Reading: Primary Marketing Research Methods

Choosing the Right Primary Research Method

When secondary research cannot fully answer a marketing question, organizations often turn to primary research—the collection of new data directly from consumers or other stakeholders. Primary research is especially useful when businesses need insights that are specific to their products, services, or markets.

Primary research takes two main forms: exploratory and conclusive. Exploratory research is open-ended, aimed at uncovering ideas or themes. It often uses methods such as focus groups, in-depth interviews, or ethnographic observation. Conclusive research, on the other hand, is more structured and designed to test specific hypotheses through surveys, experiments, or field tests.

Quantitative vs. Qualitative Research

Qualitative research explores ideas, perceptions, and behaviours in-depth with a relatively small number of research participants. It aims to answer questions with more complex, open-ended responses such as, “What does this mean to you…?” or “Why do you believe…?” or “How do you like to…?” Qualitative research doesn’t yield data that are easily tabulated and translated into tidy percentages. Instead, provides information that can help marketers understand the big picture of how customers perceive or experience something.

Qualitative research can also give an organization directional information. That is, it can help an organization tell whether it’s on the right track with its approach or solution to a problem. Qualitative research techniques tend to be loosely structured and less formal, since the topical exploration may head in very different directions depending on the person or group participating. These techniques can provide great insights to marketers, but because they involve relatively few participants, the results can be very subjective and idiosyncratic. The risk is in assuming what you learn from a handful of individuals pertains to your target audience as a whole.

In contrast, quantitative research collects information that can easily be counted, tabulated, and statistically analyzed. When organizations need to understand (or quantify) the exact percentage of people who believe or act in a certain way, quantitative research is necessary. Quantitative methods allow researchers to test and validate a hypothesis or what they believe is the best course of action. These methods collect enough data to provide statistically valid results, and managers use them to inform the choices they make.

Often marketing research projects start with qualitative research activities to get a more complete picture of an issue or problem and how customers/consumers are thinking about it. With a better understanding of the issue, they follow up with quantitative research that provides more specificity about what proportion of the population shares common preferences, beliefs, or behaviours. This information provides insights to help marketers refine their segmentation and targeting strategy, the marketing mix, or other considerations related to marketing effectiveness.

Qualitative Research Methods

In Canada today, qualitative research remains a cornerstone of marketing insights, especially when companies need to understand the context, emotions, and motivations behind consumer choices. While technology has expanded the toolkit, a few methods are especially common across industries:

• Focus Groups: Still the most widely used method, focus groups allow brands to test new concepts and marketing campaigns in a moderated group setting. Canadian companies like Tim Hortons continue to rely on focus groups to gauge reaction to new products and promotions before national rollouts.^[1]

• In-Depth Interviews: One-on-one interviews are frequently used in financial services, healthcare, and technology, where trust and personal experience drive decisions. Firms such as Wealthsimple and major Canadian banks conduct interviews to better understand consumer concerns about fees, security, and digital adoption.^[2]

• Ethnographic Observation: While more resource-intensive, observational research is increasingly used by retailers and consumer goods companies. Canadian Tire and Loblaw have studied how consumers interact with products in real-life settings—homes, garages, or kitchens—to identify unmet needs and opportunities for product improvement.^[3]

• Online Communities & Digital Diaries: A fast-growing area, online qualitative platforms allow participants across Canada to share videos, photos, and written reflections about their experiences over days or weeks. Retailers like Lululemon use these communities to follow how customers integrate products into daily routines, informing both product design and brand positioning.^[4]

These methods have become standard in Canadian marketing research because they are adaptable, cost-effective, and produce insights that help organizations stay competitive in a fast-changing marketplace.

Quantitative Research Methods

In Canada, the most common quantitative marketing research methods are surveys, experimental research, and increasingly, big data analytics. These methods are often combined to give businesses, policymakers, and nonprofits deeper insights into consumer behaviour.

Survey Research

Survey research remains one of the most widely used tools for collecting primary data. Canadian firms across retail, finance, and public policy rely on surveys to capture consumer attitudes and behaviors. Surveys may be distributed through online platforms, mobile apps, email, telephone, or in-person intercepts at stores or events.

Effective surveys require clear, concise wording. Confusing questions produce invalid results, so survey design emphasizes straightforward language, appropriate question formats, and a logical flow. Researchers typically balance closed-ended questions (yes/no, multiple choice, scales, “select all that apply”) with occasional open-ended questions to capture deeper insights. Closed-ended questions are easier to analyze and less burdensome for respondents, while open-ended questions provide nuance but increase completion time.

In Canada, where internet penetration is high, online surveys are especially popular due to their low cost and speed. Many organizations use platforms like SurveyMonkey or Qualtrics, while Statistics Canada relies on online and telephone methods for major national surveys.^[5]  However, in regions with limited broadband access, telephone and in-person surveys remain important, particularly for reaching older populations or rural communities.

Survey length is a critical factor. Research shows that surveys longer than 15 minutes significantly reduce completion rates. Incentives—such as discounts, contest entries, or charitable donations—are commonly used in Canada to boost participation.

Canadian companies also publish survey results as part of their marketing strategies. For example, the Royal Bank of Canada (RBC) conducts annual surveys on homeownership, retirement readiness, and economic outlook. These surveys not only inform internal decision-making but also generate media coverage and position RBC as a thought leader in financial services.^[6]

Experimental Research

Experimental research involves testing variables to determine cause-and-effect relationships. The most common form in Canadian marketing is A/B testing, widely used in digital advertising, e-commerce, and email campaigns. For example, a retailer like Canadian Tire may test two different homepage layouts to see which drives more online sales.

Beyond digital, experiments are also used in product testing and service design. For instance, Canadian telecom providers have piloted new pricing bundles in select markets before rolling them out nationwide. Experimental designs allow marketers to isolate key factors influencing consumer behaviour and optimize offerings accordingly.^[7]

Big Data & Analytics

A newer but increasingly central element of quantitative research in Canada is the use of big data analytics. Instead of relying solely on surveys or small-scale experiments, many organizations now analyze massive datasets generated by digital transactions, loyalty programs, mobile apps, and social media.

For example, Loblaw Companies Ltd. uses data from its PC Optimum loyalty program to identify shopping patterns across millions of households, tailoring promotions and store layouts accordingly.^[8]  Similarly, Canadian banks and insurers analyze transaction data to detect trends in savings, spending, and investment, which informs both product development and targeted marketing campaigns.

Big data allows for near real-time insights and predictive modelling, but it also raises privacy and ethical considerations, particularly under Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA). Organizations must ensure data use is transparent, secure, and respectful of consumer consent.^[9]

Research Contact Methods: Offline vs. Online

As researchers select their methods, they must also choose how to contact respondents. In Canada today:

Historically, Canadian researchers relied on mail and telephone. Today, however, digital methods dominate, with online panels, mobile surveys, and social media polls providing efficient and cost-effective data collection. Still, for certain populations—such as Indigenous communities in remote areas or seniors less active online—telephone or in-person methods remain essential for ensuring representative results.^[10]

Developing Research Instruments

Every marketing research method requires an instrument—the tool used for data collection. The three most common are questionnaires (for surveys), discussion guides (for in-depth interviews and focus groups), and mechanical data collection techniques that capture behavioural or observational data.

Designing Questionnaires

Effective questionnaires follow a few basic principles. Each question should be clear, concise, and unambiguous, so that respondents understand exactly what is being asked and how to answer. After drafting, it is wise to have others review the wording and flow. A good questionnaire should feel like a coherent story: logical, easy to follow, and engaging enough to encourage completion.

Questionnaires typically combine open-ended and closed-ended questions. Closed-ended questions include dichotomous (yes/no), multiple choice, or scaled items (e.g., “strongly agree” to “strongly disagree”). Open-ended questions allow respondents to provide more detailed, personal responses, though there is a risk that some may skip them. Sequencing matters: simple questions often appear first to build momentum, while demographic items are usually placed at the beginning or end. The overall flow should guide the respondent smoothly through the survey.

Designing Discussion Guides

Discussion guides for interviews or focus groups share many of the same principles as questionnaires. Questions should be clearly worded, logically sequenced, and designed to draw out meaningful dialogue. Because these qualitative methods explore attitudes and motivations, they rely more heavily on open-ended questions. Closed-ended items may be used sparingly to start a conversation or to confirm specific points.

Flexibility is crucial: interviewers and moderators should be able to probe deeper into interesting responses. In focus groups, guides should also include prompts that encourage participants to interact with one another, since peer discussion often reveals insights that might not surface in one-on-one settings. Timing must also be considered so that the most important issues are covered even if the discussion runs long.

Using Mechanical Instruments

Mechanical instruments are tools that collect behavioural or observational data while participants complete a task. In marketing, these often include digital tracking tools, eye-tracking equipment, biometric sensors, or user testing platforms. For example, website usability testing may record click paths, time on page, and eye movements to reveal how design influences user behaviour. Advertising researchers sometimes use biometric feedback (such as heart rate or skin response) to measure emotional reactions to an ad. These methods are frequently used alongside qualitative or quantitative approaches to provide a more complete view of consumer behaviour.

Sampling: Selecting Research Participants

Most research projects rely on sampling rather than surveying an entire population. A sample is a smaller group selected to represent the larger audience. The first question in designing a sample is: who exactly should participate? For a study on laundry detergent, should the research involve household members who purchase detergent, those who do the laundry, or retail managers who decide which brands to stock?

Sample size also matters. Qualitative studies such as interviews or focus groups may involve as few as 10–20 participants, while quantitative surveys often require hundreds or even thousands to ensure reliability. Researchers may recruit participants from customer records, purchase contact lists, or use pre-screened research panels to access specific demographic or behavioural groups.

Sampling procedures are either probability-based (each individual has a known chance of being selected, such as in a random sample) or non-probability-based (participants are chosen based on researcher judgment or convenience). The choice depends on the research objectives, resources, and the level of statistical confidence required.

Analyzing Primary Data

Once data are collected, researchers move to analysis and interpretation. Qualitative data are often summarized thematically, with participant quotes illustrating key insights. Quantitative data usually require statistical analysis, such as tabulations, correlations, or significance testing, to uncover meaningful patterns.

The challenge is not only to process the data but also to tell the story it reveals: what does the evidence say about the problem or opportunity, and how should organizations act on it? Framing insights in this way helps managers and marketers apply the findings effectively to strategy and decision-making.

Creation note: This content was updated with the assistance of ChatGPT, a language model developed by OpenAI, and was subsequently reviewed and edited by the author for clarity and accuracy.