Market Research for Non-Researchers: Tips, Tricks, and Tools

Every company wants consumer insights. Organizations use them to steer product development, marketing and communications strategies, UX design, competitive intelligence, pricing, and many other business-critical decisions. Direct consumer feedback is what enables companies to stay ahead without expensive trial and error. 

But what happens when your org doesn’t have a dedicated market research team, so the task of collecting insights falls upon… you? 

You’re aware there are agencies that handle this kind of thing, of course. But how do you vet an agency that will deliver the results you’re looking for? What do you do if its proposal will take far longer and cost much more than you have? How do you go about conducting research yourself? 

If you’re a non-research professional in need of consumer insights, this guide is for you. 

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First, understand the difference between qualitative and quantitative research

You can probably infer the difference between these, but it’s good to cover the basics because they make up the foundation of market research. 

‍Quantitative Research (often abbreviated to “quant”) is about the hard numbers. How many people prefer option A over option B? What percentage of the respondent pool tried the product and loved it or hated it? It gives you the what. 

Quant research is also, historically, the most practical for scale. Researchers default to this kind of survey to reach substantial respondent pools instead of arranging a high number of in-person interviews or focus groups. 

‍Qualitative research (often abbreviated to “qual”) gives you the why. This is where previously mentioned interviews and focus groups come in, as well as open-ended responses and video questionnaires. Qual research dives into why people feel the way they do — the language they use, the surprises, and the trade-offs — so you get deeper context about their actual thought processes. 

A ranking that says “Concept 2 won” is only half the story. Hearing a real customer explain their reasoning is what makes insight more actionable. The best studies capture both from the same participants. 

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Determine your research objectives and goals

Next, determine what you want to research. Not vague statements like “customer preferences” or “latest trends” — what kind of data do you need to guide a business decision, and what will you do with the results? 

Your objective will determine the type of study you run. Common ones include, but are certainly not limited to: 

‍Attitudes and Usage (A&U): How do consumers think about and behave within your category? 

‍Concept Testing: Will this product, idea, or creative piece resonate with audiences before you invest? You can also compare multiple stimuli to determine which is the most popular. 

‍Whitespace Analysis: What unmet needs exist in your category that you could own? 

‍Brand Lift: Did your message or creative move the needle? 

‍Shop Along: This study type involves capturing consumer sentiment in-store before point-of-sale; most other survey kinds take place after customers have already purchased something. 

‍Customer Segmentation: What kinds of distinct consumer groups shape your category? Can you influence new ones or breathe life into existing ones? 

‍UX Research: How do users interact with your digital product interfaces and where do they identify friction points? 

‍Tracking and Longitudinal: How do consumer preferences, attitudes, and behaviors change over time? 

Other study types include: 

• Occasion mapping
• Path-to-purchase
• Price sensitivity
• Retailer sell-in
• Line optimization
• Due diligence 

And more. So, be concrete about the decision your research will influence. If you can’t articulate it, you’re not ready for fielding (putting a study “out in the field” for respondents to complete) just yet. 

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Identify your audience 

Equally important as what you ask is who you ask. Define who belongs in your sample pool and who should be screened out. 

Getting this wrong could mean seemingly amazing data — until you realize it doesn’t apply to your actual customers. Think about demographics, behaviors, and usage patterns that matter to your question and build screening logic accordingly. 

3 ways to get research done

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The DIY method

This is where you design, field, and analyze a study yourself using off-the-shelf tools. It’s usually the most affordable route and is excellent for building internal capability. 

However, it puts the entire burden of methodological rigor and data analysis on your shoulders. 

A bit of guidance if you decide to go this route: 

‍Budget wisely. Your cost isn’t just the software subscription. Factor in how difficult your audience is to reach (which raises costs because you’ll need to spend a lot of time on recruiting participants or sourcing from multiple panel providers), how many respondents you’ll need, and — often underestimated — how long execution and analysis will take. 

‍Start with a research brief. Even solo, write one: your objectives, audience, hypotheses, and the business decisions you’ll make to keep your project focused. 

‍Write a solid questionnaire. This step is a given (it’s what surveys are composed of!), but avoid the temptation to make lengthy questionnaires because you want to collect as much data as possible. “Respondent fatigue” is real: participants might drop out if the effort involved isn’t worth the compensation. Keep your questionnaire tight and tied to your core research objective. 

Run the quantitative leg with a survey tool. There's no shortage of options; pick based on your use case and budget:

• Google Forms / Microsoft Forms — free, fast, perfect for simple internal surveys and small samples.
• SurveyMonkey — a well-rounded general-purpose platform with templates and built-in respondent panels.
• Typeform — conversational, one-question-at-a-time design that boosts completion.
• Jotform — flexible forms with strong integrations and payment collection.
• QuestionPro or Qualtrics — heavier platforms for complex logic, advanced analytics, and enterprise-grade studies.

Handle the qualitative leg separately. Not many, if any, DIY tools exist that allow you to capture both quant and qual in the same study, so you’ll have to find other solutions for this part. 

Organize online or in-person interviews or focus groups. This is usually the slowest, most manual part of the DIY route (recruiting, scheduling, moderating, and transcribing), but qualitative data is essential for enriching your quantitative research with context. 

Be cognizant of data quality. Bots abound on the internet, so verify that all of your participants are real people. Not just real, either — engaged, because some respondents will speed through a study to receive the monetary incentive and give you junk data. 

Analyze the data and look for patterns. Cross-tabulate, segment, and hunt for themes. This part is where non-researchers struggle the most because interpretation is a skill that comes with practice.

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The traditional vendor method 

If you’re not a researcher, there is, of course, the obvious choice: hiring an agency full of them. This way, you can lean on their expertise and trust them to execute and be accountable for the work. 

The process works like this: 

It starts with a discovery call. You’ll learn how the agency would approach your research objectives and they’ll learn about your business context. Note that there are multiple kinds of agencies, including: 

‍Full-service: Manages the entire project end to end, including design, fielding, analysis, and reporting. Full-service agencies are known for doing things manually, so they can be costly and take several weeks to several months to complete a study depending on its complexity. 

Field services: Handles participant recruitment and data collection, but leaves analysis to you.

The agency will then create a brief, questionnaire, field the study (you can pay for both quant and qual or only one of the two), analyze the results, and provide you with a final report you can present to your stakeholders or use to make your business decision. 

A few tips if you go this route: 

‍Vet the agency carefully. Look for thorough data-quality safeguards that eliminate the risk of bots and speeders, strong communication and service quality, and a solid reputation. Ask how they validate data and how they keep clients informed. 

‍Review the proposal and study design critically. This helps avoid a great deal of wasted spend: make sure the questionnaire actually gets to the root of your core business problem, not just the surface topic. A beautifully executed study aimed at the wrong target still fails. 

‍Plan ahead. Traditional timelines can stretch, though shorter than if you did everything yourself, depending on scope. Build buffer into your calendar. 

‍Don’t be afraid to question the report. Yes, researchers are experts, but you’re allowed to ask follow-up questions, to request new audience cuts, to examine the data from new lenses, and so on (note: the downside of this is that many final reports are static, delivered as PDFs, so receiving answers to further questions might take the agency additional time and they may even need to run a net-new study if necessary).  

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Hire an AI research partner 

Many agencies now leverage AI to deliver results faster than traditional timelines. This can be a viable option if you can’t afford to wait months for a report to arrive. The agency still handles every step of the process, but follow-up questions are easier to answer because the data doesn’t disappear afterward and the technology can better re-analyze it. 

The process works similarly to traditional vendors, but here are a few questions to ask while you’re vetting: 

‍How fast is fast, and for how much? One of the perks of hiring an agency that uses AI is that it can be much more affordable than the traditional route. So, compare pricing models, and double-check what timelines look like — it could be weeks, but in this case, it could be a matter of days. 

‍Does rigor come at the expense of speed? This is one of the most important questions to ask because AI is notorious for hallucinating or outputting junk that you have to waste your time reworking anyway. You’re not hiring an AI agency just for speed, you want the research to be just as rich, contextual, and insightful as a traditional vendor would produce. 

‍Can they do qual and quant together? This another key value prop: it’s rare that an agency can run both qual and quant in the same study. If they can, it’s an incredible opportunity to get responses from the same set of participants, deepening your insights while shortening timelines. 

Qualitative research, in this case, looks less like in-person interviews and more like video questions. You still get insight into tone, inflection, facial expressions, and other nuances that color the findings, but the AI can also analyze recurring themes across all responses, saving time watching them all and identifying patterns manually. 

‍What kind of final deliverable do you receive? Do you receive a static report, or something more evergreen? If the agency keeps data in a proprietary platform you can access whenever and wherever, then consumer insights become a living resource instead of a one-and-done PDF.

Does research context compound? It’s annoying if you have to launch every study like it’s the first one. Before signing a contract, verify if your business context will carry over to further studies and compound over time, getting you richer insights catered to your goals rather than starting over each time. 

‍How involved in the process can you be? Even though you’re not a researcher, it’s understandable you want as much transparency into the process as possible. Maybe you hope to learn more about research or simply want to supervise what the agency is doing. The right research partner won’t shut you out from the process and will keep you in the loop as much as you desire. 

Be sure to check out this list of the top AI consumer insights partners on the market. 

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How to choose your path 

‍Go DIY if you have (or are building) in-house research skills, a narrow and well-defined question, the time to learn the tools, and confidence to interpret the results. 

‍Go with a traditional agency if you need deep custom methodology and can absorb longer timelines and longer budgets. 

‍Go with an AI research partner if you need credible, decision-ready insights fast, without hiring a full research team or waiting months. For most non-researchers who own outcomes but not the craft, this tends to be the sweet spot: agency accountability with modern speed. 

If you want the best of all worlds, Knit isn’t just an AI research partner, but an AI-native research agency. We believe that being a non-researcher shouldn’t be a barrier to solid consumer insights: we’ll help you nail your objective, reach your target audience, match the method to the question, combine quant and qual in the same study, and help you go from scoping to story in as little as a week or less.

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