What We Do

We Help Shape Public Opinion

Qualitative and Quantitative Data Analysis

Smarter, better decisions to help you win

Public goodwill is about winning the hearts and minds of the people who matter, and therein lies the key to victory. Whether in the marketplace or the battlegrounds of election, to win, you need to know who matters? what matters to them? and what will make them choose you over your competitor? Our science driven approach eliminates guess work, helping you make smarter and better decision than your competitor. Combination of methodologies including qualitative and quantitative data analysis are used to generate insights to inform your strategic decisions.

Blending our proprietary data with unique insights mined through our polling techniques, the insights we provide help you make decisions that increase your competitive advantage and generate public goodwill. Our bespoke approach to answering your most difficult question is what sets us apart from the one-size-fits-all experts. Our unique solutions driven approach addresses some of the most difficult challenges faced by Corporations or Political Parties

Whether it is qualitative or quantitative data analysis, we develop the optimum solutions to best fit your need to find answers. From in-depth interviews, focus groups, jury groups with influential, to conducting the largest ever polling exercise for Indian elections, we reach audiences that are hard to reach and find the answers you need to win.

Market Segmentation

We help you find and connect with your most profitable consumer segments

Thought Leadership Strategy & Research

Most thought leaders are actually thought followers. We help our clients become real thought leaders.

Reputation Management Services

Good reputation is the topmost priority of a Chief Executive

Crisis Communication

News is 24X7. Is your Crisis Plan the Same?

Politics and Government

Don’t just govern the people. Involve them. Walk the talk with them

The Astrum Centre

The Astrum Centre houses a range of best-in-class capabilities

Frequently Asked Questions on Qualitative and Quantitative Data Analysis

What is the difference between quantitative and qualitative analysis?

Quantitative research is a methodology used to generate empirical/numerical data, by employing statistical, logical and mathematical techniques. While, Qualitative research is a method of inquiry that develops an understanding of human behaviour and social sciences, to explore the way people think and feel.
For example, to understand why people feel/carry a perception about a brand would be discovered using qualitative techniques whilst the strength of that perception/feeling within homogenous groups would be discovered through quantitative techniques. This could form the basis of actions and messages needed to inform a reputation strategy. This is what forms the basis of the Science of Reputation ™ at Astrum

What is quantitative data analysis?

What is qualitative data analysis?

Qualitative Data Analysis is the range of procedures whereby we move qualitative information that has been collected, into an explanation, understanding or interpretation of the people and situations being studied. Qualitative data analysis is usually based on an interpretative philosophy. The idea is to examine the meaningful and symbolic content of qualitative data.
Qualitative data is often subjective, rich, and consists of in-depth information normally presented in the form of words. Analysing qualitative data entails reading a large amount of information looking for similarities or differences, and subsequently generating insights.

What is quantitative and qualitative data analysis?

Quantitative data analysis is the process of presenting and interpreting numerical evidence. Quantitative data analysis may include the calculation of frequencies of variables and differences between variables. It is a systematic approach to investigations during which numerical data is collected and/or the researcher transforms what is collected or observed into numerical evidence. It often describes a situation or event, answering the ‘what’ and ‘how many’ questions you may have about something. A quantitative approach is usually associated with finding evidence to either support/ reject hypotheses or exploring facts, measures, numbers and percentages. Statistical consulting applies statistical analysis to quantitative data to make inferences about causal relationships or forecast impact on dependent variable.
Qualitative Data Analysis is the range of procedures whereby we move qualitative information that has been collected, into an explanation, understanding or interpretation of the people and situations being studied. Qualitative data analysis is usually based on an interpretative philosophy. The idea is to examine the meaningful and symbolic content of qualitative data.
Qualitative data is often subjective, rich, and consists of in-depth information normally presented in the form of words. Analysing qualitative data entails reading a large amount of information looking for similarities or differences, and subsequently generating insights.

How do you analyse quantitative data?

Quantitative data means data or evidence, based on numbers. Analysing numeric information produces results from data. Interpreting data through analysis is key to communicating results to stakeholders. The type of analysis depends on the research design, the types of variables, and the distribution of the data.
Quantitative data can be analysed in a variety of different ways:
1. Nominal
2. Ordinal
3. Interval
4. Ratio (scale)
Statistical consulting applies statistical analysis to quantitative data to make inferences about causal relationships or forecast impact on dependent variable.

What is the purpose of qualitative data analysis?

Qualitative data can be observed and recorded. Qualitative data is collected through methods of observations, immersions, interview, focus groups and other similar methods to aid a certain level of understanding, explanation, and interpreting the patterns and themes included in textual data. To put it in general words, qualitative data cannot be expressed in the form of numbers and is often represented in words, observations, pictures, and symbols.

What is the purpose of quantitative data analysis?

The purpose of quantitative data analysis is turn raw numbers into meaningful evidence about the past, current or project the expected. While analysing large volumes of data, it is important to keep in mind the questions that the data needs to provide answers to, so that we use the correct analysis tool. Due to the numerical nature of quantitative data, the personal bias is reduced to a great extent and the results are extremely accurate.

What are the methods of qualitative data analysis?

Qualitative research involves several methodologies ranging from observations, immersion, in-depth interviews, focused group discussions to jury groups and more. Moreover, these may have been collected face to face, telephonically, using video chats or recordings. There could be projective techniques that may have been used to elicit deep seated beliefs and emotions suing drawings, comparisons, collages, etc. The analysis will therefore be very specific depending on the method of data collection, platforms and techniques used.

What is quantitative analysis in research methods?

Quantitative analysis is a technique that seeks to understand behaviour by using mathematical and statistical modelling, measurement, and research. Quantitative analysts aim to represent a given reality in terms of a numerical value. Quantitative analysis provides analysts with tools to examine and analyse past, current, and anticipated future events.
Quantitative analysis is a mathematical and statistical method of studying behaviour and predicting outcomes that investors and management use in their decision-making process. Through the use of research and analysis. Quantitative data analysis help us turn quantitative data into useful information to help with decision making. Quantitative data analysis can be descriptive or inferential. Descriptive statistics help us to summarise our data whereas inferential statistics are used to identify statistically significant differences between groups of data. Statistical consulting applies statistical analysis to quantitative data to make inferences about causal relationships or forecast impact on dependent variable.