top of page


Make the most out of your data

We fuse technology with data science tools to help organizations stay relevant and competitive in this fast-paced world. We then use the insights to craft innovative strategies. Get in touch to learn more about how this service can help you.

Analytics: Welcome


Data is everywhere, big, small, and most ambiguous, “The value of an idea lies in the using it ~ Thomas A. Edison”,

Auditing data is a process of analyzing data for anomalies (inconsistencies), patterns to produce meaningful leanings. Do you have data? Are you struggling with where to start? whether structured or unstructured, we provide an open synthesis and objective discussion and diagnostics


Data Audit And Strategy

Basic Data Analysis

  • One way ANOVA

  • Principal Component Analysis

  • Multiple Linear Regression

  • Basic Descriptive statistics

  • Correlation test

Read More >

Sensory Research

  • Multiple factor analysis

  • TURF analysis

  • Sensory shelf-life analysis

  • CATA (Check-All-That-Apply) Analysis

  • Generalized Procrustes Analysis (GPA)

  • Preference Mapping

  • Sensory Panel Analysis

  • Penalty Analysis

  • Sensory discriminant triangle test

Read More >

Data Modelling

  • Correlation/Association tests

  • Parametric tests

  • Nonparametric tests

  • Testing for outliers

  • Mathematical Tools

Read More >


Grow Your Business

Whether it is a process, product, or an idea, life is full of statistics “If statistics are boring, you’ve got the wrong numbers ~ Edward Tufte. Do you have doubts about the statistical test to do? Do you want a second professional opinion? Do you have questions about your dataset? We are here to help; we are well-trained and experienced experts in a wide variety of statistical and analytics methods. From study design, sampling, and sample size calculations. Statistical analysis ranging from significance testing to (multivariate) analysis and much more!


Peek into the future

How well can you segment your customers/population into groups that differ from each other, based on some quantity of interest? Would you want to know which customers are likely to leave, who are more likely to default, or which documents/web pages contain the most relevant content to your business? Whether it is supervised or unsupervised machine learning techniques, we have the solutions. We have applied regression, logit analysis, cluster analysis, latent class analysis, Bayesian models, neural nets, decision trees, and much more, your need will dictate the method.


Focus on the most important factor

This is a variety of methods used in identifying the factors which affect a metric of interest. For example in business, the most important factor on customer satisfaction, or in social, such as the most appealing behavioral change agent. “A powerful idea is absolutely fascinating, and absolutely useless until we choose it” ~ Richard Bach. Driver analysis will help you understand what makes customers

prefer your brand versus a competing brand, or how to create a unique proposition.


Learn patterns more efficiently

These are unsupervised methods that have been applied in many complex data situations to help in discovering patterns. Do you have much data and no hypothesis? Have standard approaches not been promising? It’s time to try machine learning, Bayes and neural nets, or even deep learning.

Some of the common methods we have used are

  • Classification and regression trees

  • K Nearest Neighbors (KNN)

  • Classification and regression random forests

  • Naive Bayes classifier

  • Support Vector Machine

  • One-class Support Vector Machine

  • k-means clustering

  • Fuzzy k-means clustering

  • Gaussian mixture models

  • Association rules


If your understand, you will serve them better

Market segmentations have lately been one of the hard nuts to crack in dividing the market into product categories, such as a product’s function or price perhaps, or dividing the customer base into target demographics, such as age, gender, or income level. Some of the new frontiers are the use of latent class segmentation methods, these are methods that use probability/likelihood to predict the classification of a consumer to a certain group, based on patterns in multiple variables (such as attitudes and needs or buying behaviors.

Statistical Support
Predictive Modelling
Driver Analysis
Machine Learning
Market Segmentation
Other Statistical Solutions
bottom of page