In the beginning stages of a project, before any design begins, UX designers must at the forefront, understand their audience. Then comes a delicate balance of examining their client’s business goals, coordinating with various stakeholders, marketing teams, developers, and sometimes other designers.

UX design becomes most effective when the design team has access to quantitive and qualitative tools. In short, quantitive tools are expressed numerically, like Google Analytics. Conversely, qualitative tools look at behavior, like HotJar’s heatmap tool. These are effective tools in helping shape a more accurate and detailed representation of the user.

In this post, we’ll discuss how the quantitive tool Google Analytics helps UX designers make decisions based on various metrics, and why those metrics are important.

1. Audience

This is the section you’ll gather data on user demographics, language & location, behavior (new and returning users, frequency & recency, engagement), and what type of browsers and devices they are using. Google Analytics offers a fully functional demo account to experiment with data. You can view the audience overview here.

Important questions to guide design decisions:

1. What is the most common age group?
2. Are there other common languages besides English to account for?
3. What is the ratio between new and returning users?
4. What is the number of sessions per user (and what is the length of that session)? A low session duration and high bounce rate tell us the user isn’t finding what they need.
5. What’s the average bounce rate (single page sessions with no interaction)? A high bounce rate could mean the user found what they were looking for quickly. However, it could also mean that the user didn’t engage or find what they needed and left.
6. What types of devices (desktop, tablet, mobile) are most commonly used? How has this fluctuated over time?

2. Behavior

Behavior insights give designers valuable data on what pages, interactions, and content users are engaging with. More specifically, designers can collect data on what pages users are entering the site through (landing page) or leaving on (exit pages), search terms, site speed, scroll depth, and the success or failure of micro-interactions (through events).

The behavioral flow tool gives a valuable visualization of the path users take from one page or event to the next. This insight allows designers to track the success of a specific flow or task. For example, if a user went right from a product page to checkout without any complications. Conversely, if there were roadblocks to get from the product page to checkout, this report can help designers identify the issue.

Important questions to guide design decisions:

1. What is the most popular/least popular site content?
2. What search terms are users querying?
3. Are users interacting with specified events in a way you’d expect? What is the level of engagement with downloads, video plays, and CTA’s, etc.?
4. What is the average page load time and what factors are playing into this?
5. What are the most common search terms and on what page did a search occur? Was a user able to find what they needed or did a failed search cause an exit?
6. Is the path a user is taking to achieve a goal seamless? Can they easily find what they need without getting stuck and exiting?

3. Event Tracking

The Event tracking tool allows designers to track specific actions like clicks on CTA buttons, forms, downloads, video plays, and other micro-interactions otherwise difficult to track. Using the event tracking and behavioral flow tools in tandem can also inform designers on how users move through a flow more precisely (what buttons they are clicking, or missing, along the way, for example).

Events are comprised of the following components: category, action, label, and value. Here’s an example of what type of values could be assigned to the components:

• Category: Video
• Action: Pause
• Label: Total Recall
• Value: 5

In the Google Analytics demo event flow report, you can visualize how many times an action, like “pause” occurred, browse events by category, and see which events occurred on specific pages.

Important questions to guide design decisions:

1. Are users not interacting with the CTA’s you’d expect? What could be some reasons they are missing or scrolling past this link?
2. Do important conversion pages (ie product pages) have a specific conversion goal set up? If so, what pages are offering the most value, or missing the mark?

4. Goal Tracking

Creating specific goals to track how many users completed an action, like creating an account, signing up for a newsletter, checkout items, and downloads. Goals can be tracked in one of four ways: URLs, time, page/visit, and events. Similarly to the behavioral flow, Google Analytics creates a goal flow report that visually displays how users are navigating between defined goals.

In the Google Analytics Demo Account, we see a goal flow example for a checkout process. In the report, we can identify the various sources the user is entering the cart funnel from. From the cart, there is a 70% exit rate, with the other 30% either continuing into billing and shipping or going directly into a completed purchase.

After identifying potential user roadblocks in the goal flow, reviewing the funnel gives a more granular visualization of why user friction arose. In setting up a funnel, it’s best practice to create a “funnel step” for every potential point a user can leave a session (for example, signin or payment). In the Google Analytics Demo Account, we see a funnel example that showcases where the 70% exit rate from our goal flow came from. This allows us to understand that the user was roadblocked by “signin”, likely having to create an account to continue with checkout.

Important questions to guide design decisions:

1. In the goal flow, are there any particularly high bounce rates that are unexpected to a typical user flow?
2. What is preventing a user from completing a goal?
3. What are the highest exits being attributed to?
4. Is the funnel set up correctly?

In Conclusion

Google Analytics, along with other quantitative and qualitative tools gives UX/UI designers real data that can guide the information architecture and design decisions being made. And while designers can use best practices and judgment, having access to this data is invaluable to the design process, and will make the greatest impact on user engagement and retention.