Google's data-driven approach to superior user experience, revisited

When Google first came on the scene in the late 1990s, Internet search engines were a dime a dozen, and the space was led by the likes of AltaVista, Yahoo and Lycos. But Google seemed to understand something a little more intuitively than the others, which propelled them ahead. Users wanted speed, simplicity and elegance in their searches.

So what can the company that mastered the art and science of UX all the way to the top of the global business world tell us about UX these days?

Appcue's Ty Magnin recently took an informative walk-through of Alphabet/Google's "HEART" approach to managing and providing a superior user experience. The HEART approach (Happiness, Engagement, Adoption, Retention, and Task success) was put in practice several years ago. The guidelines make a great deal of sense in terms of staying on top of user preferences. "What I find so appealing about HEART is that it pins the discipline of user experience to revenue-driving metrics--a connection I previously struggled making," says Magnin.

Google successfully made the connection between UX and the business through effective use of data analytics. In a paper they published a few years back, Kerry Rodden, Hilary Hutchinson, and Xin Fu (now with LinkedIn) described Google Research's process. HEART, along with a process called Goals-Signals-Metrics, was created as a "framework and process for defining large-scale user-centered metrics, both attitudinal and behavioral," which is suitable for any organization interested in data-driven UX, they said.

Google's Rodden provides a more recent update on HEART and GSM in GV Library, noting that "we like to think of large-scale data analysis as just another UX research method."

Here is how that breaks down, as explained by Rodden and the Google team:

Happiness. This applies to attitudinal metrics, the authors note, including aspects such as "subjective aspects of user experience, like satisfaction, visual appeal, likelihood to recommend, and perceived ease of use." They advocate the use of well-designed surveys to "track the same metrics over time to see progress as changes are made." This has helped Google designers determine if negative reactions to new features has more to do with change aversion, or actual declines in satisfaction.

Engagement: This encompasses the degree of users' frequency, intensity, or depth of interaction over some time period." Examples of metrics, the team continues, may include "the number of visits per user per week, or the number of photos uploaded per user per day."

Adoption and Retention: These metrics "can be used to provide stronger insight into counts of the number of unique users in a given time period (e.g. seven-day active users),addressing the problem of distinguishing new users from existing users. Adoption metrics "track how many new users start using a product during a given time period." Retention metrics "track how many of the users from a given time period are still present in some later time period."

Task success: The metrics coming out of this phase tie into more "traditional behavioral metrics of user experience, such as efficiency (e.g. time to complete a task), effectiveness (e.g.percent of tasks completed), and error rate." The way to track and measure task success is through remote usability or benchmarking studies that look at specific tasks, the Google team states.

The key to implementing a HEART methodology is the ability to articulate and track goals, signals and metrics, the Google team adds. Defining goals helps to figure out what metrics are best applied, Rodden says. "Next, map your goals to lower-level signals," she says. "How might success or failure in the goals actually manifest itself in user behavior or attitudes?" Then, refine those signals "into metrics you'll track over time or use for comparison in an A/B test."

At the time Rodden and her team wrote the original paper, they had applied the HEART framework and the Goals-Signals-Metrics process "to more than 20 different products and projects from a wide variety of areas within Google."

Just as important to the data-driven process is communication, Magnin observes. "Google uses many means of communication," he says, combining "email, feedback forms, tool tips, and modals to increase the HEART of their products and drive more revenue to the fourth most valuable company in the world."