What’s the difference between quantitative vs qualitative research? Are you thinking about launching a new product or service, or developing new features for an existing one? Market research is the essential first move for brands, providing valuable information to guide the process and provide the highest likelihood of success.
There are two main types of research that marketers should engage in to effectively profile their customer base – quantitative and qualitative. You’ve probably heard the terms before, but do you know what they mean, or most importantly, when and where it’s best to use each type?
Read on to understand the two research methods, the type of data each produces and how you can use that to build and test concepts effectively.
What is qualitative research?
Qualitative research seeks more in-depth, free form answers from respondents either in person or via open-test responses.
This type of research is usually carried out with small groups and takes the form of in-person focus groups, telephone interviews or detailed surveys with free text responses. The method is used to gather anecdotal views and opinions, which inform generally rather than offer hard data.
What is quantitative research?
Quantitative research, as the name suggests, is primarily about numbers. It generally involves surveying a large group of people (usually at least several hundred and often thousands), using a structured questionnaire that contains predominantly closed-ended, or forced-choice, questions.
This is so that findings may be expressed numerically, enabling companies to garner statistics upon which plans and predictions can be made.
Why do quantitative research?
Quantitative research enables brands to profile a target audience by measuring what proportion has certain behaviours, behavioural intentions, attitudes, and knowledge.
In the planning stages for a new product or service, the quantitative method can help establish the importance of specific customer needs and validate the best product concept.
It can also be used as a deductive process to test pre-specified concepts and theories, such as, “working mothers are time-poor and find cooking a healthy meal for their family every evening a challenge.”
Quantitative research can help you answer questions such as “how many” and “how often” and is invaluable when putting together a business case for any new product or service, or proposing changes to existing ones.
The statistically robust results that can be derived from quantitative research are good for estimating the probability of success.
As well as helping you validate the marketplace and demand for your particular product or service, quant surveys can be used to shape your market proposition and gain understanding of how to market to your target audience.
You can garner data to determine things such as the best price point or places to advertise by looking at respondents’ price sensitivity or media usage.
But quantitative research is not just for the planning stage of your product or service; you can employ it further down the line to test customer satisfaction or assess the proportion of a target audience that recalls a message, for example.
Why do qualitative research?
Numerical (quantitative) research can measure behaviours, but it can’t necessarily tell you why customers behave as they do (or how to change that behaviour). That’s where qualitative research comes in; providing brands a more in-depth look into their customers’ psyches, with feedback right from the horse’s mouth. It helps to answer ‘why?’
It’s best used for more deeply exploring a topic or idea, when you want unprompted and unbound input rather than set answers to structured questions. Qualitative research is a primarily inductive process used to formulate theory rather than test existing ones. It helps brands to gain an insight into a target audience’s lifestyle, culture, preferences and motivations.
Like quantitative research, it can help identify customer needs. The results will be much more subjective but can be used to shape quantitative surveys that will validate the findings.
For example you may ask an open ended question ‘what is most important to you when it comes to dining out?,’ and then take the most common free-text answers, and validate them with a larger number of consumers using a quantitative survey, with fixed choice options based on the answers you got in your preliminary qual research.
You can also employ the two methods in the opposite direction – using quantitative research to gain statistics on behaviour or beliefs, and then qualitative to discover the reasons behind those behaviours or beliefs. It helps brands to better understand the context of the data.
Qualitative research can be very useful when it comes to developing brand image and marketing campaigns, since you can capture the language and imagery customers use to describe and relate to products and services in their own words.
Likewise, you can understand how people perceive a marketing message or communication piece and get their reactions to graphic identity or packaging designs.
Because qualitative research is conducted among smaller groups it’s ideal for exploring different market segments, as well as getting input from key informants who may be outside your target audience (such as industry experts).
The pros and cons of quantitative research
- Objectivity: quantitative research is numerical. Therefore, the results are clear and are harder to misinterpret. The survey can also be easily repeated and you can reliably track changes over time.
- Easy to analyse: because responses are numeric you can use statistical analysis to gain additional insight from the data.
- Quick: because you’re asking closed questions, it usually means data can be collected more quickly (because it’s easier for people to answer), while digital tools such as Attest can be used to easily analyse the results.
- Ability to generalise: when the survey involves a statistically valid random sample, you can generalise your findings beyond your participant group and make decisions with confidence.
- Big sample needed: quantitative research requires a large sample of the population to deliver reliable results. The larger the sample of people, the more statistically accurate the outputs will be.
- Limited answers: because results of quantitative research must be numeric, free text responses can not be permitted, meaning contextual detail may be missing.
- Potential for bias: those willing to respond to surveys may share characteristics that don’t apply to the audience as a whole, creating a potential bias in the study.
- Wording is crucial: to be confident in the results of quant surveys, you have to be confident you’re asking the right questions, in the right way, with the correct answer-options included.
The pros and cons of qualitative research
- More detailed: qualitative research offers a deeper understanding, with the ability to explore topics in more detail.
- Unprompted feedback: open-ended questions facilitate unprompted responses, vital for testing things where you don’t want to bias the outcome with prompts (such as for unprompted brand recall).
- Taps consumer creativity: generate ideas for improvements and/or extensions of a product, line, or brand.
- Smaller sample needed: you don’t need to recruit as many participants.
- Less measurable: with free text answers, it’s more difficult to quantify how many of your audience answer one way or another, and the data set is less accessible for statistical interrogation.
- Can’t generalise: qualitative research does not give statistically robust findings, and you therefore cannot generalise to your broader audience – although if followed up with quant research this is easy to remedy.
- Not repeatable: freeform interviewing makes it difficult to track changes over time.
How to do quantitative research
When you design a quantitative research survey all questions must be closed-ended, with pre-defined answers. These can take a variety of forms:
- Dichotomous – “yes/no”
- Multiple-choice – select one or more options from a list
- Rank order scaling – reorder a list by, for example, order of importance or preference
- Rating scale – select a rating such as “satisfied” or “extremely satisfied”
- Semantic differential scale – select a number on a scale (i.e. 1-10)
Because you want results to be easily measurable, you need to think carefully about the answer options to make them as inclusive as possible and thus minimise the amount of respondents who will select “other” (but do be sure to include “other” or “don’t know” as an option).
Avoid loaded questions, which make assumptions that might not be relevant to all being surveyed, such as, “When you buy hair gel, is packaging important to you?” with “yes/no” as answer options – it may be that they don’t purchase hair gel at all and would be unable to answer truthfully. This could lead to abandoned surveys or skewed results.
How to do qualitative research
Although qualitative research is less structured than quantitative, it’s still necessary to plan the topics that will be discussed and what information you aim to glean.
You should develop a set of clear and specific questions, otherwise the input will be too unmanageable. For example, asking a group of horse riders to tell you their biggest frustration in regards to their hobby is too broad a question.
Participants will struggle to answer and the researcher will struggle to draw meaningful data. Work instead on narrowing it down to, for example, their biggest frustrations with grooming or with feeding.
Design your questions so they are open-ended and cannot be answered with a simple “yes or no” – the point of qualitative research is obtain more in-depth understanding. Open-ended questions might start:
- Tell me
- What do you think about…
Generally, you’re aiming for more than a one-word answer; you want to probe the thoughts, beliefs and emotions of the participants. This will help you understand their behaviours.
Qualitative research is also useful for obtaining unprompted recall, so you might ask participants to think of a brand they’ve seen advertised on the TV recently and name it.
Qualitative research is not restricted to in-person interviews; it can be carried out via digital survey by using free-text responses.
How to analyse quantitative research data
Surveying tools should come with a range of options to help you work with the data, such as cross-tabbing and filters which enable you to observe answers by demographic combinations (variables). You can also export data to Excel where you can use features such as pivot tables and descriptive statistics.
There are three core types of analysis:
- Univariate – analyse by one variable, such as gender
- Bivariate – analyse by two variables, such as gender and age
- Multivariate – analyse by several variables, such as gender, age and education
To help you visualise the results, you can use data visualisation tools which take your data and put it into graphs and charts…or you could simply use Attest! Meanwhile, you can utilise Excel’s Prediction Calculator tool to create a scorecard that can be used to evaluate options or risk (probability).
How to analyse qualitative research data
Qualitative research results cannot be analysed in the same way as quantitative data or expressed as percentages; rather the output should be thought of as themes.
You can organise the results using coding. In coding, you assign a word, phrase, or number to each category, such as “pricing” or “barriers to entry”. You then go through all of your data in a systematic way and “code” ideas, concepts and themes as they fit categories.
Another way to get a feel for the overall themes is to use a basic text analysis tool, which allows you to find the most frequent phrases and frequencies of words. Or use more sophisticated software to mine text for themes, alongside analysing for sentiment and subjectivity.
To see keywords visually depicted, use a wordcloud generator – simply paste text or upload a document to generate a graphic which illustrates the frequency of words by giving them more or less prominence in the design.
Quantitative and qualitative research both have their place in market research and a mix of both should be carried out whenever you’re extending product lines or launching something new.
Both methods can work hand-in-hand; brands can use qualitative research for developing concepts and theories, and quantitative for testing pre-existing ones.
You can also use free-form qualitative research to guide the creation of more structured qualitative surveys. And following quantitative surveys, turn to qualitative to better understand the context of the responses!