The Research Funnel
I'm creating a research knowledge base for those people who conduct, commission or use research across Monotype. It'll be a place to share ideas, resources and examples of good practice. A place we can talk about the research we're doing and how such research can inform decision making. With only one dedicated researcher (me) and some such as the amazing Dr Nadine Chahine, who are part researcher, part designer but many people for whom research forms part of their job, it's important to support a culture of research and insight at Monotype.
I was recently drafting a research plan for some of our products and services and came up with a simple category system for commissioning of all future research. I thought it might help everyone know what kind of research they were working on and what the likely outcomes would be. I called it the Research Funnel. Here's a (slightly messy) sketch I did:
Research should be designed to address a problem - either to solve it or to get closer to a solution. The funnel categories describe research as something that can and should happen at every stage of a product/project lifecycle and describe how close you are to the problem or solution. Category 5 = furthest from the problem and Category 1 = closest to the problem. It also describes how broad the data collection should be - how wide or deep to go.
If we use our existing product Gridset as an example, here are some ideas of how research could be used along the whole lifecycle of the product.
A category 5 project might be to research a completely new market or underserved customer group. For example, you want to develop a web app for making Responsive Web Design easier. You might have some hunches or assumptions to test - for example, grids and layout are difficult in RWD. You might have some ideas how this might affect different people in different ways - for example, a designer designs a layout and then the front end developer has to work out how to make it work for different screen sizes. You have some broad areas to investigate and an idea of who to speak to. After doing a piece of research like this, you might come up with an idea for an app - Gridset.
A category 4 project might be to do some research to define the strategy for your new app or to define the target users more closely. For example, you have come up with the idea of an app that helps with Grids but you want to create some personas and empathy maps to encapsulate the target users and user needs.
An example of category 3 project might be once the app has launched, to get some broad feedback of the whole service via a customer satisfaction survey. The outcome might be a set of trackable measures to look at over time.
From your customer satisfaction survey, you may notice a lot of requests for a particular feature - for example, adding SASS capabilities. During the design process for this new feature, you might conduct remote user interviews to get some feedback on your prototype. This would be an example of a category 2 project.
You may have noticed a drop off in the sign up process so you decide to do some A/B testing on the copy used in the user flow. The outcome would likely be a clear difference and therefore a solution but it might be that the results were much the same. In this case, more research or another approach would be needed. This would be an example of a category 1 project.
The way I have described the flow here seems to imply that each stage happens in order but of course research can happen in any order in the funnel - this category system just describes how close you might be to the problem or solution and what the likely outcomes might be. I wrote about using some of these different methodologies - both in-house and agency side - on 24Ways last year. This is the next stage of gathering resources for my knowledge base. Examples, ideas and documentation for how to carry out these different methodologies.
I'd be interested to find out what you think of this system? Is this way of thinking about research helpful? Does it work in practice? Particularly for non researchers - maybe designers (or developers) carrying out their own research. Does this help you come up with an appropriate research solution for a problem you need help with? Does this make you think beyond just the same old methodologies such as user interviews or personas? What can I do to improve this?