Setting your objectives

- [Presenter] The success of your research efforts really begins before you collect a single piece of data. You need to set clear research goals and design the proper kind of study to answer the questions at hand. If you don't capture the right sort of data, it doesn't really matter how thorough your process is. This seems obvious, but especially for those of us who are new to research, it's easy to get caught in the trap of applying the same methods all the time. I walk through choosing the right kind of research method in my UX Research Fundamentals class. So feel free to check that out if you need a refresher. In short, you'll need to first consider the stage of product life cycle and associated risks, business goals, what you already know about users and solutions and any hypotheses about problem areas to come up with a list of potential research questions. Then you'll need to identify a research topic and delineate specific goals to explore. It's okay if you have a wide range of open questions, but you want to be explicit and prioritize just one area because different research methods are best suited for different kinds of questions. Your research goals will determine what methods you employ, and the more granular your goals, the easier it will be to plan an effective research effort, and the easier it will be to analyze that data later. If you're in exploration phase where you don't know your users, their contexts, or what problems to solve, your focus is necessarily broad. But you can still identify and prioritize research goals by figuring out what is most important to you for the project or effort. For instance, let's say you're working on a mobile application for a grocery store, and they want to provide some sort of in-store benefits for frequent shoppers. You'd want to explore things like people's shopping patterns and frequency, what, if any, planning or organizational tools they use while shopping, and what sort of perks they find valuable. Sometimes it's easier to identify and rule out the things that you aren't as interested in or that you don't need to explore, like maybe you already have really good data about what products sell best on different days of the week, or decide that you only want to focus on people who spend a certain amount per week. If you're doing more solution-focused work, it can be especially useful to craft a hypothesis to frame your research questions and narrow the scope of your effort. I like to use the following template to set a hypothesis. If we do, build or provide X thing, then these people will do some sort of desirable outcome. We'll know that this is true when some kind of actionable metric. The do, build or provide X thing describes the solution or service you might offer. It might be as high level as what channel to use for communications or as detailed as which specific interaction you'll use on an interface. The these people are a brief description of your target user. You may start with guesses informed by initial research or have empirically driven definitions of your user base. Maybe you're doing this research to flesh that out. The do some desirable outcome component is what you want your user to do, like maybe making a purchase. This should be an indication of your progress towards business success and help you make a decision for future direction. For instance, if I'm working on an eCommerce site, I might want users to increase their order size or the number of items purchased. Again, this sort of hypothesis framework is most helpful when you're assessing a potential solution. When you're in a very exploratory or formative stage, you don't want to limit yourself to specific solutions, but you can still narrow your focus of exploration. Ultimately, setting clear research objectives will bring clarity to everyone about why you're doing research and ensure that you're collecting the right sort of data to answer your open questions.