Over the years, the world has ever-increasingly shifted towards a data-driven decision-making process. Organizations no longer make decisions only based on the fact that this would be a good market to expand into, or people might like this product, etc. All these decisions are now made after they collect customer feedback and research every factor that might be responsible for the success or failure of the venture.
This data-driven model has even found its way into other industries. The 2011 movie “Moneyball” documented the introduction of this in Major League Baseball. Leicester City proved that the model still works by winning the English Premier League in 2015/16.
Even in our day to day life, why has e-commerce gained the stronghold it has in today’s market? The answer is pretty easy if you think about it, you see the feedback of others who used that product right there. You look into how well it is rated by how many people, the most common problems, etc. before coming to a decision. Our decisions are influenced by the data that is available to us, mediocrity is no longer tolerable, and so we base our decisions on what data suggests is the best option.
Analyzing Data: Qualitative vs. Quantitative Research
Whether you’re deciding to launch a new product or looking up online reviews to choose where to buy your dinner from, there is lots of data to analyze. So how exactly do you study and analyze all the data available to you? In this article we’ll be looking into the kinds of data and how to obtain them.
If you do put in the effort to analyze all data and explain it to a layperson in simple terms, data comes down to two categories:
- Qualitative data
- Quantitative data
Read on as we go in-depth understanding of the difference between qualitative and quantitative data and how to analyze both sets of data.
Qualitative research is the aggregation of people’s opinions on a specific topic. Qualitative data doesn’t help you make beautiful looking pie-charts and graphs instead, it helps you understand the motivations, thought process, etc. of people behind a decision.
Quantitative research is used to collect hard facts and figures. It is statistical and structured, thus making the whole process of collecting quantitative data more rigid and defined. As it is measured in defined numbers and values, quantitative data is a lot easier to analyze as compared to qualitative. This data can be further divided into two categories:
- Discrete Data: This is data that is finite and cannot be broken down further. E.g., how many samples of a product were sold last year?
- Continuous Data: This is data that regularly changes in value and can be further divided.
|Expressed in Words||Expressed in Number|
|Uses Open-Ended Questions||Uses Closed Questions|
Qualitative vs. Quantitative Data: When to Collect
The debate is not between qualitative vs. quantitative analysis, the challenge is finding a balance between the two of them. Yes, numbers, stats, graphs, etc. play a big part in our decision-making process, but what also plays a part is the personal opinion of people.
When to Collect Qualitative Data?
Qualitative data is perfect when you are looking for new opportunities or trying to identify problems in existing goods and services. Say you’re looking to enter a new market with your current product. Qualitative research will help you identify the issues which you could help solve, the areas where existing products fall short, and other macroeconomic questions.
When to Collect Quantitative Data?
Once you have formed a hypothesis based on the responses from the qualitative research, quantitative data will give you the metrics to confirm the extent/reach of each challenge and opportunity.
Finding the Balance Between Qualitative and Quantitative Data
As customers become increasingly technical and more savvy, companies have realized the importance of customer experience. This increased awareness has led to many advances in how questions are framed and into how you can balance qualitative and quantitative data.
Net Promoter Score (NPS) at one time called “the one question you need to grow” is probably the most successful example of what can be achieved when you find the right balance. It starts off with a quantitative question “On a scale of 0-10, how likely are you to recommend our product to a friend or acquaintance?” This is followed by an open-ended question which asks the responder why they picked the answer they did.
The best way to find this balance for yourself is to be clear of what you expect to gain from the question. What if, instead of the NPS question you were asked, “How does our product compare to other similar products you’ve used?” While you’d have a more detailed answer, you wouldn’t have any way of identifying your loyal and detracting customers.
Most survey maker tools will provide you with survey question examples that fit this balance and that you can include in your surveys.
It’s also important to account and plan ahead for the volume of data you will be working with. As you attempt to strike a balance between the quality of qualitative and quantitative data you obtain, keep in mind the sheer volume of raw data you will have to analyze before developing actionable insights. As you spend time in the initial stages forming survey questions and preparing for data collection, also give some thought to the methods you can use to analyze big data output.
Qualitative vs. Quantitative: Data Collection Methods
Qualitative Data Collection Methods
- Interviews: This includes asking open-ended questions to respondents.
- Focus Groups: Focus groups are an excellent way to gather different opinions from multiple people.
- Case Studies: In-depth studies into individuals, events, or organizations.
Quantitative Data Collection Methods
- Surveys: Surveys that consist of close-ended questions aimed towards studying individuals or groups.
- A/B Testing: This involves introducing respondents to situations where they are asked to pick one of two options. This helps establish cause and effect relationships.
- Analyzing Metrics: Metrics like CTR, conversions, etc can be used to systematically record and analyze which keywords and types of content work with the customer base.
Qualitative vs. Quantitative Research Questions
Let’s take a look at a few examples of qualitative and quantitative research questions.
- As a company, what can we do to improve our services?
- Do you have any comments, concerns, or questions regarding our service?
- What new features would you like to see in future updates?
- Where do you see yourself to be after five years?
- Why are you unhappy with your existing service provider?
- How long have you been a customer with us?
- When was your last purchase from us?
- How likely are you to purchase any of our products again on a scale of 1-10?
- How would you rate your experience with our customer support team?
- How reliable is your Internet service?
Now that we’ve studied the differences between these two methods, you can make use of both to get the best responses from your surveys. ProProfs Survey Maker has a wide range of ready to use professionally made templates that you can use for your next project.
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