XLSTAT-Sensory

XLSTAT-Sensory, sensory analysis statistical tools in Excel

A reference software in sensometrics: Preference Mapping, CATA, Panel Analysis, Discrimination tests and many more.

What is XLSTAT

XLSTAT is a leader in software for statistical analysis in Excel

Since 1993, we have worked continuously to bring you and some other 50,000 customers from more than 100 countries a powerful, versatile, and above all user-friendly and affordable software to meet all of your statistical needs. 

Featuring over 200 standard and advanced statistical tools, XLSTAT works as a seamless add-on to MS Excel®, allowing you to easily analyze and reformat your data within Excel. XLSTAT is compatible with both PC and Mac.  

XLSTAT uses pioneering computing techniques so that you get actionable results at unbeatable speeds: parallel computing allows you to take full advantage of all your computer processors.

Today XLSTAT offers a wide variety of industry/field specific solutions designed for each and every one of you.

So make way for a statistical software that will change the way you work.

The XLSTAT-Sensory solution

XLSTAT-Sensory is the solution for sensory data analysts who want to gain valuable time by using the most recent methods available. Take advantage of a solution that speaks your language (products, assessors, attributes...) and gives you actionable results. With XLSTAT-Sensory you can give your R&D department the power to create the right products for targeted groups at a reasonable cost.

With tools ranging from multiple factor analysis to product characterization and panel analysis, XLSTAT-Sensory is used by some of the largest food & consumer goods companies in the world.

XLSTAT-Sensory includes all of the XLSTAT-Base solution features in addition to features specific to the sensory data analysis field.

To get even more insightful information from your data, go for the XLSTAT-Marketing solution. It is an enhanced version of XLSTAT-Sensory that encompasses all of the XLSTAT-Sensory features in addition to conjoint analysis, partial least square path modeling and Monte Carlo simulations.