There are many things to consider when building your quantitative research – like how to define your target audience, how to select the best list of questions, how to ensure your survey format is easy to follow, all while keeping your overall research objectives, project timing, and budgetary constraints in mind. Read the list below to understand more about quantitative market research tips to consider when developing quantitative surveys.
It’s important to understand the difference between quantitative and qualitative research before embarking on your research. While qualitative research is exploratory in nature, quantitative research is confirmatory, methodical, numbers-based and consists mostly of close-ended questions. It is used in all phases of research and across all types of sectors, but is best used for predicting consumer behaviour based on a fixed stimulus (for example A/B testing), or for gauging interest in a specific product, service or feature.
Quantitative research is often used to validate findings from qualitative research or as a benchmark for further exploratory work. If the focus of your research is to explore customer emotions and motivations in a broader sense, or to hear from respondents in a less structured way where they have the ability to elaborate on a topic, a qualitative approach to the research may be more appropriate.
This may sound obvious, but it is important the people you survey are representative of the market you are hoping to target. Think carefully about how you structure the initial questions in your questionnaire (e.g. screener) and how you determine who qualifies to continue.
For example, if your client is a milk-alternatives manufacturer interested in understanding perceptions around some new product packaging, you’d want to address the questionnaire to those who currently purchase alternative milk products, or those would seriously consider the purchase of alternative milk products. You may wish to do some initial research on the demographics of current buyers of milk alternatives, so that you can use that to determine the demographic targets to include in your survey sample. For example, if you find that 50% of current buyers of alternative milk products are aged 18-34 years old then you may want to ensure that 18-34 year olds make up 50% of your sample.
In addition to your sample being representative of your target audience, when setting up your research it’s also important to consider how many people you need to survey in order for your findings to be reliable (replicable in the real-world). Online calculators are available to estimate the sample size needed to achieve a given level of confidence in the results, but a common rule-of-thumb for any kind of quantitative research is to try to collect a minimum of 50 instances of any given answer that is important to you; anything less than that is usually brought to the attention of the client/reader when presented as a finding.
Another crucial quantitative market research tip is structuring your quantitative research is understanding how each question helps address the research objectives. Unlike qualitative research which often evolves in structure and design while the research is being conducted (e.g. in the course of speaking to respondents), quantitative requires you understand exactly what kind of output you are seeking before you begin.
As a researcher, it can be hard to be selective with the questions that you ask, but keep in mind both time restrictions (a good rule-of-thumb here is that you can ask 20-30 simple questions in a 10-minute survey) and the possibility of respondent fatigue if you ask questions that are too repetitive in form or content.
A good way to ensure you’re being smart with what you include is to tie every question back to your list of objectives. The more meaningful and goal orientated your questions are, the fewer questions you’ll need. If you find there are questions you can’t tie back, then you may want to remove them from your survey.
You should also avoid the trap of being too ambitious in the number of objectives for a single survey – it’s advisable to limit each survey to answering a maximum of three questions that you have about your business. Including any more than three objectives may lead to confused findings, and increases the risk of fatigue among respondents.
This goes without saying, but it’s extremely important to keep your questions as simple as possible and word them so they are easily understood by your respondents. Generally speaking, be as concise as possible, avoid ambiguous and leading questions, but also include instructions on how a question should be interpreted and answered (even simple directions such as ‘select one answer’ and ‘select all that apply’ can make a real difference).
Question wording should use professional language, but any words or jargon that may not be easily recognisable by your audience should include an explanation as well. To test if your survey is simple and unambiguous, you might consider asking friends or family members to test it for you rather than colleagues.
Researchers will often underestimate or misquote the amount of time needed for quantitative research. This is often a result of wanting to please stakeholders by turning work around quickly. As a general guide, allow a minimum of one week in field for any quantitative research and at least two weeks for harder-to-reach audiences (particularly B2B). Allowing sufficient time makes it more likely that you will achieve the minimum number of response needed, and also allows the team to review the initial data from a ‘soft launch’ (which typically aims to collect responses from 10% of the final sample) and make any revisions to the survey if needed before proceeding.
It’s a good idea to visualise what your data output will look like once you’re done with the fieldwork. This will help understand the time needed for data analysis as well as any other data processing components necessary for final delivery. For example, if the survey data output is an Excel spreadsheet, which it often is, it will be important that the Excel file can be used to build survey tables. You will want to consider which software you’ll use to process the data tables and check compatibility with any vendors you’re using for this process.
The ways in which you plan to report on data findings will also help you understand what formats you’ll require with the data output. For example, if you’re hoping to include heat map images in your deliverable, check that your survey tool can generate and export this type of chart and if not, build in time to create them manually.
FieldworkHub frequently partners with clients on quantitative research projects. We offer survey development, hosting and management, data collection, plus analytics and reporting where needed. Get in touch with us today if you’re interested in exploring quantitative opportunities with us – we’d love to hear from you!