Fit to Concept measures and the use of Multiple Factor Analysis to handle sensory expectation trials. Brand conceptualisations including sensory, emotion and function can be investigated using CATA and Best-worst measures. MAXDIFF scales for prototypes and concept enable the best matching product to be selected.
Deliverables: Partial least Squares, Fit to Concept, Sensory expectation trials, Multiple Factor Analysis, Best-Worst, MAXDIFF scales, Concept to product matching.
Based around the use of XLSTAT, attendees will gain practical experience using real-life examples and will be able to save their work to take away, so they will be competent to start using their expertise from day 1 after the course. (There is an option to purchase XLSTAT -Sensory at a discounted price.)
Use our Virtual Training Room option and attend the class from the comfort of your office or home.

Course Outline

Day 1 Exploratory and Analytical methods for Consumer Science




Exploratory- Principal Component Analysis
Definition, graphical explanation, scaling. Sample maps, correlation maps, biplots. Interpretation. XLSTAT exercises. Rotating for Interpretability


Exploratory- Correspondence Analysis
Frequency data applications, theory and interpretation, CATA , XLSTAT analysis


Exploratory- Cluster Analysis
Distance and similarity measures, clustering algorithms, dendrogram, defining clusters. XLSTAT exercises

12.30 -13.30



Analytical- Quadratic regression and simple Preference mapping
Ideal point model, quadratic response, surface response diagrams, picking an optimum, multi-response problems. XLSTAT exercise


Analytical- Partial Least Squares
Concept, graphical explanation, cross validation, predictive modelling. Liking to sensory, sensory to instrumental
Reverse PLS to identify target product. XLSTAT exercises


Analytical- Path Analysis – Simple and PATHPLS modelling
Rotated factor modelling, XLSTAT exercises
PATH PLS theory and demonstration

Day 2 Segmentation, Mapping and Product Optimisation


Segmentation Masterclass
AHC versus Kmeans versus Latent Class Analysis
Choosing the method. How many clusters?
PCA versus CVA plotting strategies
XLSTAT exercises
Testing the Stability of the solution. How many non-discriminators?
XLSTAT exercises


Demographics, Psychographics and Segments.
ANOVA approach, Chi-square, Correspondence and CHAID approach


Preference Mapping using the XLSTAT
PREFMAP module
Ideas behind the method, different strategies (overall versus segment means or individuals). Contour plotting. Interpretation of output, decision making. Exercises in XLSTAT




What Sensory Properties will the Desired Product Have?
Using the preference maps to identify “optimal” products. Estimating their sensory properties using reverse regression. XLSTAT exercise

15.00 -16.00

Using Open ended comments in Preference mapping
Role of open ended comments, Quantification
Alternative Preference Map basis XLSTAT exercises


Portfolio optimisation and other approaches
Selecting products for global markets
Internal versus External versus Probabilistic models
A practical approach
XLSTAT Exercise

Day 3 am What can you do with 3 products or less?


JAR Scales and Penalty Analysis
Analysis of JAR scale data (Friedman v ANOVA). Correlation with liking, XLSTAT Penalty Analysis routine,. Interpretation and decision making. XLSTAT Exercises


Ideal Point Profiling
Ideal point scoring, Radar Plotting, Analysis, Product Optimisation
XLSTAT exercise


CATA Data and Kano Impact Analysis
CATA data, significance testing, Kano approach.  XLSTAT CATA routine



Day 3 pm Concept Optimisation and Product matching


Concept and single product trials and analyses
Data set up and theory
Factor Analysis and Segmentation analysis of concept question batteries and interpretation
XLSTAT exercises


Matching Product to concept
PLS of Fit to concept on sensory data
Expectation, Blind and Informed testing, design, conduct and analysis
Multiple Factor Analysis theory and XLSTAT Exercises
Context, Virtual reality trials and analysis

16.00-17.00 Conceptualisation theory, Best-Worst scaling and Analysis
Matching sensory and emotion to concept.
XLSTAT exercises



About the Course Venue:

Location: MicroTek Training Facilities
180 Maiden Lane, New York 10038

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MicroTek’s New York training facility is located in the trending Seaport district of Manhattan. Select rooms are also equipped with MicroTek’s Virtual Training Room technology. These specially designed spaces utilize the latest in audio and video conferencing tools and allow customers to deliver rich, interactive training to both on-site and remote class participants. Public areas include café and lounge areas where training participants can relax between sessions.
The facility design features an open layout, contemporary finishes and an exposed grid ceiling. Bright colors and natural lighting help to create an environment that enhances the learning experience, while the seaport location offers spectacular views of the East River and Brooklyn Bridge. The location is convenient to transportation, hotels, restaurants and shopping. Building amenities include an indoor park/green area and premium catering through the Chef’s Hall.

Please see for details of hotels nearby with discounted rates.


Yes: Please enrol me in Hands on Consumer Driven Product Optimization Course 21 to 23 March 2018

Registration fees:

Day 1 Exploratory and Modelling methods for Consumer Research   $1000
Day 2 Segmentation, Mapping and Product Optimisation  $1000
Day 3 Concept and Product Matching   $1000
Discount for attending all 3 workshops  -$600
XLSTAT Sensory module
Special offer 1 year license at 70% of full price ($590)  $400
Remote attendance using MCLABS  
Virtual Training rooms( $500
This additional charge enables you to attend the course from the comfort of your own desk. The costs include support and training from Mclabs staff and courier your course materials.
Fees reduced by 5% for members of academia - space limited.
We will also provide you with access to your own individual computer for exercises.
Attendees may bring along their own PC laptops for the exercises and we will install a free trial copy of XLSTAT on your computer. (We do not guarantee to load XLSTAT if you have an unusual software configuration.)
Discounts: We offer a 10 % discount on registrations when two or more people from the same company register for the same course, at the same time.

Registration Policy:  Registration is not final until payment is received. Unpaid spaces will be opened to new registrants 30 days ahead of courses.

Payment:  Payment may be made in US dollars, Euros or GB pounds via the Worldpay Gateway or into Currency accounts. Contact for routing and IBAN details of the currency account you require.

Refund Policy: Cancellation of registration can be made up to 30 days ahead, and return of payments, minus reasonable administrative expenses, will be made for these cancellations. Cancellations within 15 to 30 days of the course start will receive a credit for a future course. Registrants who fail to attend or cancel less than 15 days prior to the seminar start date are responsible for the entire fee.

Substitution of another person for the same course may be made at any time.


Course Registration Fees



Number of Places

Course Fee Day 1


Course Fee Day 2


Course Fee Day 3


Discounted 3 Day Course Fee


Virtual Training Room




Total: $

    Payments and Refund Policy    

 For electronic bank transfers: contact for IBAN details
Mailing address for registration and payment:
Dr H J H MacFie
43 Manor Road
Keynsham, Nr Bristol,
BS31 1RB, United Kingdom

Tel/Fax +44(0)1179863590

Electronic registration forms to