Picking New Product Features? Let Data Light Your Way
A quick guide for making choices that are backed by data when picking and prioritizing features for your product.
When a client comes to Viget looking for smart ways to improve their digital product or site by revising or enhancing their feature set, we have a lot of recommendations. We can help improve their code, redesign their visual identity, reimagine their user experience. Regardless of our methods, however, we always strive to use data to inform our decision-making. In fact, we frequently have projects in which data and testing serve as core focuses.
But what do you need to do first? According to Airbnb’s Ian MacAllister, prioritizing potential features is key. Here’s a quick guide for confidently making choices that are backed by data when picking and prioritizing features for your product.
Before You Start
Having the right tools to organize yourself is essential no matter what type of analysis you’re planning. Project management software such as Trello, PivotalTracker, or Redmine will allow you to categorize features, set timelines, and create lists to your heart’s content. You and your team will be on the same page, maximizing efficiency and expediting the iteration and testing process.
Qualitative Tools (a.k.a. Know Your Audience)
Maybe you already have a set of internal goals for your product. You might also have preliminary feedback from users of your app or visitors to your site, or better yet a list of features that your clients or customers have specifically requested. But what do you do with all this information?
Roger Graham at Flip shared with me how they go about obtaining and prioritizing this feedback. “We separate almost everything into two categories: core experience, and additional features… Once we have core experiences laid out, we look at what additional features to build first largely based on user feedback. We use Olark for live chat on the site, so people can give us direct feedback on what they want.”
In terms of source data, nothing beats real-world testing by users. While there are many methods of user research available, some require more time and effort, and therefore money, to complete. (Here are our tips on how to save time during research.) Information about how users are interacting with your product should always be combined with how you, and your company, can manage and implement your chosen feature improvements. As others, like Intercom’s Des Traynor, have pointed out, laying out potential projects on an effort vs. impact matrix can be tremendously helpful.
According to Ketaki Rao at Jivox, “... we consider several data points including revenue impact, requests from customers, man hour (workflow efficiency) impact, usage metrics, competitive studies, infrastructure costs and cost savings” when prioritizing product features. They also utilize user surveys and interviews to add to their dataset. Ketaki adds that this approach “not only guides our product team with prioritizing objectively, it also helps us make our case as we evangelize these new features internally and externally.”
And although insights from users can be instrumental in new feature development, ultimately, product managers and owners are in a position to come up with features that users might not even know they want yet. As Jay Patel from FlexReceipts explained to me, it’s important to understand your users to such a degree that you can anticipate their needs, search for “gaps” in their experience, and innovate potential solutions they might never have thought of. Automating common processes so as to make them “effortless” for visitors is key to creating an experience that will keep people coming back and loving your product.
Quantitative Tools (a.k.a. Numbers FTW)
In terms of the best tools for testing and analytics, you probably already know about the great Google Analytics, of which we are huge fans (and a Certified Partner). But many aren’t aware of GA’s built-in internal site search tracking. As our very own Paul Koch tells me, “It’s one of the most underused features. We do so much ‘reading the tea leaves’ to try to figure out what people want, but often people directly type it into the search box.” We also use our home-grown tool, Search Words, to identify broader keyword patterns that may not immediately reveal themselves in the standard data.
There are a lot of other great analytics platforms out there depending on your needs. Among the ones we use, recommend to clients, or have heard good things about:
Optimizely - Helps you test features on random samples of your website visitors to gauge impacts on conversions.
Crazy Egg - Shows you heatmaps of where people are clicking and how far they are scrolling, which helps you figure out what’s popular.
Mixpanel - Can be used in conjunction with GA to easily see user flows.
Inspectlet - Also works with GA to visualize user behavior on sites.
Segment - Synchronizes analytics data across platforms.
For more on all the ways we can employ data and analytics help you understand your users and determine how to develop new features that will achieve both their goals as well as your product team’s, check out our Analytics & Optimization page.