User experience is typically thought of as being an emotional and visual field – yet traditional UX principles don't provide designers with the agility that developers have with rapid development methods.
Unfortunately, these methods often put design on the backburner because some believe that "an imperfect something is better than a perfect nothing." When it comes to prototyping, there needs to be some focus on design. Fortunately, you can improve your efficiency by using data to hack your UX research.
Although there are plenty of experiments you can use to leverage this information, you don't need to be a hardcore statistician to understand the basics. You don't even need to create special scenarios specifically for testing. There're plenty of insights you can gather just from your existing prototypes or finished products.
The Customer Funnel
Whether you're trying to have users sign up for a newsletter, purchase a product, or browse certain sections of your site, the journey from beginning to your user objective is like a funnel. You'll start with a large base, but only a fraction of the base will actually go through to the end. If you're offering SaaS products for example, your checkout funnel would consist of:
- Create an account
- Select a plan
- Enter payment information
- Enter billing information
- Confirm the information
- Show a thank you message and offer an upsell
Reducing lost conversions
The funnel concept is simple, yet just like a sieve, users are going to leave at each level. To reduce the drop-off, you'll need to find the friction points and come up with the solutions by using your data.
Sure, it's a bit dry at times, but analyzing the qualitative (what causes the action) and quantitative data (why the action occurs) is how you'll stand out from the competition. It's simply a matter of creating a guess of what you think would happen if you tried fixing a problem a certain way.
When you're figuring out how to begin troubleshooting, you need to speak with your users to pinpoint their frustrations. From there you'll have immediate direction on improving your offering.
Of course, user interviews only work in small batches. If you're rapidly building the solution, you'll have to iterate, measure, analyze, and repeat the process for an accurate overview of what's going on.
Using the checkout funnel example from before, you'll want to focus on small tweaks during product development. Something as simple as a promo code field might be doing more harm than good. You might lose conversions because customers are leaving your site to find coupon codes, and then not coming back.
With lean UX, it makes sense to run A/B tests on pages with and without the promo field. From there you can look at the data and stick with the winning page. From there, you repeat the process for other areas you feel need improvement.
Going beyond funnel analysis
Running data based UX tests isn't limited to checkouts and sign-up flows. The entire visitor journey on your website can be a funnel. If you're short on time or simply don't want to put the effort into full blown analysis, you also could look at a single variable and run the tests on that.
As Dave McClure mentioned in his presentation on Startup Metrics for Pirates, UX designers and product managers need to focus on five key metrics: acquisition, activation, revenue, retention, and referrals.
Put simply, 80% of your time should be on optimizing existing features whereas 20% should be on new feature development. It's a win-win-win for developers, users, and yourself since it keeps things manageable for everyone.
On a similar note, you'll want to minimize the steps to complete tasks since each one adds more room for drop offs.
Don't become a data scientist just yet…
Of course, data isn't the end all be all when it comes to UX work. It isn't going to replace your need for graphic design, enable you to anticipate all user needs, and it isn't going to tell you what to build.
Using data for lean UX development will, however, save you money, boost morale, and enable your teams to focus on being productive rather than constantly reinventing the wheel. The benefits from testing also decline after each round.
Performing user research has become cheaper than ever, yet it's still expensive. There's no cut and dry rule on when to stop your user research. Klien sums it up simply by saying you don't want to measure something if it doesn't directly affect user behavior.