5 Methods of Data Collection for Quantitative Research

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mrx glossary quantitative data collection

In this blog, read up on five different ways to approach data collection for quantitative research studies. 


Quantitative research forms the basis for many business decisions. Data-backed metrics indicating how business actions are likely to impact consumer behavior and attitudes are not only reassuring, but they also save valuable time and money. But which data collection methods are used in quantitative research and how do they differ? In this blog, we’ll take a look at five of these methods.


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What is quantitative data? 

Quantitative data deals with actual numbers and metrics. Brands use quantitative data to collect a set number of responses via quantitative research methods. Quantitative studies tend to be gathered using mainly closed-ended questions in questionnaires (such as yes/no questions, or a list of answers to select from) and are distributed to a sample of people who represent the target market for a business. So for a cookie brand’s quantitative study, the sample might be those who eat cookies, those who buy from the business’s brand, or those who buy from competitors. The study might ask these respondents questions like ‘Do you eat cookies for dessert?’ or ‘What kind of cookies do you like?’ - with a list of flavors/types to choose from.

Quantitative data is expressed in numbers or percentages - for example, 850 people out of those surveyed eat cookies for dessert. Or, 28% of 45-55-year-olds prefer cookies with chocolate in them. These kinds of statistics help businesses formulate a picture of their target audience (and potentially its subgroups) so that products and services can be developed and marketed according to consumer needs. Because these important business decisions are made based on research findings, a quantitative research sample must be large enough to apply statistical analysis and to provide a reliable and representative indication of the target audience at large.

In contrast, qualitative research is more exploratory and descriptive in nature - using focus groups or in-depth interviews (as two examples) to discuss research subjects amongst a smaller sample.

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Why is data quality important for quantitative research?

While quantitative research focuses on numbers and the quantity of the findings, these findings are highly dependent on the quality of the data as well. Without knowing the quality of your data source, there’s no way to be sure that the numerical data you’re basing decisions off of is sound.


Quantitative data findings can lead to business projections such as - how many people will buy white chocolate cookies, what percentage of people prefer plastic packaging over cardboard boxes, what proportion of people choose a certain brand over its competitors, how many people would try a new cookie product based on new advertising, and so on. These business projections are often serious investments for a business and not ones to be made based on unreliable or poor-quality data.


Poor-quality data would be sampling a non-representative group, capturing responses from consumers without screening them for certain credentials, or not reviewing the actual quality of responses to ensure respondents took a survey seriously. Simple data verification checks can ensure that a respondent didn’t just breeze through a survey and select random answers, or didn’t just select the first checkbox at every question before moving on. And, panel providers today are able to target very specific groups of consumers who have been vetted for the quality of their responses - leaving no excuse for brands to settle for poor-quality data.
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Methods used for quantitative data collection 

So how does one go about researching a large, high-quality, representative sample? Below are five main quantitative data collection methods.


1. Online Surveys

Surveys are a common and effective way of collecting data from a large number of people. They tend to be made up of closed-ended questions so that responses across the sample are comparable; however, a small number of open-ended questions can be included as well (i.e. questions that require a written response rather than a selection of answers in a close-ended list). Open-ended questions are helpful to gather actual language used by respondents on a certain issue or to collect feedback on a view that might not be shown in a set list of responses).


Online surveys are quick and easy to send out, either by email or text. They can also appear in pop-ups on websites or via a link embedded in social media. From the participant’s point of view, online surveys are convenient to complete and submit, using whichever device they prefer (mobile phone, tablet, or computer). Anonymity is also a plus point: online survey software ensures respondents’ identities are kept confidential.

2. Offline Surveys

While online surveys are by far the most common way to collect quantitative data in today’s modern age, there are still some harder-to-reach respondents where other mediums can be beneficial; for example, those who aren’t tech-savvy or who don’t have a stable internet connection.

Postal questionnaires are sent out to a sample population and asked to return the questionnaire by mail. This process is more time-consuming than an online survey, and also runs the risk of a high budget if the response rate is lower than expected. As with online surveys, anonymity is protected, assuming the mail is not intercepted or lost.

Telephone surveys, as they sound, involve phoning a participant and asking quantitative questions orally. These responses are recorded in the same way as online surveys or postal questionnaires, with responses still interpreted on an aggregated, numeric level.

3. Interviews

Interviews are another popular way of researching or polling a population. They can be thought of as a survey but in a verbal, in-person, or virtual face-to-face format. The online format of interviews is becoming more popular nowadays, as it is cheaper and logistically easier to organize than face-to-face interviews, yet still allows the interviewer to see the respondent.

Like a phone survey, an interviewer runs through a survey with the respondent, asking mainly closed-ended questions (yes/no, multiple choice questions, or questions with rating scales that ask how strongly the respondent agrees with statements). The advantage of structured interviews is that the interviewer can pace the survey, making sure the respondent gives enough consideration to each question. It also adds a human touch, which can be more engaging for some respondents. On the other hand, for more sensitive issues, respondents may feel happier completing surveys online for a greater sense of anonymity - so it all depends on your research questions and the survey topic.

4. Observation

Observation is a technique that focuses on recording the number or types of people who do a certain action - such as choosing a specific product from a grocery shelf, speaking to a company representative at an event, or how many people pass through a certain area within a given timeframe. Observation studies are generally structured, with the observer asked to note down behavior using set parameters. Structured observation means that the observer has to home in on very specific behaviors, which can be quite nuanced. This requires the observer to use his/her own judgment about what type of behavior is being exhibited (e.g. reading labels on products before selecting them; considering different items before making the final choice; making a selection based on price).

Observation studies in quantitative research are similar in nature to a qualitative ethnographic study (in which a researcher also observes consumers in their natural habitats), yet observation studies for quant research remain focused on the numbers - how many people do an action, how much of a product consumer pick up, etc.

5. Review existing documents

The final method of data collection for quantitative research is known as secondary research: reviewing existing research to see how it can contribute to understanding a new issue in question. This is in contrast to primary research, which is research that is specially commissioned and carried out for a research project (into which our first four methods above might fall).


There are numerous documents that can be analyzed to support primary data, or used as an end in themselves. Secondary data collection can include reviewing public records, government research, company databases, existing reports, paid-for research publications, magazines, journals, case studies, websites, books, and more.


Aside from using secondary research alone, document review can also be used in anticipation of primary research, to understand which knowledge gaps need to be filled and to nail down the issues that might be important to explore in a primary research study.
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Quantitative research typically needs to undergo statistical analysis for it to be useful and actionable to any business. It is therefore crucial that the method of data collection, sample size, and sample criteria are considered in light of the research questions asked.

quantilope’s online platform is ideal for quantitative research studies. The online format means a large sample can be reached easily and quickly through connected respondent panels that effectively reach the desired target audience. Response rates are high, as respondents can take their survey from anywhere, using any device with internet access.

Surveys are easy to build with quantilope’s online survey builder. Simply choose questions to include from pre-designed survey templates or build your own questions using the platform’s drag & drop functionality (of which both options are fully customizable). Once the survey is live, findings update in real-time so that brands can get an idea of consumer attitudes long before the survey is complete. In addition to basic usage and attitude questions, quantilope’s suite of advanced research methodologies provides an AI-driven approach to many types of research questions. These range from exploring the features of products that drive purchase through a Key Driver Analysis, compiling the ideal portfolio of products using a TURF, or identifying the optimal price point for a product or service using a Price Sensitivity Meter (PSM).

Depending on the type of data sought, it might be worth considering a mixed-method approach, including both qual and quant in a single research study. Alongside quantitative online surveys, quantilope’s video research solution - inColor, offers qualitative research in the form of videoed responses to survey questions. inColor’s qualitative data analysis includes an AI-drive read on respondent sentiment, keyword trends, and facial expressions.

To find out more about how quantilope can help with any aspect of your research design and to start conducting high-quality, quantitative research, get in touch below:

Get in touch to learn more about quantitative research studies!

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