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Quantitative research entails objectively and comprehensively collecting numerical data to help analyze, describe or predict the topic at hand. In general, this form of market research aims to test relationships between variables, and extrapolate results to wider populations.
Research which generates data that usually entails questions like “How many”, or “how much”, or “with what frequency”. The data gathered by such research is mathematically verifiable. Simply put, most parameters or attributes relating to a topic can have a quantity attached to it. Take software for example – market researchers can ask: “How many units did software A sell?”, or how “In how many days did software A sell x amount?”
As the data collected via quantitative research is usually numerical you can consider this form of research to be a statistical method for collecting data.
Essentially there are two ways of collecting data quantitatively – via one on one interviews or through surveys. It’s now possible to conduct quantitative data research telephonically, online or via face to face surveys.
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Traditionally, surveys were paper-based and conducting them was a time consuming process. However, survey technology has improved significantly over the last few decades. For quantitative research, one should be looking at close ended questions as they’re better at collecting numerical data. Researchers should include options which they believe are most suited to the topic at hand. You should also keep in mind that the responses you collect can be easily scaled up to fit population data.
Quantitative data surveys can be further classified into:
Cross-sectional research: This is a type of study which analyzes data from a population, or a topic at a particular time period. Usually researchers create a questionnaire about a topic, and ask respondents questions which can help them understand aspects about a subject at a specific point in time.
Longitudinal research: A type of market research in which researchers conduct surveys which refer to a period of time. Longitudinal research helps in trend analysis or any form of research where the goal is to collect and analyze data to look for patterns.
Correctly setting up quantitative research is a fairly straightforward process, but it needs to be structured properly to get the most accurate results possible.
Ideally one should ensure they cover their bases by incorporating the following steps in their research process.
Frame your questions: You need to ensure that you include all measurement scales that you would require for your survey. Nominal, ordinal, ratio and interval scales form the basis of multiple choice questions, and are essential for multiple choice questions in a survey.
Be sure to use correct survey question types: For quantitative data collection, one needs to collect survey responses from close ended questions. Question types like constant sum, slider, multiple choice matrix, rating scale are extremely effective tools for quantitative research.
The key to getting more accurate data from surveys is distribution. You can make the most comprehensive survey possible, but your efforts will be in vain unless you’ve spread your survey effectively, and to the right respondent base.
Here are a few platforms which you should leverage for dispensing your surveys effectively:
Social media: Everyone’s on social media these days, which makes it a good place to find respondents for your surveys as well. This platform is especially useful for quantitative research conducted on behalf of known brands, services or products.
Email: You’ve probably seen this yourself – an email asking you to participate in a survey. Email survey invitations are an extremely effective method to get respondents for your surveys. Also, as you are in control of who you send the email to, you can ensure that the respondents are of a calibre that does right by your survey.
API integration with your platform: Whether its a mobile app, or windows program, tools like Voxco survey software allows you to integrate surveys anywhere.
Embed on a website: Chances are your target audience are already visiting your website – embedding a survey on your domain can help get relevant insights from quantitative data collection surveys.
Hire respondents: Hiring professional respondents for your surveys is an effective method of collecting data. These respondents are usually more knowledgeable and have prior experience giving surveys, and can provide accurate insights.
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After you’ve gathered data, you need to analyze it to derive insights. Statistics help turn the results of quantitative research into actionable insights. They help summarize your data and help paint a story about patterns and relationships about the topic at hand.
Here’s a few commonly used methods for analysing quantitative data:
Conjoint Analysis: Conjoint analysis is a method which helps analyze factors behind a purchase decision. One can use this method to gather metrics and analyze them for intelligent insights into purchasing decisions as well as rank the factors by importance.
Trend Analysis: This is a statistical form of analysis which has the capability to look at collected data that has been collected for a long period of time. It helps researchers collect feedback and track changes in respondent behavior over time.
Cross-tabs: Crosstabs are one of the most widely used methods for quantitative data analysis. It uses a basic table format for drawing insights from multiple data sets in your research.
MaxDiff Analysis: Like conjoint analysis, MaxDiff is a method of data analysis that is used to understand customer preferences, and see which factors rank higher when customers make a purchase.
SWOT Analysis: SWOT analysis is a commonly used analysis method that when used for quantitative data analysis, assigns numerical values to indicate strengths, weaknesses, opportunities and threats of the topic in question.
We’ve talked about what quantitative data is, but what about Qualitative research? What does it involve?
Qualitative data is non statistical and is usually semi structured. The data in question doesn’t have to be measured in cold hard numbers, and can be categorized based on other pre decided attributes. You can read more about qualitative data research here.
Objective nature: As quantitative data is based on statistical data and analysis, it is considered to be scientifically objective.
Requires expertise: Researchers need to be experienced to get insights from this type of data collection
Can be quickly analyzed: Voxco’s omnichannel survey software can quickly analyze data collected via quantitative research.
Suspect to confirmation bias: Researchers can possibly miss out on noticing trends and instead focus on confirming their hypothesis or theory.