quantitative research in business

98 Quantitative Research Questions & Examples

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As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list , so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

• Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
• Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

• What is the market share of our major competitors?
• What is the average purchase price of our competitors’ products?
• How often do our competitors release new products?
• What is the total number of customer reviews for our competitors’ products?
• What is the average rating of our competitors’ products?
• What is the average customer satisfaction score for our competitors?
• What is the average return rate of our competitors’ products?
• What is the average shipping time for our competitors’ products?
• What is the average price discount offered by our competitors?
• What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

‍♀️ Question: What is the market share of our major competitors?

Insight sought: Industry market share of leaders and key competitors.

Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

• Share of visits 

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

• Share of search 

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior , preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

• What is the average amount consumers spend on a certain product each month?
• What percentage of consumers are likely to purchase a product based on its price?
• How do the demographics of the target audience affect their purchasing behavior?
• What type of incentive is most likely to increase the likelihood of purchase?
• How does the store’s location impact product sales and turnover?
• What are the key drivers of product loyalty among consumers?
• What are the most commonly cited reasons for not buying a product?
• How does the availability of product information impact purchasing decisions?
• What is the average time consumers spend researching a product before buying it?
• How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

‍♀️ Question: What type of content performed best in the market this past month?

Insight sought: Establish high-performing campaigns and promotions in a market.

Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique , multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market. 

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

• To what extent is Brand Z associated with innovation?
• How do consumers rate the quality of Brand Z’s products and services?
• How has the awareness of Brand Z changed over the past 6 months?
• How does Brand Z compare to its competitors in terms of customer satisfaction?
• To what extent do consumers trust Brand Z?
• How likely are consumers to recommend Brand Z?
• What factors influence consumers’ purchase decisions when considering Brand Z?
• What is the average customer satisfaction score for equity?
• How does equity’s customer service compare to its competitors?
• How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview, I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

• How does changing the ad’s headline affect the number of people who click on the ad?
• How does varying the ad’s design affect its click-through rate?
• How does altering the ad’s call-to-action affect the number of conversions?
• How does adjusting the ad’s color scheme influence the number of people who view the ad?
• How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
• How does changing the ad’s placement on the page affect the amount of money spent on the ad?
• How does varying the ad’s targeting parameters affect the number of impressions?
• How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

• Assess the success of their social media campaigns
• Understand what content resonates with customers
• Spot potential areas for improvement
• How often are people talking about our brand on social media channels?
• How many times has our brand been mentioned in the past month?
• What are the most popular topics related to our brand on social media?
• What is the sentiment associated with our brand across social media channels?
• How do our competitors compare in terms of social media presence?
• What is the average response time for customer inquiries on social media?
• What percentage of followers are actively engaging with our brand?
• What are the most popular hashtags associated with our brand?
• What types of content generate the most engagement on social media?
• How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are YouTube, Facebook, LinkedIn, and Reddit – in that order.

In 30-seconds, I’ve discovered the following:

• YouTube is the most popular social network in my market.
• Facebook and LinkedIn are the second and third most popular channels.
• Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
• Bank of America is outperforming all key players significantly on LinkedIn.
• American Express has found a high referral opportunity on Reddit that others have been unable to match.

Power-up Your Market Research with Similarweb Today

Examples of quantitative research questions for online polls

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

• What is your annual income?
• In what age group do you fall?
• On average, how much do you spend on our products per month?
• How likely are you to recommend our products to others?
• How satisfied are you with our customer service?
• How likely are you to purchase our products in the future?
• On a scale of 1 to 10, how important is price when it comes to buying our products?
• How likely are you to use our products in the next six months?
• What other brands of products do you purchase?
• How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

• How much time do participants spend looking at each visual element of the product or ad?
• How does the order of presentation affect the impact of time spent looking at each visual element?
• How does the size of the visual elements affect the amount of time spent looking at them?
• What is the average time participants spend looking at the product or ad as a whole?
• What is the average number of fixations participants make when looking at the product or ad?
• Are there any visual elements that participants consistently ignore?
• How does the product’s design or advertising affect the average number of fixations?
• How do different types of participants (age, gender, etc.) interact with the product or ad differently?
• Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
• How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

• What is your age range?
• What is your annual household income?
• What is your preferred online shopping method?
• What is your occupation?
• What types of products do you typically purchase?
• Are you a frequent shopper?
• How often do you purchase products online?
• What is your typical budget for online purchases?
• What is your primary motivation for purchasing products online?
• What factors influence your decision to purchase a product online?
• What device do you use most often when shopping online?
• What type of product categories are you most interested in?
• Do you prefer to shop online for convenience or for a better price?
• What type of discounts or promotions do you look for when making online purchases?
• How do you prefer to receive notifications about product promotions or discounts?
• What type of payment methods do you prefer when shopping online?
• What methods do you use to compare different products and prices when shopping online?
• What type of customer service do you expect when shopping online?
• What type of product reviews do you consider when making online purchases?
• How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

• What is the average age of customers in each segment?
• How do spending habits vary across customer segments ?
• What is the average length of time customers spend in each segment?
• How does loyalty vary across customer segments?
• What is the average purchase size in each segment?
• What is the average frequency of purchases in each segment?
• What is the average customer lifetime value in each segment?
• How does customer satisfaction vary across customer segments?
• What is the average response rate to campaigns in each segment?
• How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

Added bonus: Similarweb API

If you need to crunch large volumes of data and already use tools like Tableau or PowerBI, you can seamlessly connect Similarweb via the API and pipe in the data. So for faster analysis of big data, you can leverage Similarweb data to use alongside the visualization tools you already know and love.

Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Research Intelligence to uncover facts that help inform your research and strengthen your position.

Take a look at:

• Our Market Research suite
• Our Benchmarking tools
• Our Audience Insights tool
• Our Company Research module
• Our Consumer Journey Tracker
• Our Competitive Analysis Tool

Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

by Liz March

Digital Research Specialist

Liz March has 15 years of experience in content creation. She enjoys the outdoors, F1, and reading, and is pursuing a BSc in Environmental Science.

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What is Quantitative Analysis?

Quantitative analysis techniques, applications of quantitative analysis in the business sector, the bottom line, related readings, quantitative analysis.

The collection and evaluation of measurable and verifiable financial data to understand the behavior and performance of a business

Quantitative analysis is the process of collecting and evaluating measurable and verifiable data such as revenues, market share, and wages in order to understand the behavior and performance of a business. In the past, business owners and company directors relied heavily on their experience and instinct when making decisions. However, with data technology, quantitative analysis is now considered a better approach to making informed decisions.

A quantitative analyst’s main task is to present a given hypothetical situation in terms of numerical values. Quantitative analysis helps in evaluating performance, assessing financial instruments, and making predictions. It encompasses three main techniques of measuring data: regression analysis , linear programming, and data mining.

1. Regression Analysis

Regression analysis is a common technique that is not only employed by business owners but also by statisticians and economists. It involves using statistical equations to predict or estimate the impact of one variable on another. For instance, regression analysis can determine how interest rates affect consumers’ behavior regarding asset investment. One other core application of regression analysis is establishing the effect of education and work experience on employees’ annual earnings.

In the business sector, owners can use regression analysis to determine the impact of advertising expenses on business profits. Using this approach, a business owner can establish a positive or negative correlation between two variables.

2. Linear Programming

Most companies occasionally encounter a shortage of resources such as facility space, production machinery , and labor. In such situations, company managers must find ways to allocate resources effectively. Linear programming is a quantitative method that determines how to achieve such an optimal solution. It is also used to determine how a company can make optimal profits and reduce its operating costs, subject to a given set of constraints, such as labor.

3. Data Mining

Data mining is a combination of computer programming skills and statistical methods. The popularity of data mining continues to grow in parallel with the increase in the quantity and size of available data sets. Data mining techniques are used to evaluate very large sets of data to find patterns or correlations concealed within them.

Business owners are often forced to make decisions under conditions of uncertainty. Luckily, quantitative techniques enable them to make the best estimates and thus minimize the risks associated with a particular decision. Ideally, quantitative models provide company owners with a better understanding of information to enable them to make the best possible decisions.

Project Management

One area where quantitative analysis is considered an indispensable tool is in project management . As mentioned earlier, quantitative methods are used to find the best ways of allocating resources, especially if these resources are scarce. Projects are then scheduled based on the availability of certain resources.

Production Planning

Quantitative analysis also helps individuals to make informed product-planning decisions. Let’s say a company finds it challenging to estimate the size and location of a new production facility. Quantitative analysis can be employed to assess different proposals for costs, timing, and location. With effective product planning and scheduling, companies will be more able to meet their customers’ needs while maximizing their profits.

Every business needs a proper marketing strategy. However, setting a budget for the marketing department can be tricky, especially if its objectives are not set. With the right quantitative method, marketers can easily set the required budget and allocate media purchases. The decisions can be based on data obtained from marketing campaigns.

The accounting department of a business also relies heavily on quantitative analysis. Accounting personnel uses different quantitative data and methods, such as the discounted cash flow model , to estimate the value of an investment. Products can also be evaluated based on the costs of producing them and the profits they generate.

Purchase and Inventory

One of the greatest challenges that businesses face is being able to predict the demand for a product or service. However, with quantitative techniques, companies can be guided on just how many materials they need to purchase, the level of inventory to maintain, and the costs they’re likely to incur when shipping and storing finished goods.

Quantitative analysis is the use of mathematical and statistical techniques to assess the performance of a business. Before the advent of quantitative analysis, many company directors based their decisions on experience and gut. Business owners can now use quantitative methods to predict trends, determine the allocation of resources, and manage projects.

Quantitative techniques are also used to evaluate investments. In such a way, organizations can determine the best assets to invest in and the best time to do so. Some of the quantitative analysis methods include regression analysis, linear programming, and data mining.

Thank you for reading CFI’s guide to quantitative analysis. To keep learning and advancing your career, the following CFI resources will be helpful:

• Correlation
• Consumer Surplus Formula
• Quantitative Trading
• Econometrics
• See all data science resources
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Quantitative Business Analysis Explained with Examples

Editorial Team

What is Quantitative Analysis?

Business analysis is a research field that can assist us in identifying problems and developing convincing solutions to them. A business analyst can help an organization develop effective and efficient solutions. However, creating leads to address the challenges is difficult, but it is doable by the business analyst alone. After all, business analysis is a collaborative effort, and using effective solutions can help a firm grow and flourish. Practical answers to business-related difficulties are critical to every company’s success.

Techniques, methods, software, strategic planning, policy formulation, organizational structure reform, and other enhancements to the firm or project are all part of the business analysis process. The basic aim of business analysis is to discover the best solution for a specific situation and business analysis provides us with insights into how to create a specific project. Applying or adopting them will provide us with a competitive advantage. Any company that wants to stay competitive in the market might benefit from business analysis.

Techniques of Quantitative Analysis 

 A quantitative analyst’s primary task is to express a given hypothetical situation in terms of numerical value. Quantitative analysis is beneficial for making forecasts, assessing financial products, and evaluating performance. Its three methods of data measurement are regression analysis, linear programming, and data mining.

1. Regression Analysis

Statistics professionals, economists, business owners, and other professionals frequently employ regression analysis. It entails applying statistical equations to make predictions or estimate the effects of one variable on another. For example, regression analysis can indicate how interest rates influence consumers’ asset investment decisions. Another application of regression analysis is determining the impact of education and job experience on employees’ annual wages.

Business owners can utilize regression analysis to determine how advertising costs affect their bottom line. Using this strategy, a business owner can decide whether two things have a positive or negative relationship.

2. Linear Programming

Most organizations experience intermittent shortages of resources such as office space, manufacturing equipment, and people. In such cases, corporate managers must design ways to use resources wisely. Linear programming is a quantitative approach that indicates how to arrive at such an optimum solution. It is used to examine how a corporation may maximize earnings while lowering operating expenses given a set of constraints, such as labor.

3. Data Mining 

Data mining combines statistical techniques with computer programming expertise. Data mining is becoming well-liked as the variety and number of data sets available expand. Very big data sets are analyzed using data mining techniques to look for hidden patterns or relationships.

Different Types of Business Analysis Methods

Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, Political, Economic, Social, Technological, Legal, and Environmental (PESTLE) analysis, HeptalysisTM, the 5 Whys method, and the Six Thinking Hats® method are a few of the business analysis techniques. All businesses should perform business analysis if they want to succeed. Such an analysis reveals the demands and issues of the firm and may also suggest the best solutions for achieving its objectives.

1. SWOT Analysis 

The most often used method of company analysis is the SWOT analysis. A company must be aware of its strengths and weaknesses or the areas where it operates best. Examples of strengths would be the best-performing departments or activities. Opportunities and threats are two ways that competitors are categorized in the marketplace to identify areas where the competition is struggling, which presents a business opportunity, as well as areas where the competitor is succeeding, which poses a threat to the company using this method of strategic planning.

A technique for assessing the external environment in which a corporation operates is PESTLE analysis. This kind of analysis aids a company mainly in situating itself in the area. Additionally, it provides commercial solutions for adjusting product prices, modernizing technology infrastructure, and favorably influencing society.

3. Heptalysis

Due to its seven main areas of inquiry, HeptalysisTM is possibly the most in-depth form of business analysis. These include market prospects, goods or services, financial considerations, plans for implementation, human resources, prospective returns on investment, and margin of safety. Especially during the early stages of development, a business analyst can identify the most crucial elements of launching and maintaining a corporation using this method. Because it encompasses all primary business operations, this type of analysis is also essential for developing policies.

4. The 5 Whys Method

The 5 Whys Method is excellent for identifying the root causes of company issues and promoting organizational transformation. It starts by outlining the problems faced by the company, followed by a “why” and a subsequent “why” it is frequently perceived as a straightforward strategy. Despite how simple it may seem, it demands participants to delve deeper and consider the underlying reasons for the issues within the company. The fundamental cause found using the 5 Whys method is typically unexpected and quite precise.

5. Six Thinking Hats

The Six Thinking Hats approach to business analysis is the best for brainstorming sessions that can produce good answers for strategic planning. In this scenario, several organization members are picked and assigned positions or ways of thinking that are color coded. These include black for pessimistic perspectives, yellow for optimistic views, green for creative views, and white for logical or factual thinking. When deciding on manufacturing or marketing solutions, this strategy works incredibly effectively for service- and product-oriented firms. 

Advantages of Business Analysis

The process of assessing the needs of an organization and providing realistic solutions to business-related challenges is known as business analysis. It entails developing new strategies or processes to create a suitable plan and applying them to the firm. Business analysis is a vital tool for providing insights and real cost-cutting measures. New marketing methods and commercial difficulties have emerged as a result of technological innovation. Business analysis can help us better grasp what we’re up against, giving us an advantage and a better likelihood of success in the market. Business analysis can help an organization’s market presence, resulting in increased sales and ROI. In the financial market, it is critical to establish a solid foundation and business structure. So, how can we put practical business analysis to use? This is where business analysts come in.

Business analysts are critical members of any organization. They can have a substantial impact on an organization’s budget. Using reasonable business analysis can provide us with the following advantages:

1. Increased Return on Investment(ROI)

The most important goal of any firm in the market today is to have a consistent ROI. Using business analysis can dramatically reduce costs, allowing for greater profit. Implementing efficient techniques and solutions to work-related difficulties can result in significant cost savings. ROI assesses the effectiveness of the solution we implemented and analyzes its investment. Practical solutions are required for any organization to favorably influence the firm.

2. Reduce expenses

Using business analysis can help an organization save money on numerous initiatives or operations. Business analysts can save money by developing and applying cost-effective methodologies, strategies, and approaches. Reduced corporate costs are an important component that can aid a firm’s development and growth. Business analysts and the team can devise creative solutions to recurring challenges that are both affordable and practical.

3. Increased Success Rate

Any organization’s empirical pillar is business analysis. This can increase the project’s success percentage by utilizing effective and cost-effective remedies to any challenges that may develop. A robust team structure and business analyst(s) can also save a project from failure. We can also use business analysis to keep track of projects and make changes more quickly that can assist us in meeting the project’s objectives and aims.

4. Collaboration in an Effective Team

We lose a lot of money and time addressing a single issue, which causes project delays. Using business analysis can be advantageous to both the organization and its employees. It can enhance team collaboration, resulting in speedier project implementation and completion. This can also help to avoid mistakes and lessen the need for rework on a given project. Effective team collaboration allows project completion on time and within budget.

5. Expect Business Issues

Business analysis can provide us with insight that can assist us to envision the challenges that may develop. By developing a viable solution, we can prevent project rework by adopting the best processes and techniques. Problems are unavoidable in the marketing business. It is preferable to be prepared to predict and address future challenges.

6. Sales Increase

Increased sales is an important goal and ambition of any business. We can increase revenue by applying business analysis. How can business analysts develop marketing plans that use an efficient method of acquiring information about the needs and desires of the target audience? Furthermore, low-cost and efficient solutions can reduce costs, resulting in substantial sales.

7. Potential for improvement.

Every company isn’t perfect. Management will face issues from time to time. Using business analysis can show us where we can improve. We all know that owning a business is difficult therefore prospering oneself is essential. This can be very advantageous to both management and employees. This can also help to improve abilities and help the organization grow and thrive. In any particular market, having competent management and staff may build or ruin a corporation in the long run.

Quantitative Analysis Applications In The Business World

Let’s look at an illustration of how quantitative analysis might be used to navigate risky investing markets. One of the main concerns for those who invest in international markets is geopolitical risk. The risk became serious with the COVID-19 epidemic and the global inflationary surge. According to an online poll by Bloomberg, 70% of investors spend too much time researching and maximizing their risk exposure. Here’s where quality assurance technologies like Bloomberg Intelligence’s “Factor Evaluation Model” come into play. It takes into account variables such as valuation, volatility, dividend yield, etc. With the help of this model, investors can look up historical country-level geopolitical patterns and see how they affected the markets. Investors can examine the effects of the presidential election, the financial crisis in Greece, the 2011 earthquake in Japan, etc. A tool like this would assist investors in evaluating many viewpoints, comprehending the markets, and making sensible investments. It additionally improves their profits and helps diversify their portfolio by lowering risk.

How Are The Abilities Of Quantitative Analysis Used In The Workplace?

Quantitative analysis can be used to inform decision-making in all business domains. Data is more easily accessible as businesses develop to become more digitally focused. The amount of data that businesses access now is more substantial than ever before, whether through their website or social media. Businesses have access to a wide range of insights that influence choices across all departments when they use this data efficiently to analyze trends, anticipate future revenue, and plan marketing initiatives. Business leaders frequently have to make judgments in an uncertain environment. They can produce the most accurate estimations thanks to quantitative methodologies, which help to reduce the risks involved. To help business owners understand information better and make the best decisions possible, quantitative models are ideal. Here are a few examples of how companies can employ quantitative analysis:

1 .   Project Administration 

One area where quantitative analysis is useful is project management. When resources are scarce, quantitative methodologies are used to establish the proper distribution of those resources, as previously stated. Then, based on the availability of specific resources, projects are scheduled. To determine the allocation of resources effectively quantitative methods can be used. Project managers may schedule and plan projects for the best outcomes by identifying the resources needed for specific activities and the resources available at certain stages of a project.

2. Manufacturing Planning

Individuals can use quantitative analysis to make smart decisions about product planning. Consider a situation where a business finds it difficult to predict the size and location of a new production facility. A quantitative analysis can be used to compare various costs, timing, and location proposals. Companies will be better equipped to meet their consumers’ needs while maximizing their revenues with smart product planning and scheduling. Several factors need to be taken into account when planning production volumes. Businesses must consider choices including updating or extending existing facilities, constructing additional manufacturing facilities, or outsourcing production when consumer demand exceeds production capacity. Decisions based on cost, risk, and timing can be made using quantitative analysis techniques to produce the greatest results for the business.

3. Marketing

Every company needs a sound marketing plan. Setting a budget for the marketing division can be challenging if its goals are not defined. Marketers can calculate the necessary budget and allocate media purchases with ease if they use the appropriate quantitative strategy. Data gathered from marketing activities may be used to inform the decisions. Marketers employ quantitative analysis to allocate resources, and marketing teams use campaign data analysis to calculate the return on investment for their projects. They can then utilize this knowledge to change their marketing strategy and estimate future campaign outcomes. To better understand their audience marketing teams frequently mix quantitative methodologies with qualitative analysis through focus groups or open-ended questionnaires. Marketing professionals may design more successful campaigns by having a better grasp of consumer behavior.

Financial reporting is a significant area in which quantitative analysis is used. Analysts strive to minimize expenses, maximize income, and ultimately boost profits while examining balance sheets. Businesses can utilize data analysis to plan, forecast, and carry out activities to meet financial objectives because financial data is frequently given on a monthly, quarterly, and annual basis. Pricing selections are one specific area where quantitative research can significantly impact a company’s profitability. To maximize revenues analysts can predict and assess how consumers will respond to price adjustments. A company’s accounting division also makes extensive use of quantitative analysis. Accounting professionals evaluate an investment’s value using quantitative data and techniques, including the discounted cash flow model. Products can also be judged according to their profitability and production costs.

5. Stock and Purchase

One of the most challenging difficulties companies confront is predicting demand for a good or service. Using quantitative approaches businesses can be advised on how many resources to purchase, how much inventory to have on hand, and how much it will cost to ship and store finished things. For businesses, being able to predict consumer demand is very advantageous. You can ensure you have enough inventory on hand at the appropriate moment to meet demand if you can forecast potential future sales. Businesses can predict the volume of stock they need to buy, the amount of inventory required to meet demand, and how much this will cost to buy, transport, and store by using quantitative analysis to uncover historical trends and growth levels. Being able to pinpoint these expenses helps with budgeting as well

Utilizing mathematical and statistical methods to evaluate a company’s performance is known as quantitative analysis. Before the development of quantitative analysis, many corporate directors relied on their intuition and expertise to make choices. Today business executives can utilize quantitative techniques to forecast trends, choose how to allocate resources, and oversee initiatives. Investment evaluation also uses quantitative methods. Organizations can choose the best assets to invest in and the ideal moment to do so in this fashion. Data mining, linear programming, and regression analysis are a few quantitative analytical techniques.

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Home Market Research

Quantitative Research: What It Is, Practices & Methods

Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It’s used in various fields, including the natural and social sciences. Quantitative data analysis employs statistical techniques for processing and interpreting numeric data.

Research designs in the quantitative realm outline how data will be collected and analyzed with methods like experiments and surveys. Qualitative methods complement quantitative research by focusing on non-numerical data, adding depth to understanding. Data collection methods can be qualitative or quantitative, depending on research goals. Researchers often use a combination of both approaches to gain a comprehensive understanding of phenomena.

What is Quantitative Research?

Quantitative research is a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects statistically significant information from existing and potential customers. It uses sampling methods and sending out online surveys , online polls , and questionnaires , for example.

One of the main characteristics of this type of research is that the results can be depicted in numerical form. After carefully collecting structured observations and understanding these numbers, it’s possible to predict the future of a product or service, establish causal relationships or Causal Research , and make changes accordingly. Quantitative research primarily centers on the analysis of numerical data and utilizes inferential statistics to derive conclusions that can be extrapolated to the broader population.

An example of a quantitative research study is the survey conducted to understand how long a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey can be administered to ask questions like how long a doctor takes to see a patient, how often a patient walks into a hospital, and other such questions, which are dependent variables in the research. This kind of research method is often employed in the social sciences, and it involves using mathematical frameworks and theories to effectively present data, ensuring that the results are logical, statistically sound, and unbiased.

Data collection in quantitative research uses a structured method and is typically conducted on larger samples representing the entire population. Researchers use quantitative methods to collect numerical data, which is then subjected to statistical analysis to determine statistically significant findings. This approach is valuable in both experimental research and social research. It helps in making informed decisions and drawing reliable conclusions based on quantitative data.

Quantitative Research Characteristics

Quantitative research has several unique characteristics that make it well-suited for specific projects. Let’s explore the most crucial of these characteristics so that you can consider them when planning your next research project:

• Structured tools: Quantitative research relies on structured tools such as surveys, polls, or questionnaires to gather quantitative data . Using such structured methods helps collect in-depth and actionable numerical data from the survey respondents, making it easier to perform data analysis.
• Sample size: Quantitative research is conducted on a significant sample size  representing the target market . Appropriate Survey Sampling methods, a fundamental aspect of quantitative research methods, must be employed when deriving the sample to fortify the research objective and ensure the reliability of the results.
• Close-ended questions: Closed-ended questions , specifically designed to align with the research objectives, are a cornerstone of quantitative research. These questions facilitate the collection of quantitative data and are extensively used in data collection processes.
• Prior studies: Before collecting feedback from respondents, researchers often delve into previous studies related to the research topic. This preliminary research helps frame the study effectively and ensures the data collection process is well-informed.
• Quantitative data: Typically, quantitative data is represented using tables, charts, graphs, or other numerical forms. This visual representation aids in understanding the collected data and is essential for rigorous data analysis, a key component of quantitative research methods.
• Generalization of results: One of the strengths of quantitative research is its ability to generalize results to the entire population. It means that the findings derived from a sample can be extrapolated to make informed decisions and take appropriate actions for improvement based on numerical data analysis.

Quantitative Research Methods

Quantitative research methods are systematic approaches used to gather and analyze numerical data to understand and draw conclusions about a phenomenon or population. Here are the quantitative research methods:

• Primary quantitative research methods
• Secondary quantitative research methods

Primary Quantitative Research Methods

Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research design can be broken down into three further distinctive tracks and the process flow. They are:

A. Techniques and Types of Studies

There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:

01. Survey Research

Survey Research is fundamental for all quantitative outcome research methodologies and studies. Surveys are used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys , etc. Every small and big organization intends to understand what their customers think about their products and services, how well new features are faring in the market, and other such details.

By conducting survey research, an organization can ask multiple survey questions , collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response.

This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis . A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. 

Traditionally, survey research was conducted face-to-face or via phone calls. Still, with the progress made by online mediums such as email or social media, survey research has also spread to online mediums.There are two types of surveys , either of which can be chosen based on the time in hand and the kind of data required:

Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which are considered for research . Throughout the survey, this one variable will stay constant.

• Cross-sectional surveys are popular with retail, SMEs, and healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
• Multiple samples can be analyzed and compared using a cross-sectional survey research method.
• Multiple variables can be evaluated using this type of survey research.
• The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

Longitudinal surveys: Longitudinal surveys are also observational surveys , but unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.

• In cross-sectional surveys, the same variables were evaluated at a given time, and in longitudinal surveys, different variables can be analyzed at different intervals.
• Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend analysis , analyze customer satisfaction, or gain feedback on products/services.
• In situations where the sequence of events is highly essential, longitudinal surveys are used.
• Researchers say that when research subjects need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

02. Correlational Research

A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other, and what changes are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.

Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original setup. The impact of one of these variables on the other is observed, along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.

Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.

Example of Correlational Research Questions :

• The relationship between stress and depression.
• The equation between fame and money.
• The relation between activities in a third-grade class and its students.

03. Causal-comparative Research

This research method mainly depends on the factor of comparison. Also called quasi-experimental research , this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural setup. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.

Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis plan is used to present the outcome using this quantitative research method.

Example of Causal-Comparative Research Questions:

• The impact of drugs on a teenager. The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa.

04. Experimental Research

Also known as true experimentation, this research method relies on a theory. As the name suggests, experimental research is usually based on one or more theories. This theory has yet to be proven before and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences. Traditional research methods are more effective than modern techniques.

There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.

After establishing the statement, efforts are made to understand whether it is valid or invalid. This quantitative research method is mainly used in natural or social sciences as various statements must be proved right or wrong.

• Traditional research methods are more effective than modern techniques.
• Systematic teaching schedules help children who struggle to cope with the course.
• It is a boon to have responsible nursing staff for ailing parents.

B. Data Collection Methodologies

The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection using surveys and polls.

01. Data Collection Methodologies: Sampling Methods

There are two main sampling methods for quantitative research: Probability and Non-probability sampling .

Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling . Participants of a sample are chosen by random selection processes. Each target audience member has an equal opportunity to be selected in the sample.

There are four main types of probability sampling:

• Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
• Stratified random sampling: In the stratified random sampling method , a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
• Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic segmentation and demographic segmentation parameters.
• Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.

Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the researcher’s involvement, not all the target population members have an equal probability of being selected to be a part of a sample.

There are five non-probability sampling models:

• Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved.
• Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.
• Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Members of various strata can then be chosen to be a part of the sample as per the researcher’s understanding.
• Snowball sampling: Snowball sampling is conducted with target audiences who are difficult to contact and get information. It is popular in cases where the target audience for analysis research is rare to put together.
• Judgmental sampling: Judgmental sampling is a non-probability sampling method where samples are created only based on the researcher’s experience and research skill .

02. Data collection methodologies: Using surveys & polls

Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.

Using surveys for primary quantitative research

A survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people it can reach depending on the research time and objective makes it one of the most important aspects of conducting quantitative research.

Fundamental levels of measurement – nominal, ordinal, interval, and ratio scales

Four measurement scales are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which no multiple-choice questions can be created. Hence, it is crucial to understand these measurement levels to develop a robust survey.

Use of different question types

To conduct quantitative research, close-ended questions must be used in a survey. They can be a mix of multiple question types, including multiple-choice questions like semantic differential scale questions , rating scale questions , etc.

Survey Distribution and Survey Data Collection

In the above, we have seen the process of building a survey along with the research design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:

• Email: Sending a survey via email is the most widely used and effective survey distribution method. This method’s response rate is high because the respondents know your brand. You can use the QuestionPro email management feature to send out and collect survey responses.
• Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample. Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher.
• Embed survey on a website: Embedding a survey on a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.
• Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand.
• QR code: QuestionPro QR codes store the URL for the survey. You can print/publish this code in magazines, signs, business cards, or on just about any object/medium.
• SMS survey: The SMS survey is a quick and time-effective way to collect a high number of responses.
• Offline Survey App: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline.

Survey example

An example of a survey is a short customer satisfaction (CSAT) survey that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.

Using polls for primary quantitative research

Polls are a method to collect feedback using close-ended questions from a sample. The most commonly used types of polls are election polls and exit polls . Both of these are used to collect data from a large sample size but using basic question types like multiple-choice questions.

C. Data Analysis Techniques

The third aspect of primary quantitative research design is data analysis . After collecting raw data, there must be an analysis of this data to derive statistical inferences from this research. It is important to relate the results to the research objective and establish the statistical relevance of the results.

Remember to consider aspects of research that were not considered for the data collection process and report the difference between what was planned vs. what was actually executed.

It is then required to select precise Statistical Analysis Methods , such as SWOT, Conjoint, Cross-tabulation, etc., to analyze the quantitative data.

• SWOT analysis: SWOT Analysis stands for the acronym of Strengths, Weaknesses, Opportunities, and Threat analysis. Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement.
• Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions. Trade-offs are involved in an individual’s daily activities, and these reflect their ability to decide from a complex list of product/service options.
• Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study.
• TURF Analysis: TURF Analysis , an acronym for Totally Unduplicated Reach and Frequency Analysis, is executed in situations where the reach of a favorable communication source is to be analyzed along with the frequency of this communication. It is used for understanding the potential of a target market.

Inferential statistics methods such as confidence interval, the margin of error, etc., can then be used to provide results.

Secondary Quantitative Research Methods

Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data. Existing data is summarized and collated to increase the overall effectiveness of the research.

This research method involves collecting quantitative data from existing data sources like the internet, government resources, libraries, research reports, etc. Secondary quantitative research helps to validate the data collected from primary quantitative research and aid in strengthening or proving, or disproving previously collected data.

The following are five popularly used secondary quantitative research methods:

• Data available on the internet: With the high penetration of the internet and mobile devices, it has become increasingly easy to conduct quantitative research using the internet. Information about most research topics is available online, and this aids in boosting the validity of primary quantitative data.
• Government and non-government sources: Secondary quantitative research can also be conducted with the help of government and non-government sources that deal with market research reports. This data is highly reliable and in-depth and hence, can be used to increase the validity of quantitative research design.
• Public libraries: Now a sparingly used method of conducting quantitative research, it is still a reliable source of information, though. Public libraries have copies of important research that was conducted earlier. They are a storehouse of valuable information and documents from which information can be extracted.
• Educational institutions: Educational institutions conduct in-depth research on multiple topics. And hence, the reports that they publish are an important source of validation in quantitative research.
• Commercial information sources: Local newspapers, journals, magazines, radio, and TV stations are great sources to obtain data for secondary quantitative research. These commercial information sources have in-depth, first-hand information on market research, demographic segmentation, and similar subjects.

Quantitative Research Examples

Some examples of quantitative research are:

• A customer satisfaction template can be used if any organization would like to conduct a customer satisfaction (CSAT) survey . Through this kind of survey, an organization can collect quantitative data and metrics on the goodwill of the brand or organization in the customer’s mind based on multiple parameters such as product quality, pricing, customer experience, etc. This data can be collected by asking a net promoter score (NPS) question , matrix table questions, etc. that provide data in the form of numbers that can be analyzed and worked upon.
• Another example of quantitative research is an organization that conducts an event, collecting feedback from attendees about the value they see from the event. By using an event survey , the organization can collect actionable feedback about the satisfaction levels of customers during various phases of the event such as the sales, pre and post-event, the likelihood of recommending the organization to their friends and colleagues, hotel preferences for the future events and other such questions.

What are the Advantages of Quantitative Research?

There are many advantages to quantitative research. Some of the major advantages of why researchers use this method in market research are:

Collect Reliable and Accurate Data:

Quantitative research is a powerful method for collecting reliable and accurate quantitative data. Since data is collected, analyzed, and presented in numbers, the results obtained are incredibly reliable and objective. Numbers do not lie and offer an honest and precise picture of the conducted research without discrepancies. In situations where a researcher aims to eliminate bias and predict potential conflicts, quantitative research is the method of choice.

Quick Data Collection:

Quantitative research involves studying a group of people representing a larger population. Researchers use a survey or another quantitative research method to efficiently gather information from these participants. It makes the process of analyzing the data and identifying patterns faster and more manageable through the use of statistical analysis. This advantage makes quantitative research an attractive option for projects with time constraints.

Wider Scope of Data Analysis:

Quantitative research, thanks to its utilization of statistical methods, offers an extensive range of data collection and analysis. Researchers can explore a broader spectrum of variables and relationships within the data. It can enable a more thorough comprehension of the subject under investigation. This expanded scope is precious when dealing with complex research questions that require in-depth numerical analysis.

Eliminate Bias:

One of the significant advantages of quantitative research is its ability to eliminate bias. This research method leaves no room for personal comments or the biasing of results, as the findings are presented in numerical form. This objectivity makes the results fair and reliable in most cases, reducing the potential for researcher bias or subjectivity.

In summary, quantitative research involves collecting, analyzing, and presenting quantitative data using statistical analysis. It offers numerous advantages, including:

• The collection of reliable and accurate data
• Quick data collection
• A broader scope of data analysis
• The elimination of bias

These advantages makes it a valuable approach in the field of research. When considering the benefits of quantitative research, it’s essential to recognize its strengths in contrast to qualitative methods and its role in collecting and analyzing numerical data for a more comprehensive understanding of research topics.

Best Practices to Conduct Quantitative Research

Here are some best practices for conducting quantitative research:

• Differentiate between quantitative and qualitative: Understand the difference between the two methodologies and apply the one that suits your needs best.
• Choose a suitable sample size: Ensure that you have a sample representative of your population and large enough to be statistically weighty.
• Keep your research goals clear and concise: Know your research goals before you begin data collection to ensure you collect the right amount and the right quantity of data.
• Keep the questions simple: Remember that you will be reaching out to a demographically wide audience. Pose simple questions for your respondents to understand easily.

Quantitative Research vs Qualitative Research

Quantitative research and qualitative research are two distinct approaches to conducting research, each with its own set of methods and objectives. Here’s a comparison of the two:

Quantitative Research

• Objective: The primary goal of quantitative research is to quantify and measure phenomena by collecting numerical data. It aims to test hypotheses, establish patterns, and generalize findings to a larger population.
• Data Collection: Quantitative research employs systematic and standardized approaches for data collection, including techniques like surveys, experiments, and observations that involve predefined variables. It is often collected from a large and representative sample.
• Data Analysis: Data is analyzed using statistical techniques, such as descriptive statistics, inferential statistics, and mathematical modeling. Researchers use statistical tests to draw conclusions and make generalizations based on numerical data.
• Sample Size: Quantitative research often involves larger sample sizes to ensure statistical significance and generalizability.
• Results: The results are typically presented in tables, charts, and statistical summaries, making them highly structured and objective.
• Generalizability: Researchers intentionally structure quantitative research to generate outcomes that can be helpful to a larger population, and they frequently seek to establish causative connections.
• Emphasis on Objectivity: Researchers aim to minimize bias and subjectivity, focusing on replicable and objective findings.

Qualitative Research

• Objective: Qualitative research seeks to gain a deeper understanding of the underlying motivations, behaviors, and experiences of individuals or groups. It explores the context and meaning of phenomena.
• Data Collection: Qualitative research employs adaptable and open-ended techniques for data collection, including methods like interviews, focus groups, observations, and content analysis. It allows participants to express their perspectives in their own words.
• Data Analysis: Data is analyzed through thematic analysis, content analysis, or grounded theory. Researchers focus on identifying patterns, themes, and insights in the data.
• Sample Size: Qualitative research typically involves smaller sample sizes due to the in-depth nature of data collection and analysis.
• Results: Findings are presented in narrative form, often in the participants’ own words. Results are subjective, context-dependent, and provide rich, detailed descriptions.
• Generalizability: Qualitative research does not aim for broad generalizability but focuses on in-depth exploration within a specific context. It provides a detailed understanding of a particular group or situation.
• Emphasis on Subjectivity: Researchers acknowledge the role of subjectivity and the researcher’s influence on the Research Process . Participant perspectives and experiences are central to the findings.

Researchers choose between quantitative and qualitative research methods based on their research objectives and the nature of the research question. Each approach has its advantages and drawbacks, and the decision between them hinges on the particular research objectives and the data needed to address research inquiries effectively.

Quantitative research is a structured way of collecting and analyzing data from various sources. Its purpose is to quantify the problem and understand its extent, seeking results that someone can project to a larger population.

Companies that use quantitative rather than qualitative research typically aim to measure magnitudes and seek objectively interpreted statistical results. So if you want to obtain quantitative data that helps you define the structured cause-and-effect relationship between the research problem and the factors, you should opt for this type of research.

At QuestionPro , we have various Best Data Collection Tools and features to conduct investigations of this type. You can create questionnaires and distribute them through our various methods. We also have sample services or various questions to guarantee the success of your study and the quality of the collected data.

Frequently Asked Questions (FAQs)

Quantitative research is a systematic and structured approach to studying phenomena that involves the collection of measurable data and the application of statistical, mathematical, or computational techniques for analysis.

Quantitative research is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, reliance on prior studies, data presented numerically, and the ability to generalize findings to the broader population.

The two main methods of quantitative research are Primary quantitative research methods, involving data collection directly from sources, and Secondary quantitative research methods, which utilize existing data for analysis.

1.Surveying to measure employee engagement with numerical rating scales. 2.Analyzing sales data to identify trends in product demand and market share. 4.Examining test scores to assess the impact of a new teaching method on student performance. 4.Using website analytics to track user behavior and conversion rates for an online store.

1.Differentiate between quantitative and qualitative approaches. 2.Choose a representative sample size. 3.Define clear research goals before data collection. 4.Use simple and easily understandable survey questions.

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Methodology

• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Quantitative Research – Methods, Types and Analysis

Table of Contents

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

• Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
• Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
• Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
• Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
• Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

• Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
• Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
• Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
• Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
• Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
• Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
• Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

• Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
• Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
• Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
• Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
• Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
• Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
• Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

• Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
• Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
• Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
• Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
• Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
• Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

• To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
• To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
• To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
• To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
• To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

• Description : To provide a detailed and accurate description of a particular phenomenon or population.
• Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
• Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
• Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

• Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
• Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
• Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
• Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
• Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
• Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

• Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
• Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
• Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
• Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
• Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
• Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Quantitative Research Examples for Business Success

Mary Kate Morrow

Straight forward quantitative research examples.

Two well known research methods are the quantitative and qualitative research methodologies. When deciding which research method to use the qualitative vs quantitative framework is commonplace. The two research methods have key differences ranging from data collection to research design techniques. Understanding the differences and similarities between quantitative research and qualitative research is crucial for data collection and data analysis optimization. Quantitative research focuses on quantifiable, numerical data collection and data analysis such as statistical analysis techniques. In fact, statistical, mathematical, and computational techniques are all commonly used on quantitative data collected. Alternatively, qualitative research focuses on non numerical data collection and analysis. Data qualitative research collects could originate from a market research focus group or an online survey administered. Quantitative research is undertaken for a wide variety of reasons. Common reasons range from testing a sample size from a large population to case studies for market research purposes. In fact, quantitative research is conventional in market research efforts. Data collection in quantitative market research can focus on current and potential customers. The research methods and research design quantitative and qualitative research uses oftentimes overlap. For example, case studies can use either quantitative research or qualitative research or mixed methods of both. Research questions for case studies employing qualitative research data collection would likely use open ended inquiries. Alternatively, case studies appropriating quantitative research data collection would likely use closed ended research questions. Deciding which research method is most appropriate depends on the researcher's intention. If mixed methods are utilized it is crucial that researchers can undertake quantitative and quantitative research properly.

Quantitative Research Example 1

For many researchers, it is helpful to analyze specific real world research method examples. One example of quantitative research would be a study regarding how mobile phone usage influences teenagers. The sample size of the survey includes a designated number of females and males. Researchers must take care to make sure that the sample size accurately reflects the larger population studied. Instead of researchers asking open ended questions a numerical data point scale is used for research question answer options. A numerical data point scale commonly utilized in quantitative research processes is the Likert scale. The Likert scale supplies numerical figures as research question answer options that represent associated opinion statements. For example, the number 1 could represent strongly agree while the number 10 could represent strongly disagree. The ability for the opinions of sample sizes to translate directly into numerical data is a powerful quantitative research tool.

Quantitative Research Example 2

Another example of quantitative research could be regarding the number of hours that employees spend at their workplace. Instead of having to go to offices all around the city, a proper sample size suffices. Rather than asking employees directly how much time they spend at their office, alternative data collection methods can be utilized. For example, researchers could note the times that sample size participants arrive at and leave the office. As a result, data collected via observation translates the non numerical research process of observation into a numerical data format. Researchers then use data quantitative research produced to find the average amount of hours an employee spends in the office.

Quantitative Research Example 3

Quantitative research is often undertaken in healthcare organizations. Quantitative data can massively assist hospitals seeking to improve their business processes and customer experience. For example, a hospital may want to know how efficiently the organization is functioning. Research question focus can range from doctor time spent per patient to the frequency of patient visits. Similar to other examples, instead of open ended research questions administered, numerical data points are assigned to research question answers. Numerical data point research question answer options may also include a range of numbers. A doctor time research question answer options may include up to 15 minutes, 15 to 30 minutes, over 30 minutes. For a patient visit frequency question, answer options may include 1 time, 2-5 times, more than 5 times. As a result, research question answers are translated into a quantifiable data format. From there, data collected can be analyzed and then applied to real world solutions. Actionable insights can be used to improve customer experience and business processes significantly.

Quantitative Research Example 4

Many businesses utilize the quantitative research method in order to better understand customer satisfaction. Customer satisfaction surveys are so commonplace that survey templates are widely available. A business professional can then customize the survey template to match the research design and objectives. A customer satisfaction survey seeks to learn more about everything from brand reputation to product or service pricing and quality. Survey data collected can occur through techniques like net promoter score questions and matrix table questions. Overall, the objective of customer satisfaction surveys is to improve the customer experience in a measurable way.

Quantitative Research Example 5

Many different countries all across the world utilize quantitative research methods for census purposes. A census is an official survey of a country's population. While the census aims to gain universal response it is still a sample size unless the entire population is polled. Once quantitative data collection is completed for the census, further subgroups can be classified. For example, classifications of population subgroups can include age ranges or gender assigned at birth.

Key Takeaways of Quantitative Research Examples

• There are different applications for qualitative data and quantitative data collected. Gaining a comprehensive understanding of qualitative data and quantitative data collection methods is massively helpful.
• Real world examples of quantitative research range from a business administered customer satisfaction survey to an employee hour research study.

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Quantitative Research

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Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.

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Wilson, L.A. (2019). Quantitative Research. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_54

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Quantitative and Qualitative Research in Business & Technology: Justifying a Suitable Research Methodology

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The right choice of a suitable research methodology is a crucial decision to perform effective scientific research and is mainly based on linking research objectives to the characteristics of the available research methodologies. Based on the notion that researchers in the fields of Economics, Business and Technology have to choose among multiple methods and techniques the selection of an appropriate research approach that might support cross-disciplinary research is one of the most difficult decisions for a researcher. For that reason, the aim of this paper is to provide issues related to: (a) Quantitative Research, (b) Qualitative Research and (c) Strategic Management of Digital Systems in order to investigate a suitable research methodology for identifying and analyzing key strategic management factors and phases. The publication of this paper has been partly supported by the University of Piraeus Research Center.

Keywords: Quantitative Research, Qualitative Research, Strategic Management, Digital Systems.

1.INTRODUCTION

Digital systems have been characterized as social systems where technology is only one aspect of them (Land, 1992). The study of Business and Technology is a multidisciplinary research object and as the literature review shows, there is a lack of a single global research approach that includes all the necessary areas of knowledge required for an efficient study (Galliers, 1992; Walsham, 1995). Strategic Management of Digital Systems is based on the understanding of various variables and key strategic factors related to: (a) business, (b) technology, (c) people, (d) enterprises, (e) economy, (f) law and (g) politics. Research in Business and Technology is characterized by methodological pluralism and the assortment of an appropriate research methodology is a crucial topic that attracts researchers' attention (Galliers, 1992; Miles & Huberman, 1994; Yin, 2011). Therefore, in research issues that combine Economics, Business and Information and Communication Technology (ICT) aspects, researchers has to choose among a variety of research methods, approaches and techniques to develop an appropriate research framework.

Research encompasses creative work undertaken on a systematic basis in order to increase knowledge and to use this knowledge to establish or confirm facts, solve problems, develop new theories and provide innovative solutions. There are two key categories of research design: (a) qualitative research and (b) quantitative research. Researchers choose quantitative or/and qualitative research methods according to the research aim, the...

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Your ultimate guide to quantitative research.

12 min read You may be already using quantitative research and want to check your understanding, or you may be starting from the beginning. Here’s an exploration of this research method and how you can best use it for maximum effect for your business.

You may be already using quantitative research and want to check your understanding, or you may be starting from the beginning. Here’s an exploration of this research method and how you can best use it for maximum effect for your business.

What is quantitative research?

Quantitative is the research method of collecting quantitative data – this is data that can be converted into numbers or numerical data, which can be easily quantified, compared, and analysed.

Quantitative research deals with primary and secondary sources where data is represented in numerical form. This can include closed-question poll results, statistics, and census information or demographic data .

Quantitative data tends to be used when researchers are interested in understanding a particular moment in time and examining data sets over time to find trends and patterns.

To collect numerical data, surveys are often employed as one of the main research methods to source first-hand information in primary research . Qualitative research can also come from third-party research studies .

Quantitative research is widely used in the realms of social sciences, such as biology, chemistry, psychology, economics, sociology, and marketing .

Research teams collect data that is significant to proving or disproving a hypothesis research question – known as the research objective. When they collect quantitative data, researchers will aim to use a sample size that is representative of the total population of the target market they’re interested in.

Then the data collected will be manually or automatically stored and compared for insights.

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Qualitative vs quantitative research

While the quantitative research definition focuses on numerical data, qualitative research is defined as data that supplies non-numerical information.

Quantitative research focuses on the thoughts, feelings, and values of a participant , to understand why people act in the way they do . They result in data types like quotes, symbols, images, and written testimonials.

These data types tell researchers subjective information, which can help us assign people into categories, such as a participant’s religion, gender , social class, political alignment, likely favoured products to buy, or their preferred training learning style.

For this reason, qualitative research is often used in social research, as this gives a window into the behaviour and actions of people.

In general, if you’re interested in measuring something or testing a hypothesis, use quantitative methods. If you want to explore ideas, thoughts, and meanings, use qualitative methods.

However, quantitative and qualitative research methods are both recommended when you’re looking to understand a point in time, while also finding out the reason behind the facts.

Quantitative research data collection methods

Quantitative research methods can use structured research instruments like:

• Surveys : A survey is a simple-to-create and easy-to-distribute research method , which helps gather information from large groups of participants quickly. Traditionally, paper-based surveys can now be made online, so costs can stay quite low.

Quantitative questions tend to be closed questions that ask for a numerical result, based on a range of options, or a yes/no answer that can be tallied quickly.

• Face-to-face or phone interviews: Interviews are a great way to connect with participants , though they require time from the research team to set up and conduct.

Researchers may also have issues connecting with participants in different geographical regions . The researcher uses a set of predefined close-ended questions, which ask for yes/no or numerical values.

• Polls: Polls can be a shorter version of surveys , used to get a ‘flavour’ of what the current situation is with participants. Online polls can be shared easily, though polls are best used with simple questions that request a range or a yes/no answer.

Quantitative data is the opposite of qualitative research, another dominant framework for research in the social sciences, explored further below.

Quantitative data types

Quantitative research methods often deliver the following data types:

• Test Scores
• Percent of training course completed
• Performance score out of 100
• Number of support calls active
• Customer Net Promoter Score (NPS)

When gathering numerical data, the emphasis is on how specific the data is, and whether they can provide an indication of what ‘is’ at the time of collection. Pre-existing statistical data can tell us what ‘was’ for the date and time range that it represented

Quantitative research design methods (with examples)

Quantitative research has a number of quantitative research designs you can choose from:

Descriptive

This design type describes the state of a data type is telling researchers, in its native environment. There won’t normally be a clearly defined research question to start with. Instead, data analysis will suggest a conclusion , which can become the hypothesis to investigate further.

Examples of descriptive quantitative design include:

• A description of child’s Christmas gifts they received that year
• A description of what businesses sell the most of during Black Friday
• A description of a product issue being experienced by a customer

Correlational

This design type looks at two or more data types, the relationship between them, and the extent that they differ or align. This does not look at the causal links deeper – instead statistical analysis methods looks at the variables in a natural environment.

Examples of correlational quantitative design include:

• The relationship between a child’s Christmas gifts and their perceived happiness level
• The relationship between a business’ sales during Black Friday and the total revenue generated over the year
• The relationship between a customer’s product issue and the reputation of the product

Causal-Comparative/Quasi-Experimental

This design type looks at two or more data types and tries to explain any relationship and differences between them, using a cause-effect analysis. The research is carried out in a near-natural environment, where information is gathered from two groups – a naturally occurring group that matches the original natural environment, and one that is not naturally present.

This allows for causal links to be made, though they might not be correct, as other variables may have an impact on results.

Examples of causal-comparative/quasi-experimental quantitative design include:

• The effect of children’s Christmas gifts on happiness
• The effect of Black Friday sales figures on the productivity of company yearly sales
• The effect of product issues on the public perception of a product

Experimental Research

This design type looks to make a controlled environment in which two or more variables are observed to understand the exact cause and effect they have. This becomes a quantitative research study, where data types are manipulated to assess the effect they have. The participants are not naturally occurring groups, as the setting is no longer natural. A quantitative research study can help pinpoint the exact conditions in which variables impact one another.

Examples of experimental quantitative design include:

• The effect of children’s Christmas gifts on a child’s dopamine (happiness) levels
• The effect of Black Friday sales on the success of the company
• The effect of product issues on the perceived reliability of the product

Quantitative research methods need to be carefully considered, as your data collection of a data type can be used to different effects. For example, statistics can be descriptive or correlational (or inferential). Descriptive statistics help us to summarise our data, while inferential statistics help infer conclusions about significant differences.

Advantages of quantitative research

• Easy to do : Doing quantitative research is more straightforward, as the results come in numerical format, which can be more easily interpreted.
• Less interpretation : Due to the factual nature of the results, you will be able to accept or reject your hypothesis based on the numerical data collected.
• Less bias : There are higher levels of control that can be applied to the research, so bias can be reduced , making your data more reliable and precise.

Disadvantages of quantitative research

• Can’t understand reasons: Quantitative research doesn’t always tell you the full story, meaning you won’t understand the context – or the why, of the data you see, why do you see the results you have uncovered?
• Useful for simpler situations: Quantitative research on its own is not great when dealing with complex issues. In these cases, quantitative research may not be enough.

How to use quantitative research to your business’s advantage

Quantitative research methods may help in areas such as:

• Identifying which advert or landing page performs better
• Identifying how satisfied your customers are
• How many customers are likely to recommend you
• Tracking how your brand ranks in awareness and customer purchase intent
• Learn what consumers are likely to buy from your brand.

6 steps to conducting good quantitative research

Businesses can benefit from quantitative research by using it to evaluate the impact of data types. There are several steps to this:

• Define your problem or interest area : What do you observe is happening and is it frequent? Identify the data type/s you’re observing.
• Create a hypothesis : Ask yourself what could be the causes for the situation with those data types.
• Plan your quantitative research : Use structured research instruments like surveys or polls to ask questions that test your hypothesis.
• Data Collection : Collect quantitative data and understand what your data types are telling you. Using data collected on different types over long time periods can give you information on patterns.
• Data analysis : Does your information support your hypothesis? (You may need to redo the research with other variables to see if the results improve)
• Effectively present data : Communicate the results in a clear and concise way to help other people understand the findings.

How Qualtrics products can enhance & simplify the quantitative research process

The Qualtrics XM system gives you an all-in-one, integrated solution to help you all the way through conducting quantitative research. From survey creation and data collection to statistical analysis methods and data reporting, it can help all your internal teams gain insights from your numerical data.

Quantitative methods are catered to your business through templates or advanced survey designs. While you can manually collect data and conduct data analysis in a spreadsheet program, this solution helps you automate the process of quantitative research, saving you time and administration work.

Using computational techniques helps you to avoid human errors, and participant results come in are already incorporated into the analysis in real-time.

Our key tools, Stats IQ™ and Driver IQ™ make analysing numerical data easy and simple. Choose to highlight key findings based on variables or highlight statistically insignificant findings. The choice is yours.

Some examples of your workspace in action, using drag and drop to create fast data visualisations quickly:

Find out how Qualtrics XM solution can help improve research team’s quantitative methods

Related resources

Market intelligence tools 10 min read, qualitative research questions 11 min read, primary vs secondary research 14 min read, business research methods 12 min read, ethnographic research 11 min read, business research 10 min read, qualitative research design 12 min read, request demo.

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