What is the need for qualitative data during new product development?
A question like this is not uncommon.
We live in a world where phrases like ‘data is the new gold’ and ‘data is king’ are treated like biblical prophecies. Generally, people don’t understand the meaning of such vague messianic messages.
Thus qualitative data analysis in a field like product development doesn’t get as much attention as it should. Many foolishly view quantitative and qualitative data as two battling ideas. In reality, they are both very important contributors to any serious type of analysis.
However, it is fair to say the world today is more interested in whatever is quantifiable. Take a field like product development. Entrepreneurs sell their idea and company to investors based increasingly on hard numbers without appreciating the qualitative aspect of the product they are bringing to market.
Let’s take an example. An entrepreneur decides to open a company of mid-priced ladies handbags in India. In order to get investment for handbags, he approaches an investor. He pitches his idea by telling the investor this –
“There are almost half a billion women living in India. Our company will target 1% of this population, equaling roughly to 5 million women. Even if we manage to reach 1% of this audience (50,000) and manage to sell them handbags marked at an upscale price of Rs. 2000 on an average, we can make 10 crore rupees”
This line of thinking is usually a symptomatic of rigid quantitative thinking. People who think along such lines refuse to account for obvious qualitative factors which drive the market. This problem doesn’t just plague entrepreneurs. Big companies today don’t account for qualitative factors during new product development.
In this piece, we lay down reasons why qualitative data is essential for new product development.
Comparison between Qualitative and Quantitative Data
Before delving into the role of qualitative data in new product development, let’s first understand its difference with quantitative data.
By definition, qualitative and quantitative data stand poles apart. Qualitative data is an exploration of all things about a product that are not quantifiable. These are typically things which are one cannot express through metrics. Quantitative data, on the other hand, refers to everything quantifiable.
The table below gives a more complete idea about the differences between qualitative and quantitative research.
|1.||Involves the creation of a theory or a hypotheses||Involves the testing of a theory based on available data|
|2.||Generally expressed in words without the use of numbers or data since it involves unquantifiable observations||Is expressed through the use of graphs and other pictorial representations because it is driven by numbers|
|3||Involves the general use of summarizing and categorizing||Involves the use of mathematical and statistical techniques|
|4||Takes a subjective view on a given topic and tries to understand the context||Takes an objective view of the subject and studies the hard cold numbers|
|5||Requires little use of data and respondents||Requires immense use of data and respondents|
|6||Some data collection methods include focus groups, interviews, and literary reviews||Data collection takes place through reliable surveys and experiments.|
Mixed Method Approach
One point to note here is that companies have the option of choosing a mixed approach to product development. In other words, it is not necessary for companies to think of this as qualitative vs quantitative research. This is not a fight between two perspectives.
Generally, most companies follow a mixed approach. In other words, companies account for both qualitative and quantitative data during product development. This is because they understand the larger need for balance between the two.
It is impossible to develop a good product concentrating solely on either qualitative or quantitative data. Companies which manage to strike a balance are generally the ones which succeed.
Read More: Mixed Method Approach
Why is Qualitative Data Important for New Product Development?
The role of qualitative research in new product development is well-established. The most successful products and companies have found a way to balance qualitative and quantitative research data.
However, asking the question ‘why’ is still valid. Why indeed is qualitative data important for developing new products?
In this piece, we try to bring to the fore specific stages in product development where the role of qualitative data is immense. Remember, there are many other reasons why qualitative research and data is important. However, we are going to focus on four specific stages of product development to understand the importance of qualitative research.
Number One: Research Stage
In the beginning, the need for qualitative data is first felt during the research phase of product development. Why is this the case?
The research stage is typically the part of the product development process where creators need to analyse all perspectives.
For instance, let’s assume a smartphone manufacturer wishes to bring a new line of smartphones to the market. On one side, the company has to consider the resources it can invest in manufacturing the smartphones. This is typically the quantitative research and analysis of the situation.
However, there are other factors to consider. What is the USP of this particular smartphone? Which need of the audience is this particular smartphone addressing? How will the company market the product to the different consumer markets of the world?
These questions broaden the scope of smartphone manufacturing from the process alone to the wider points. Remember, a company can’t just bring any product to market and expect to make money. There are many questions the company must answer. Is there a demand for the product? Which other companies are making a similar product? Is it feasible to enter the market given the competition in a given segment?
Generally, these questions constitute qualitative analysis and research. By the nature of these questions alone, you can guess their immense importance. Companies which encourage employees to ask these questions and use qualitative data to answer them tend to create better products.
This doesn’t imply that quantitative research is useless. The qualitative vs quantitative confrontational perception is naïve and fraudulent. Generally, companies take into account both types of data. There is no qualitative vs quantitative matchup. Both are crucial for making good products.
Read More: Research Stage
Number Two: Product Feature Development
This is the era of multi-functional products. People used to buy phones ten years ago primarily to call others and receive incoming calls. Today, calling someone is hardly a quality one would distinguish a mobile phone with.
A smartphone today is an essential digital organ of every human being. This is the beauty of features and functionality development. Every product goes through a feature development and refinement phase. During this stage, the company has to decide which features it adds and refines in its product.
Approaching this stage of product development without qualitative data is like committing business suicide. Why? Let’s take the previous example of a smartphone manufacturing company starting a new line of phones. How will the company settle on the features it must add to the new smartphone?
Quantitative research can give the company an idea about its ability to develop a given set of features. It can also point to the additional cost and the number of phones the company will have to sell to make up the cost.
However, none of these points explain the very reason new features are added to smartphones – will the end user like the new feature? Furthermore, is a new feature or a set of features enough to convince someone to buy the smartphone?
Questions like these, which are vital during feature development, can only be answered with qualitative data.
Think about this – what is stopping Apple today from launching a 12-inch screen smartphone? It certainly has the money and the technical ability to do this. The answer is simple – the people who buy Apple phones or smartphones in general don’t need such a large screen.
Every company must make an effort to understand the exact features their customers need. This can be achieved with the help of qualitative data.
Read More: Product Feature Development
Number Three: Tactile Factors
Many buying decisions are based on the physical feel of the product. This is an inescapable fact of retail. The product must feel good in order to make a customer actually buy it. Thus, a simple factor like packaging becomes very important.
How does one approach packaging from a quantitative perspective? In reality, it is not possible. If one looks at this from the qualitative vs quantitative research point of view, it would be an error in judgement.
The analysis of tactile factors has to come from a qualitative standpoint. In other words, in order to make the right decisions when it comes to tactile factors like packaging and retail placement, qualitative data is essential.
Quantitative data is not enough for tactile factors because it doesn’t provide the context in which such factors become important. For instance, how can any number of quantitative factors explain how a customer feels when he or she picks up the product? This analysis can only come from qualitative data which helps companies go deep and study customer psyche.
Generally, many companies ignore tactile factors altogether when they consider the product development process. This is partly because new companies coming into the market rely more on online sales. Thus, they do not see a need to work on tactile factors.
However, every company has to think about tactile factors for the long term growth of the business. Retail is not going anywhere. People continue to throng to malls and shops to buy whatever they need to. Any company that wishes to make more money has thought of retail, and this inescapably leads them to deal with tactile factors.
Read More: Tactile Factors
Thus, it is best for companies today to rely on qualitative data for optimizing tactile factors during the product development process.
Number Four: Feedback
Perhaps the most underrated part of the product development process, feedback analysis brings forth the obvious need for qualitative data.
Once a product goes to market, there are two possible realities – profit or loss. The degree of both these realities can vary. However, the overall result is either of these two.
Why is feedback important? For one, it helps shed light on the reason behind success or failure. Here again, the qualitative vs quantitative research debate comes into the picture. After all, which type of approach to analyzing feedback brings greater insight?
Let’s look at quantitative data first. When analyzing feedback with quantitative data alone, companies get an insight into the number of sales they made, the demographic breakdown, and so on. There is no insight into the specific feedback the audience gave. In other words, feedback is measured solely by how people spend their money.
Qualitative data broadens the scope. It provides companies with more insight into how customers reacted to the product in real-time. This data is important because it directly helps companies understand the specific problems in their product. No company ever starts off to make its last product. Creating something is always a journey to understand what the customers want. If the first product doesn’t accomplish this completely, the feedback data can help companies create a second product which does.
The feedback on the second then presents ideas for the third. Thus, this cycle keeps going on as the company grows and keeps improving its product. Thus qualitative data is immensely important from a feedback perspective.
Read More: Feedback
In Conclusion – Qualitative Data for New Product Development
The role of qualitative data for new product development is crucial.
In this piece, we do a complete analysis of the difference between qualitative and quantitative research. Furthermore, we also cover the need for qualitative data for new product development. We do this by highlighting the key phases of product development where qualitative data is an absolute essential.
Read More: Qualitative Data for New Product Development