Digital product research is essential if your goal is to create something that people will want to use.

Whether it’s a brand new product, service, or feature update, you have to understand it and its value inside and out. Otherwise, how can you hope to sell it?

Thorough product research, integrated throughout the development life cycle, reduces risk and maximizes returns on investment. Data provides valuable insight into customer needs and market opportunities. And when you understand what users want, not just what you think they need, you’re more likely to increase the number of satisfied and repeat customers.

There is no one right way to do product research. Strategies vary from project to project. The processes are interdependent and iterative, not linear. But the basics remain the same.


Test Your Idea

Every great product starts with a compelling concept. Even the best ideas are unlikely to come to fruition unless they are accompanied by a thorough grasp of the product market.

Many businesses fail because they “create items that no one wants.” The process of assessing the demand for your product before it is created is known as idea validation.


Idea validation and early market research reduce project risk. It will save you time, money, and energy. Make sure you develop the right product for the right market. Something feasible and viable.

Idea testing and market research methods include online surveys, focus groups, and in-depth interviews. Social media and online communities are valuable ways to connect with target audiences. New and innovative market research methods such as virtual/ augmented reality, mobile ethnography, gamification, and biometric response research are also on the rise.



Once you have the right idea, you have to get everyone to agree on it. The entire team- the product owner, developers, designers, marketers, support, and stakeholders- must have a shared vision for the product. And that vision should be data-driven. Data is collected and organized in a number of ways by teams:

  • Business Model Canvas

This aids in the definition of the product’s value proposition, infrastructure, client groups, and cost structure. It’s basically a one-page overview of the complete company plan.

  • User Personas 

  Detailed images of your target demographic — helps you better understand your customers. This exercise is crucial because it builds a foundation on which to build and shifts your focus to your users.

  • User Journey Maps

This is a visual representation of your customer’s journey as they interact with your product and brand. This exercise is beneficial after you’ve developed detailed user personas. The process is very iterative, but it gets easier over time. The more data you have about your customers, the better you can understand them and predict their needs.

  • Feature Mapping

 Once everyone agrees and initial research is complete, the team can document the feature set, build a roadmap and prioritize the work – ultimately guiding the team through design, development, and launch. 


Gathering User Feedback

What people say isn’t always the same as what people do. So it’s a good idea to get people to interact with your product as often as possible. Qualitative research – direct observation of user behavior – is beneficial for identifying the strengths and weaknesses of your design and interaction patterns.

Users may interact with wireframes, prototypes, betas, or MVPs, depending on the product. Study participants should be thoroughly vetted against the target audience’s criteria. Their feedback helps shape a product that is intuitive from a user’s perspective.

At the same time, your users do not mind readers. Their feedback is very valuable, but their intuition should be treated with a degree of skepticism – the “observer effect” may be at play here.

Planning, Execution, and Adjustments

The data collected in a product study is only helpful if it is implemented. Goals and recommendations can change depending on the information received. This results in an iterative cycle in which data is collected, analyzed, and continually updated.

If it turns out that a specific strategy or goal was ineffective, change it. The path from an idea to a successful product launch is rarely straightforward. Let the data drive the process.

Focused on Customer Experience

As research and development costs go down and quality goes up, the only thing left to focus on is the customer experience.

In the future, new technologies and industry trends (such as artificial intelligence or machine learning) will increasingly be used in digital product research. As they evolve, they will support the research process and create new opportunities, pathways, and markets.


Said this, we believe that the most innovative way to plan for the future of product research is to use a tool we have always had access to – collaboration.

 There is no substitute for old-fashioned teamwork: working together to solve challenges and overcome obstacles.