Quantitative market research questions to ask for actionable insights

There’s a big difference between asking “Why do you like our product?” and “On a scale of 1-10, how much do you like our product?” 

Both questions are valuable, but they reveal different kinds of truth.

Understanding your audience is not about guesswork or intuition. It’s about collecting concrete, reliable data. While qualitative research helps you uncover the why behind people’s choices, quantitative research questions tell you the what, how much and how often which gives you the data that make trends and patterns visible.

This approach is essential when you need to track changes in behavior over time, test new product ideas or understand how preferences differ between groups. Quantitative data reveals the scale and impact of sentiments which provides the evidence to make informed decisions that drive growth.

In this guide, we’ll explore the key types of quantitative market research survey questions, with quantitative question examples and practical tips to help you design surveys that deliver actionable insights.

What is a quantitative survey question?

Quantitative survey questions are designed to gather measurable, numerical data through descriptive research questions. Instead of open-ended questions, they use structured formats, like multiple-choice or ranking, for clear, easy-to-analyze results.

These types of questions help you uncover how many, how often or to what extent something happens. For example:

This is a quantitative question: It gives you hard data you can track and act on. Another classic example would be “On a scale of 1–10, how likely are you to recommend our brand to a friend?”

By contrast, qualitative survey questions aim to explore the why behind people’s opinions, using open text responses or interviews to uncover motivations and attitudes. Both methods complement each other, but quantitative data help teams make fast, evidence-led decisions.

💡Pro tip: Quantitative questions tell you the what, but qualitative ones reveal the why. For a deeper dive into how both methods work together, check out our guide on quantitative vs qualitative research and how to use each

Why use quantitative survey questions?

Quantitative survey questions help you gather evidence you can act on, to turn audience responses into measurable data that supports confident decision-making. 

Here’s why they’re so valuable:

• Objective and reliable: They remove guesswork by delivering precise, numerical data that supports quantitative analysis. This reduces the potential for personal bias in data interpretation and makes it easier to identify real trends.
• Easy to compare over time: Because responses are standardized, you can measure changes across different groups, campaigns or time periods with ease.
• Supports statistical analysis: The nature of quantitative data makes it ideal for statistical analyses like calculated averages, percentages and correlations. This helps you uncover deeper insights and patterns within your results.
• Scalable and efficient: Quantitative surveys can reach large, diverse audiences quickly. They provide statistically sound results (assuming your sample size and targeting are solid) without requiring weeks of manual analysis. 
• Fast, clear insights: Closed-ended questions are easy for respondents to answer. This boosts completion rates and helps you collect quantitative data faster.
• Useful for benchmarking: They make it simple to track responses and compare results against industry standards or historical data. It helps companies judge how they rank amongst competitors and plan accordingly.

Types of quantitative market research questions

When people think of quantitative research, they often picture numbers and percentages. But not all quantitative questions are the same. Each type of quantitative research question serves a different purpose in understanding your audience and uncovering actionable insights.

Below are the three main types of quantitative research questions, each helping you answer a different kind of “what,” “how much,” or “why” at scale.

Descriptive quantitative research questions

These are your what, when and how many types of questions. They help you map out the lay of the land in your market and understand general patterns in consumer behavior. These descriptive survey questions provide clear baselines for behavior.

ℹ️ Example: “How often do you shop online in a month?” or “What is your preferred method of payment when shopping online?”

Because the answers are predefined, the data you collect can be measured and analyzed easily. That’s what separates descriptive quantitative questions from open-ended qualitative ones, such as “Describe what a day out shopping looks like for you.”

Comparative quantitative survey questions

Comparative questions measure differences or changes between groups, markets or time periods. They’re ideal for tracking shifts in customer behavior or comparing performance across campaigns or demographics.

ℹ️ Example: “How has your spending on online shopping changed since last year?”

These questions will help you uncover both the differences between groups or time periods, as well as where they overlap.

Relationship-based quantitative survey questions

This type of quantitative question  explores how two or more variables might be connected. Rather than asking about the relationship directly, they collect the kind of data that you can use to test for correlations or patterns at a later point.

ℹ️ For example, you might ask: “How old are you?” and “How often do you use mobile payments?”

Analyzing the responses together can reveal insights such as whether younger audiences are more likely to use mobile payments. This approach can also help you test or challenge your assumptions and show whether the relationships you expect between variables exist.

Common quantitative survey question formats

Beyond categories, quantitative survey questions also use different formats. Each has its own use case depending on the kind of data you want to capture. Below are the most common quantitative question formats and when to use each one.

Multiple-choice questions (single or multiple selection)

Respondents choose from a list of options, making this format ideal for capturing categorical data such as demographics or preferences. 

ℹ️ Example: “Which of the following social media platforms do you use most often?” They’re quick to answer and easy to analyze, making them one of the most common quantitative formats.

Yes/No questions

Perfect for filtering respondents into distinct groups. These binary answers work best when you need a clear division, such as “Have you purchased from us before?”

Rating scale questions

Rating scale questions ask respondents to rate satisfaction, likelihood or intensity on a numerical scale, typically 1–5 or 1–10. 

They’re useful for tracking sentiment over time or across touchpoints, such as comparing satisfaction after purchase versus after delivery. 

ℹ️ Example:“On a scale of 1 to 10, how would you rate our customer service?”

Likert scale questions

Likert scale questions invite respondents to express how strongly they agree or disagree with a statement. This format is best for measuring opinions, attitudes or perceptions. 

ℹ️ Example: “I find the new product interface intuitive: strongly agree, agree, neutral, disagree or strongly disagree.”

Ranking questions

These ask respondents to order options by preference to help you see what matters most to them. This format reveals the relative importance of different factors and highlights trade-offs in decision-making. 

ℹ️ Example: “Rank the following product features by importance: price, ease of use and customer support.”

Numeric input questions

Numeric input questions ask respondents to enter a specific number, providing exact data that’s easy to analyze. 

ℹ️ Example:“How much do you spend on streaming services per month?” 

Use this format when you need precise figures rather than ranges and always specify units, (like USD) to ensure consistency.

Semantic differential scales

These questions ask respondents to rate something between two opposite adjectives on a scale, such as “modern ↔ outdated” or “affordable ↔ expensive.” This format helps measure perceptions and attitudes to reveal how people perceive your brand, product or campaign.

Matrix questions

Matrix questions group related items in a table so respondents can rate each one using the same scale, often a Likert scale:

They’re useful for comparing attitudes or satisfaction levels across multiple variables, such as product features or service touchpoints. Keep them short to prevent fatigue and ensure they display clearly on mobile devices.

Summary: Common quantitative survey question formats

Question format	Best suited for	Example
Multiple-choice (single or multiple selection)	Descriptive	“Which of the following payment methods do you use when shopping online?”
Yes/No	Descriptive	“Do you own a smartwatch?”
Numeric input	Descriptive	“How many times did you order groceries online last month?”
Rating scale (e.g., 1–10)	Comparative	“On a scale of 1–10, how has your satisfaction with online shopping changed compared to last year?”
Ranking	Comparative	“Rank the following factors in order of importance when choosing an online retailer: price, delivery speed, product variety.”
Likert scale	Relationship-based (can also serve comparative)	“I am more likely to use mobile payments if discounts are offered (strongly agree to strongly disagree).”
Semantic differential	Relationship-based	“Rate our app experience on the following scale: frustrating ↔ enjoyable.”
Matrix questions	Relationship-based (and comparative if repeated)	“Please rate the following features of our app on ease of use, reliability and value for money.”

A quick note on reducing bias in quantitative surveys

Before we jump into the examples of quantitative survey questions, let’s quickly chat about survey bias. Remember, the way you frame questions matters. Keep these tips in mind:

• Stay neutral: Use clear, balanced language that doesn’t suggest a particular answer
• Be specific: Avoid vague wording that can confuse respondents or skew results.
• Watch your question order: Early questions can influence how people answer later ones.
• Test before launch: Run your survey with a small group first to catch any bias or confusing phrasing.

Doing this helps ensure your data is accurate, reliable and ready to drive confident decisions.

💡Pro-tip: Want to know more? For a deeper dive, see our guide to the types of survey questions and when to use them.

36 Quantitative research questions and examples

If you want to make a quantitative survey that hits the spot, don’t just ask generic questions. We’re here with some examples that you can adapt to make your research a success.

Descriptive market research questions

With a descriptive quantitative research question, you can quickly get the most important info for your respondents on anything ranging from buying frequency to satisfaction levels.

How often do you use our product or service? (Multiple-choice)

This question reveals how frequently customers use your product or service, indicating how much they rely on it. Understanding these usage patterns can guide inventory planning, marketing strategy and resource allocation.

What is your preferred method of communication with a brand (email, social media, phone, etc.)? (Multiple-choice)

Uncover which communication channels your audience prefers. With these insights, you can tailor your customer service and marketing outreach to meet people where they already are.

How much do you typically spend on [product category] per month? (Numeric input)

This question provides an average spending figure within a product category. Knowing this helps with pricing strategies and identifying the most valuable customer segments for your business.

At what time of day do you usually shop online? (Multiple-choice)

Tracking when customers are most active uncovers behavioral patterns that can guide promotional timing. Use this insight to optimize email sends, ad scheduling or flash sales.

Where do you typically hear about new products or services (social media, word of mouth, online ads, etc.)? (Multiple-choice)

This question reveals the most effective channels for product discovery. You can use it to guide where to allocate advertising spend for maximum impact.

How many times have you recommended [product/service] to someone in the past month? (Numeric input)

Referral frequency can reveal satisfaction and brand advocacy potential. It measures the likelihood (not effectiveness!) of word-of-mouth referrals. Tracking this helps you measure organic growth and identify your most enthusiastic promoters.

What is your main reason for choosing [product/service] over competitors? (Multiple-choice with predefined options)

This uncovers your unique selling points from the customer’s perspective. The insights can guide your messaging to emphasize what customers value most about your brand.

On a scale of 1-10, how would you rate your last experience with [Brand X’s] customer service team? (Rating scale)

This provides a clear, numerical measure of satisfaction. Comparing these scores over time helps you track performance and pinpoint where service improvements are needed.

Which of our product features do you use the most? (Multiple-choice)

Feature usage data shows which elements of your product deliver the most value. Use this to inform product development and reinforce popular features in your marketing.

What factors most influence your decision to purchase a new [product/service]? (Multiple-choice or ranking)

Identifying the top drivers behind purchase decisions helps you create messages that resonate. You can use these insights to emphasize the attributes that motivate your audience to buy.

Comparative market research questions

Comparative research questions help you analyze and contrast different variables, like behavior across time periods or different product categories. They’re essential for spotting trends and understanding how preferences evolve.

If you want to analyze and compare different variables, these questions can help

How much do you spend on online shopping now compared to last year? (Numeric input)

This question tracks changes in consumer spending habits over time. It helps identify shifts in behavior that can guide forecasting, pricing and long-term planning. Pairing this with qualitative data can reveal the reasons behind those changes.

Are you more likely to purchase products in-store or online? (Multiple-choice)

Comparing purchase channels shows where customers prefer to shop. These insights help you optimize omnichannel strategies and guide resource allocation for digital and physical stores.

How has your preference for sustainable products changed in the past year? (Multiple-choice)

Tracking how sustainability preferences shift highlights evolving consumer values. Use this data to refine product development, adjust messaging and show alignment with audience priorities.

For your last purchase, which did you consider more important: price or brand reputation? (Multiple-choice)

This comparison clarifies which factor matters more to your customers at the moment of purchase. The findings can shape pricing strategies and influence promotional positioning.

How appealing do you find this packaging on a scale of 1-10? (Rating scale)

A direct measure of packaging appeal reveals how design affects perception and purchase intent. Results can guide creative decisions, validate redesigns and ensure packaging supports brand recognition and desirability.

Relationship-based questions for quantitative research

In quantitative research, especially when exploring relationship-based aspects, the key is not to cram multiple inquiries into one question but to ask them sequentially.

This approach allows for a clearer response to each individual question. During analysis, you can then correlate the responses to uncover relationships and quantify variables to identify patterns within your data.

For instance, instead of asking, “How often do you use our product and how satisfied are you with it?”, split this into two separate questions:

➡️ “How often do you use our product (daily, weekly, monthly)?”

➡️ “On a scale of 1-10, how satisfied are you with our product?”

By asking these questions separately, you ensure that respondents clearly focus on each aspect without being overwhelmed or confused by a dual-focused question. This approach yields more accurate and reliable data.

After the survey, you can analyze the results to see if there’s a correlation between usage frequency and satisfaction levels.

Here are some examples of combinations that can work well:

What is your age group? (Multiple-choice) and do you prefer shopping online or in-store? (Multiple-choice)

These paired questions correlate age with shopping preferences. The results show how different age demographics prefer to shop, helping you tailor marketing and sales strategies to each segment.

How long have you been using our products/services? (Multiple-choice) and how likely are you to recommend us to others (on a scale of 1-10)? (Rating scale)

This pairing explores how customer tenure influences brand loyalty. You can use these insights to help you understand how long-term customers perceive your brand and inform initiatives to improve retention and advocacy.

What is your approximate annual income? (Numeric input) and how often do you purchase premium products? (Multiple-choice)

These questions explore the relationship between income level and purchasing behavior. The findings can guide pricing and product strategies tailored to different income groups.

How often do you use social media for product discovery? (Multiple-choice) and how many online purchases do you make in a typical month? (Numeric input or multiple-choice)

These questions test whether social media engagement correlates with online purchasing behavior. The findings can confirm how effectively your social content drives conversions and where to focus ad spend.

How would you rate your satisfaction with our post-purchase customer service (scale of 1-10)? (Rating scale)and how likely are you to make another purchase (scale of 1-10)? (Rating scale)

Analyzing these responses together reveals how post-purchase service quality influences the likelihood of repeat purchases. This connection helps you understand whether your support experience is negatively or positively affecting repeat customer rates.

Brand tracking questions for quantitative insights

One thing you should definitely gather numerical data on, is your brand’s health. Just like your own health, stats and numbers can show you where to investigate further and ask qualitative research questions about. 

Learn if your brand stands strong through market trends and gain insights on whether your brand is growing in terms of awareness, as well as in which segments.

On a scale of 1-10, how familiar are you with our brand? (Rating scale)

This question measures brand awareness among your target audience, something that can be easily monitored using brand tracking tools to track changes in recognition and reach. Comparing results across demographics or over time shows how effectively your marketing is driving recognition and reach.

How likely are you to recommend our brand to a friend or colleague (scale of 1-10)? (Rating scale)

Often used as a Net Promoter Score (NPS) question, this gauges loyalty and advocacy. A high score signals strong satisfaction and organic growth potential through word-of-mouth, while a lower score highlights an opportunity to improve the customer experience.

From where have you heard about our brand? (e.g., social media, word of mouth, online advertising) (Multiple-choice)

Identifying where customers first encounter your brand reveals your most effective awareness channels. You can use this data to focus media spend on the platforms that deliver the greatest reach and engagement.

How often do you see or hear about our brand? (e.g., rarely, sometimes, often) (Multiple-choice)

This measures brand visibility and frequency of exposure. You can use this data to evaluate campaign reach, adjust media frequency and strengthen your brand presence across touchpoints.

Which of our brand values do you find most appealing? (list brand values for selection) (Multiple-choice or ranking)

Understanding which brand values resonate most helps you align messaging and creative strategy with what customers care about. This reinforces emotional connection and authenticity in your communications.

Quantitative consumer segmentation questions

Quantitative segmentation questions go beyond simple demographics like age and gender. After all, King Charles III is the same age as Lionel Richie, but would you say they’re very similar?

By asking consumer profiling questions across multiple variables such as income, region, education and household makeup, you can uncover real differences between your respondents.

Grouping these answers into ranges helps you build meaningful segments and tailor your marketing, product and customer experience strategies to specific audiences, rather than aiming at everyone.

This helps you connect each research topic back to your market research objectives and research goals.

What is your household income range? (Multiple-choice)

This question helps you understand the economic demographics of your customers. The results can inform pricing strategies and identify which income groups are most engaged with your brand.

Which geographical region do you live in? (Multiple-choice)

Geographic data reveals where your customers are concentrated and how preferences vary by location. These insights can guide regional marketing efforts and product distribution.

What is your highest level of education? (Multiple-choice)

Knowing your audience’s education level helps you understand their backgrounds and how they engage with information. This allows you to tailor communication style and content complexity to fit your audience.

What industry do you work in? (Multiple-choice)

Asking about professional background gives insight into your customers’ industries. This can help you design industry-specific campaigns, partnerships or product offerings.

How many people are in your household? (Numeric input or multiple-choice)

This question provides an idea of household size and composition. It’s useful for targeting products or campaigns toward individuals, couples or families.

Do you have children under 18? (Yes/No)

This question distinguishes families with younger dependents from other segments. The insight helps tailor messaging, products and promotions that appeal directly to families with children.

How to write your own quantitative market research questions

Now that you’ve seen what creating quantitative questions can look like, it’s time to create your own. They might seem broad at first, but with a little structure, you can design questions that deliver the precise insights you need for confident, data-driven decisions.

Identify the key variables you need to measure

Start by defining exactly what you want to learn. Is it customer satisfaction, buying behavior or brand awareness? Clear research objectives keep your survey focused and make analysis far easier later on

Choose the right survey distribution method

Think about how your questions will reach your audience. Will it be online via email, social media or a survey platform like Attest, or will it be over the phone or in person? Your method should align with where your target audience is most active and responsive.

Make sure your questions are crystal-clear and unequivocally unbiased

The way you phrase your questions can make or break your survey. Aim for clarity and simplicity — questions should be easy to understand and answer. Avoid leading or loaded questions that might sway a respondent’s answer. Remember: it’s a survey, not a sales pitch.

Know where to ask for more detailed information and qualitative data

Quantitative research questions only tell part of the story. If you see interesting trends in, say, purchase behavior or price sensitivity or a particular product gets a bad rating, dig a little deeper. Follow up important questions with qualitative research questions to analyze what’s going on behind the numbers.

How to collect insightful data from your quantitative surveys

To avoid ending up with a pile of numbers that don’t tell you much — or cost more than they should — it’s vital to choose a survey method that fits your goals and audience. You can partner with a full-service research agency to outsource data collection or handle it yourself using survey tools offered by UK market research companies.

Here’s a quick look at the pros and cons of each approach:

Telephone surveys:

• Pros: Ideal for reaching less tech-savvy demographics and enabling more personal interaction.
• Cons: Time-consuming, costly and often hindered by declining response rates. Best suited to qualitative follow-up, not large-scale quantitative work.

In-person surveys:

• Pros: Minimize confusion for respondents and allow for clarification in real time.
• Cons: Logistically demanding, expensive and impractical for fast or large-scale data collection.

Online survey software:

• Pros: Cost-effective, fast and scalable, with real-time analytics and access to a wide audience.
• Cons: Require careful question design to avoid fatigue or false responses from disengaged participants.

Quantitative research thrives when done with online surveys and it’s the go-to method for most international market research. 

Attest helps you get the most out of online surveys by giving you a versatile toolkit. From various types of questions to robust data analysis  tools — along with a dedicated research expert for when you need a little extra help — we set you up for measurable success.

Receive quantitative insights in weeks, not months

Speed and accuracy play a key role in market research, but that shouldn’t come at the cost of quality. With Attest, you can gather high-quality quantitative data at speed to help you make confident decisions based on reliable insights.

The right quantitative questions uncover more than numbers: They reveal patterns, priorities and opportunities for growth. Whether you’re exploring market trends, testing new ideas or tracking brand performance, Attest helps you design, launch and analyze surveys that deliver clarity fast.

Leading brands already rely on Attest to unlock insight at scale. Suntory America, for instance, used Attest to explore home drinking habits and found strong potential for tequila-based ready-to-drink beverages which highlighted  an opportunity for new product development. Meanwhile, Premier Foods strengthened retailer relationships by running consumer surveys that revealed category gaps and new shopper opportunities.

With Attest, you can do the same: Test ideas, validate assumptions and discover what your audience really thinks — all in a matter of hours.

Next, explore our guide to biased survey questions to make sure every data point you collect is as accurate and actionable as possible.