Guide to researching new products & testing concepts

The more research platforms that UX researchers rely on, the more the field has become dependent on tools versus expertise. The range of new platforms are astonishing in how easy they make it to collect data about interactions and recruit participants. Overall, they’ve enabled research activities to scale and have expanded the influence of researchers within organizations. 

Researching new products requires a different mindset and toolkit. New product research seeks to answer the unknown; it requires us to be exploratory, not evaluatory. This distinction is important as you begin a project because we all have an urge to prove what we know, rather than seek out other possibilities. 

This approach will enable researchers and product managers to shift from gathering insights about features towards finding new product opportunities.

1.  Use a Modified Design Thinking Double Diamond Model

For all the grief that design thinking has earned as a poor quick fix, the double diamond is the perfect model to frame innovation research. Popularized by the British Design Council in 2005, the double diamond conceptualizes every design activity as a process of divergent thinking followed by convergent thinking.

For what design thinking fails for being a wild oversimplification of the design process, it shines a light on the importance of problem definition. The hardest part of researching new products is being comfortable with the uncertainty of where the process will net out. 

At the beginning of an innovation research project, what matters most are the desired outcomes —acceptance criteria— and the stakeholders’ assumptions about possible problems and solutions. The modified double diamond guides researchers through divergent activities to learn the unknown, followed by convergent activities to refine lessons learned into a point of view. 

The term point of view is important in the context of innovation research. No level of exploratory research can yield a solution. That’s the fallacy of design thinking and its tendency to over-promise. Depending on your level of research and quality of findings you may yield a proof of concept for a solution or a short list of possible solutions.

2.  Build a plan that recognizes the benefits and limitations of each form of research

There is no right or wrong research methodology to use, there only are limitations to each. When creating your research strategy and plan, detail out the desired outcomes and assumptions provided by leadership. You’ll now need to map out a set of possible paths from uncertainty to resolution. This will require diving into your mixed methods toolkit and considering the benefits and limitations of each form of research.

You’ll also need to consider these key insights we’ve learned from leading innovation research projects over the past ten years at PH1 Research for clients like Spotify, Microsoft, Indigo and more:

1. Spend more time researching what participants use and why, rather than exploring ideas

2. How you frame questions and the part of a participant’s life you explore matters: Behaviours > Preferences > Intentions

3. Who you speak to matters as much as what you ask them, so recruit very carefully and strategically

4. Assume you’ll be faced with uncomfortable truths that will require you to build alignment with stakeholders anew

The key lesson here is that your research strategy must use mixed methods (quantitative and qualitative). Each offers a unique ability to excel at divergent and convergent thinking. 

3.  Focus on relevancy by weaving design into your double diamond

Research participants can only comment on what they understand. 

If you’re asking a user how to improve an onboarding experience or customer support tool they look at it one of two ways:

1. Which pain points have I experienced and wish could have been handled differently

2. What have I used elsewhere

The missing piece here is that research participants need relatable prompts to help them imagine new possibilities. These can be either: a) Examples of competitors and international peers; b) Startups and challenger brands from related industries and c) Rapid prototyping of possible solutions.

Our team tends to do all three. The first two are well-suited to the first diamond and the third, design concepts, should be central to the second diamond. So yes, designers are likely necessary for your innovation research to succeed and they’ll likely be the key to your ultimate breakthrough. Make sure to bring on a designer who excels at rapid prototyping, moving quickly through variants of ideas and who operates well at mid-fidelity.

4: Test and iterate until you reach a high level of confidence

Innovation is messy, even messier than you imagine. Where standard product research generally provides high-quality insights the more research you do, innovation research can be wildly contradictory. One day to the next your hopes can be completely crushed by a new finding.

This is because innovation research is a multivariate problem in a complex and speculative model. Solve for one variable and it has a series of cascading effects elsewhere. 

The cliche example from testing is whether the colour of a CTA button has a positive effect on conversion. That problem with a single variable. Create an experiment to control for that single variable—by conducting tests where you don’t change anything besides the button colour— and you can solve the question. If the question is how to improve conversion, then you are experimenting with content, design, interactions, intent, and user flows. Answering that problem with a high level of confidence requires either modelling or testing many variations against a control or incumbent. 

While few can afford or have the expertise to go down the big data modelling route, testing variations will yield high-quality results when you plan for enough iterations. 

For that reason we recommend phasing the testing process into four stages:

In conclusion

Researching new products is probably the most exciting form of user research. It challenges you to think like a strategist and explore the full research toolkit. You’ll look at the double diamond model of divergent and convergent thinking with renewed optimism. And you’ll quickly learn how to make the future achievable and empowering.

If you have any questions or need support on your next project, please contact arpy@ph1.ca