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Promoting Leadership Principles in Product Management

Using the right data methods in product research

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Delivering a solid product that customers love requires an up-front knowledge of the market in which customers and potential customers operate. Understanding the problems they face, and solving those problems with a software solution, is the end goal.

I’ve been asked many times what the best way is to discover a market and understand the needs of customers in that market. My answer is usually some form of “it depends.” Some have potentially millions of customers (e.g. B2C) and other markets have far fewer—generally high-paying—potential customers (e.g. B2B). Attaining access to data differs depending on the makeup of the market.

At a high level, there are two methods you use to acquire market data, regardless of the industry: they are qualitative and quantitative research. Let’s explore how you can use both to get the data you need to deeply understand your market.

 At a high level, a simple explanation of quantitative vs. qualitative research is as follows: think of quantitative as structural (numerical) data that can be plugged into a spreadsheet and analyzed using statistical methods. Conversely, think of qualitative data as unstructured information that is summarized subjectively, as opposed to mathematically.

 At first look you might think that you need to choose one method or the other, depending on your market. For example, if sell B2C products to potentially millions of customers, a quantitative approach might be the best, done through surveys, A/B testing and other methods. Or if you sell B2B products, you can focus on qualitative methods like customer interviews, focus groups and the like. However, as you dig deeper you see that using a combination of the two methods is the better approach.

These two methods of research not only do not conflict with each other, they work better as a team. In a world of ‘big data’ there’s an abundance of statistics and figures that form a strong foundation for decisions. That foundation is more complete when coupled with information collected from real people, which gives the numbers real meaning. So how do we bring data from these two types of research together to help us formulate roadmaps and product decisions?

When employing these types of research, think of quantitative research as answering the ‘what’ question, and qualitative answering the ‘why’ question. When you’re narrowing down features and functionality to add to the product, you need to know what those are; and when you’re putting together product plans and marketing briefs, the why needs to be at the forefront. I have used following approach effectively at a number of companies:

  1. Gather data: Start with customer interviews, focus groups and other types of ethnographic research. Asking the same set of questions to multiple customers and potential customers gets you significant—primarily qualitative and subjective—data that helps you understand the problems customers in your markets are facing.
  2. Analyze data: Working with engineering and UX leads, distill the gathered data into clusters of problems and ideas. In this stage you can start to put numbers to the problems and quantify which ones are bigger issues for the majority of customers. You then prioritize the problems and begin to flesh out epics that can be used to get buyoff from marketing, sales and executives.
  3. Act on data: With epics in place you move forward with your development processes (the major part of every development project) to build the products. Through this phase you build in application metrics that will provide more quantitative data. You also use surveys to get real-time data to resolve any unknowns that arise in any phase.
  4. Iterate: As the new product moves forward to market you use a combination of these methods to refine and improve it. Continue to track customer feedback and monitor product usage.

Obtaining the right data to build a product that will delight your customers is an in-exact science. It takes a lot of work and repetition and requires significant patience. Ultimately, doing this work right is the key to creating successful products.

Questions: What’s your preferred approach to gathering market data? Do you find it difficult to attain compelling market data? Why? Please leave a comment in the space below.

The Product Management Perspective: Doing the work of market research is, in my experience, the most important ‘job’ in product management. When you do this effectively, everything else falls into place.

One thought on “Using the right data methods in product research

  1. Pingback: Leading product strategy and execution | Lead on Purpose

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