Working with Big Data
Big Data Analytics is the convergence of two disciplines — big data (transactions, orders, process steps taken, images) and market research and analytical disciplines to understand the key drivers of some observed behaviour.
It entails combining consumer data, behavioural data, attitudinal data and predictive analytics to aid better and faster decisions that yield superior business results, by discovering the root causes of changing patterns and responding faster than your competitors.
Unlock value by embedding data analytics into your operations, interactions, transactions and processes
Combining industry knowledge with innovative methods in statistics, economics, mathematics and data science, we help clients improve their decision-making with insights beyond the scope of traditional market research techniques.
Leverage data analysis solutions, machine learning techniques, statistical modelling and predictive analytics to enable proactive decisions in exploring new business opportunities.
Leverage intelligent algorithms, pattern recognition, machine learning, predictive modelling, behavioural modelling to strengthen informed decision making across supply chain, customer, sales, and risk, finance and workforce domains.
We help organizations take advantage of analytics to drive:
Product recommendations | Cross-sell and up-sell opportunities
Turn data into opportunities
Data Collection, Analysis & Validation
A broad range of approaches and proprietary tools to derive actionable insights.
With the advancement of information & communication technology, we design surveys and gather data on faster, simpler and economical way.
Our survey team delivers powerful insights to help you better understand current consumer preferences, identify emerging trends and pinpoint marketing and product development opportunities in markets around the world.
Qualitative methods
We study the motives, expectations and attitudes of your potential customers through online interviews and group discussions, and validate market data and developments.
Online survey
CAWI - Computer Assisted Web Interviews are fast and accurate online surveys which offer a research-economical study approach
Telephone survey
CATI - Computer Assisted Telephone Interviews to expand the audience of surveys
Face-2-Face interview
CAPI - Computer Assisted Personal Interviews reach demanding target groups (such as doctors) reliably in face-to-face interviews
Cluster analysis
We explore, segment and describe your target groups on the basis of socio-demographic and other relevant characteristics
Optimize your product range and find out how your product should be designed and priced
Factor analysis
Reveal essential factors and properties for the findings
Correlation analysis
Recognize and identify connections! We analyze the relationship between features and open up new perspectives
Regression analysis
Simple, multiple, linear or non-linear regression, we will examine the nature of the relationship between variables in a model
Driver analysis
Identify factors that drive your product and your business to long-term success
Offline Data Collection Tools
Social media Analytics drive effective digital marketing campaigns
We help clients to better perceive and interact with their brand and enhance their marketing communications.
Social media analytics helps to:
Data Analysis
Data analysis comprises of cleaning, transforming and modelling data with statistical tools, such as Cluster Analysis, Factor Analysis, F and T Test, Correlations, Frequent Analysis.
Data Mining Services
Our team can handle data sets of any volume and size, using tools and processes - association, regression, clustering.
Data Processing, Cleansing & Validation
Our data processing solutions make sure that the data you use is relevant, accurate, up to date and not misleading.
We will audit your data, get rid of the errors and make sure it is insightful for analysis.
Data quality is assessed to reduce errors and assure its effectiveness. This is one of the initial steps of analysis with tools such as mean, standard deviation, median, associations and normality, followed by Analysis of Missing Observations and Analysis of Homogeneity to assess the consistency of the data as a whole.
Data Match
Our multi-sourced data bank and proprietary matching algorithms deliver the highest-possible match rates across a holistic range of dimensions.