June 28, 2024

Product Development Research: Intro

Small, and sometimes even medium-sized product teams view research as a long, expensive, and biased process. So they often avoid it at all. 

At JetStyle, any product development process should start and be constantly accompanied by research. It’s an integral part of hypothesis testing, even if the result of research has proved your hypothesis wrong. 

This is the first article in our series written with Pauline Bynova, head of Marketing at JetStyle, and an experienced marketing consultant. She’s been managing research activities in product teams and knows how to launch them quickly. Your product wins when you process customer feedback regularly. The more you experiment with data, the more you customize the research process according to your business requirements. 

Let’s start with the basics. 

Marketing research vs. product research 

Audience research is different for marketing and product development. Marketing researchers have different goals and use different tools. They usually focus on external factors influencing the development of the market. Marketers aim to understand the market size and share, brand health indicators, which is rarely related to user experience in a product. 

Marketing research is often not an option for product teams, as it’s too expensive. The main goal of product research is to use your audience’s experience to develop your product. Product research focuses primarily on communication with your current users. Your task is to capture the clients’ needs and pains. You look for evidence that your product can solve their problems, and for spots where you lose their loyalty. 

There is a huge variety of product research methods, both quantitative and qualitative. You can launch a research using data from your web analytics data. You do have Google Analytics on your website, don’t you? 

Qualitative vs Quantitative research 

We already mentioned two main types of research: qualitative and quantitative. The difference lies in the format of the result. Quantitative research gives you numbers: metrics, graphs, and dynamics of indicators. 

After qualitative research, you deal with words: insights, hypotheses, opinions, the wording of key needs, and the pains of the audience. 

One crucial factor for quantitative research is how accurately the data is represented. 

Statistical error 

Statistical error happens a lot among beginners. Let’s say, you’re launching an A/B test for your small product, or a web page with little web traffic. How many users do you need to get reliable results about the conversion rate? 

We highly recommend using sample size calculators such as this one to check out how much traffic you need to really trust the results. 

This approach saves you a lot of resources. Sometimes when you plan a research project, you see that your sample size could take years to accumulate, and it makes your research unviable. 

Qualitative research also prioritizes data representativeness, but it works differently. For example, if 3 of 5 respondents report a similar problem, you don’t have to conduct dozens more interviews. Certainly your next step is to fix the problem. After you fix it, you may start interviewing users again. 

Researcher bias 

When it comes to qualitative research, researcher bias is the most dangerous pitfall. The only way to get rid of it is to outsource the research process. 

However, if you do it, it will also affect the results, as the researcher is out of context. We suggest you think of bias as an inevitable element of the process. To minimize the harm, you have to learn to notice and fight it. 

There are lots of tools for that, one of Pauline’s favorites is described in a book by Robert Fitspatrik, “The Mom Test”

If you’re a small product team, mix & match 

The key is to combine qualitative and quantitative methods. In the first type, you have usability testing, focus groups, in-depth interviews, recordings of sessions , etc. You have probably done this for your product. 

In the next part of this series, we’ll share more about our favorite research combo: NPS —> in-depth interview —> SCI. It’s fast and easy to set up. At the same time, you can adjust it to your vision, as all parts of this combination are interchangeable. Stay tuned for the next article! 

FAQ
Why do small product teams often avoid research, and is it really necessary?
Many small and mid-size teams see research as slow, expensive, and biased. However, product research is essential for hypothesis testing and product growth. Even when research disproves a hypothesis, it still saves resources by preventing wrong development decisions.
What is the difference between marketing research and product research?
Marketing research focuses on external market factors such as market size, share, and brand health. Product research focuses on current users, their behavior, needs, and pain points. Its goal is to improve the product experience and prevent loss of user loyalty.
How should teams choose between qualitative and quantitative research?
Both are necessary and serve different purposes. Quantitative research provides numbers, trends, and metrics, while qualitative research produces insights, hypotheses, and user language. The most effective approach is to combine both methods depending on the product stage and business goals.
How can small teams avoid statistical errors in quantitative research?
Teams should always verify whether they have a sufficient sample size before trusting results. Using sample size calculators helps determine if data is representative or if research would take too long to be meaningful, saving time and resources.
How can product teams deal with researcher bias in qualitative research?
Researcher bias is inevitable, especially when teams research their own products. The goal is not to eliminate bias entirely, but to recognize and minimize it. Using structured techniques, learning from established frameworks like The Mom Test, and consciously challenging assumptions helps reduce its impact.
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