Quantitative Research

One of the core roles of any business owner is to understand data because it informs decisions and can help predict your business’s growth. Before diving into the world of data, it’s important to set out your research objectives, the types of data you want to analyze, and how to interpret it for future decisions.

After reading this blog, you’ll have a better understanding of how to analyze and interpret data, turning it into actionable insights.

It’s important to clarify that there are two types of research: Market and Consumer Research. 

Market research focuses on the broader market as a whole, and consumer research is focused on the individual consumer, such as their buying habits. The two types of market research can be split into quantitative and qualitative. Each type has its methods and tools for collecting and analyzing data, which can help better understand the growth and scalability of your business. 

Primary research is data you collect through focus groups, questionnaires, and surveys. This approach focuses on the consumer, gathering first-hand data from clients, customers, and stakeholders to understand their needs, preferences, and behaviors. 

To carry out this type of research, you can identify opportunities, limit risks, and make more strategic and informed decisions. 

Primary research is the why, and the motivations that drive a person to purchase your product or services. You are zoning in on one specific brand or product. 

When you are conducting primary research, there are two types: 

Exploratory: More general and open-ended and involves a lengthier interview with one individual or a small group of people.

Specific: Any problems during the exploratory phase will be discussed in a formal and more structured interview.

Secondary market research focuses on the market as a whole or a broader segment to learn about competitors, market trends, demographics, and market size.

Secondary research involves analyzing existing data from other sources from a variety of channels. This could be from reputable sources such as Statista, Gartner, Ibis World as well as using social listening tools. Many of these sources offer industry reports and trends throughout the year. Government organizations also publish research that many business owners would find useful for demographics, spending habits, and commodity use. 

Another great way to carry out secondary research is by analyzing your competitor’s websites. Dive deeper into what they post, what is performing well, and what type of audience they are attracting. This can help inform your marketing and content strategy going forward. 

Primary research takes time, effort, and money which is carried out by bigger companies and corporations while secondary research is more cost-effective for small business owners on a lower budget. 

You wouldn’t get on stage without practicing your lines so why create a product or service that isn’t in demand? 

Most businesses fail because they haven’t done enough research in the market to see if there’s a need. If you are the only person struggling with the problem, you won’t get enough business to sustain the growth. 

First, establish these key topics for your market research. 

1. Research topic

Identify the topic of your market research and why you need this data. Maybe it’s for pricing, a demand in the market, or even to analyze what your competitors are doing.

Secondary research is more accessible for small business owners especially if they don’t have a large enough data pool to pull from or the budget. 

Always start with secondary research first to get a feel for the market and then carry out primary research if it’s within your budget. 

Key questions to ask when setting the foundations are: 

1. What is my primary goal?
2. Who are my customers?
3. Who are my main competitors?

2. Research existing sources of data

Numerous reputable sources, including government agencies (such as the U.S. Census Bureau or national statistical offices), industry-specific publications, and market research firms (like Statista or Gartner), offer readily available data on market trends, demographics, and consumer behavior. These resources provide valuable insights for your secondary market research.

3. Forget to prepare, prepare to fail 

Know what you are looking for and discard what isn’t relevant. Research takes time and effort so not having a clear roadmap of what you need to collect and don’t can be confusing. Make sure to create spreadsheets or folders to place the information somewhere so you can analyze it later. 

This will help you interpret the data and be able to report your findings and make strategic decisions. 

4. Time for analyzing 

You have all the data placed neatly in folders (we hope!), it’s time to break it down and interpret it. Look for patterns and long-term trends. This information will not only inform your strategy but also pitfalls to avoid. 

Always learn from other people’s mistakes. 

5. Verify the validity of the data 

Make sure you are collecting data from unbiased sources to avoid misleading statements or figures for your reports. 

Without data, it’s harder to replicate what is working and be backed by clients and customers. You wouldn’t launch a new product without first collecting data on its product demand. 

Some common data collection methods include surveys, interviews, observations, focus groups, experiments, and secondary data analysis. When you are collecting data, it’s either to refute or back up your hypothesis about a particular topic. 

These methods and tools are used to collect quantitative and qualitative data to help you accurately understand data acquisition. 

Quantitative data includes: 

• Numerical Data 
• Surveys, polls, questionnaires
• Statistical analysis 

To observe patterns and long-term trends. Quantitative data is anything that can be measured, made up of specific quantities and numbers. Some examples include sales figures, email click-through rates, the number of website visitors, and the percentage of revenue increase. 

It’s useful for answering questions such as: 

• Is there a market for your product or service? 

• How much market awareness is there of your product or service?

• What are their buying habits?
• How are the needs of your target market changing?

Quantitative data uses tests and close-ended questions to collect, analyze, and interpret data.

Qualitative data focuses on: 

• Non-Numerical Data 
• Interviews 
• Focus Groups 
• Observations 

To delve deeper into understanding attitudes, behaviors, and beliefs. 

For interviews, the interviewer poses questions to the interviewee that are either highly structured, open-ended, or a mix of both. Focus groups are intended to collect data through interactive and directed discussions by a researcher. 

Focus groups are more useful in the initial research phase, while in-depth interviews are better in the later stage of research. Focus groups provide a powerful way to understand broader topics and generate new ideas. 

Some examples of qualitative data include comments left in response to survey questions, things people have said during interviews, tweets, social media posts, and the text included in product reviews. 

Qualitative Research Tools:

Qualitative research focuses on understanding the “why” behind behaviors, attitudes, and experiences.

Many big companies such as Google, Sony, LinkedIn, and Microsoft use GWI and it’s known as the go-to platform for global consumer research.

You can get instant access to data representative of the views, behaviors, and interests of over 3 billion consumers across 50+ markets. Agencies, brands, and media companies use GWI often to find out what really drives their audience to action. 

Other tools to decipher qualitative research are Qualtrics and Google Analytics. They analyze user engagement, and the effectiveness of marketing campaigns, and offer survey creation, and data analysis tools.

Quantitative Research Tools: 

For companies with a budget, software tools like ATLAS.TI and NVivo are the leading data analysis software to decipher complex data and turn them into actionable insights quickly. 

Other software tools like Content Square and Dovetail analyze users’ behavior on websites and synthesize data from interviews and user testing. 

If you are looking for software that combines both qualitative and quantitative, Lumivero carries out mixed-method research. Although qualitative and quantitative research provides different insights, both are useful when combined to create the bigger picture. 

Gathering and collecting data is great but now it’s time to turn the data into actionable insights. Four key data analysis techniques to focus on are Descriptive, Diagnostic, Predictive, and Prescriptive. 

Break the types into Descriptive – “What is?”, Diagnostic – “Why is it?”, Predictive – “What will be?”, and Prescriptive – “What should be done?”.

Descriptive Analysis: 

Descriptive analysis just states the facts. Let’s say you sold 10 lead magnets, two on Monday, three on Wednesday, and five on Friday. You are looking at the number of sales per day, the source of downloads such as lead magnets, the types of people downloading, and the total number of downloads. 

Diagnostic Analysis: 

Diagnostic is about finding out the why. You sold lead magnets on Monday, Wednesday, and Friday but you might wonder why not on Tuesday, Thursday, or the weekend. You are figuring out why people aren’t buying on those days. Maybe you were running ads on your website for people to buy your lead magnet. Were your ads running on Tuesday? How many clicks were there on Tuesday in comparison to Monday?

Predictive Analysis: 

You’ve been tracking your lead magnet sales for a few weeks, noting the days they sell, and you’ve also been tracking the days you send out email promotions. You might have noticed that on Wednesday and Friday, your email promotions perform better leading to increased sales.

On weekends, fewer people open your emails leading to a decrease in sales. You might predict that you’ll get three lead magnet sales on Wednesday, five lead magnet sales on Friday, and zero sales on the weekend. You are predicting your future promotional activities by observing patterns.

Prescriptive Analysis: 

Based on the information you found out through predictive analysis, you use these predictions to determine what to do next. 

Because my sales are low on Tuesdays, Thursdays, and the weekends, I’ll try new strategies to increase my sales. On Tuesdays and Thursdays, I’ll run targeted social media ads to drive sales. On the weekends, I’ll try a different subject line to increase open rates, offering a limited-time discount to incentivize purchases. If they are successful, I will incorporate them into my marketing plan for the future. 

Clustering Analysis: 

Now, you want to find out who is downloading your lead magnet and visiting your website. 

An example could be: 

Using clustering analysis, I’ve identified the top three groups who are buying my lead magnet. 

Cluster 1: Small business owners in the marketing industry who found my website through social media. 

Cluster 2: Freelance writers looking to improve their content creation process, who found my site through Google searches. 

Cluster 3: Corporate marketing managers from larger companies, who found my site through referrals.

Based on the information you’ve collected, you can group segments of the audience based on shared characteristics to personalize your approach, marketing messages, and content that’s targeted more specifically at the audience. 

Regression analysis:

You’ve been tracking the relationship between the number of email subscribers you have and the number of lead magnet sales. Using regression analysis, you found a positive correlation between the number of email subscribers and lead magnet sales. For every 100 email subscribers, I see an average increase of 5 lead magnet sales. 

Therefore, I would predict that increasing my email subscribers is an effective way to increase lead magnet sales. 

I also noticed that for every dollar I spend on ADs, I gain 2 new lead magnet downloads.

Understanding this information means I can prioritize my marketing efforts into growing my email subscriber list and invest in social media advertising, knowing that these activities will directly contribute to lead magnet sales. 

You use regression analysis to quantify the relationship between variables and make data-driven decisions about resource allocation. 

Understanding and leveraging data is a necessity for the growth of your business. By establishing clear research objective goals, mastering quantitative and qualitative research, and utilizing the right tools, you can transform this information into actionable insights. Market research is not a one-time event, it’s an ongoing process. Learn to interpret data, analyze market trends, and empower your decisions with data to drive sustainable growth and achieve success. 

Stop guessing and start knowing. Get clear, actionable insights from your data. Contact us today to learn how we can help you make informed decisions and achieve sustainable growth.