How to Create a Customer Experience Dashboard in Google Analytics with AI

A great customer experience (CX) feels seamless, but tracking it can feel like piecing together a complex puzzle. While you might be comfortable looking at traffic and bounce rates, a true customer experience dashboard in Google Analytics tells a much richer story about how users really interact with your site. This article will show you which metrics actually matter for measuring CX and how to build a dashboard in GA4 and use its built-in AI to find valuable insights.

What Exactly Is a Customer Experience Dashboard?

Unlike a standard report that just shows website traffic, a Customer Experience Dashboard focuses on the quality of a user’s visit. It helps you answer critical questions that go beyond simple page views:

Are visitors finding what they’re looking for easily?
Is the technical performance of our website frustrating them?
Which content and features are they engaging with most?
Are they becoming loyal, returning customers or leaving after one visit?

Think of it as the difference between counting how many people walk into a store versus understanding what they look at, whether they ask for help, and if they leave happy. By monitoring specific engagement and behavior metrics, you get a clear picture of user satisfaction and can pinpoint areas for improvement.

Key Metrics for Your GA4 Customer Experience Dashboard

To build a useful CX dashboard, you need to track metrics that cover the entire user journey, from their first impression to their decision to come back. Here are the essential metrics to include, broken down by experience category.

1. Acquisition Experience: The First Impression

How users find you sets the stage for their entire experience. A visitor arriving from a targeted ad has different expectations than someone who found you through an organic search.

User acquisition (Source / Medium): This shows you which channels (e.g., organic search, paid social, email) are bringing in visitors. A better experience means you're attracting the right audience who is more likely to engage.
Landing Page Performance: Your landing pages are your digital storefront. Track "Views" and "Engagement rate" for top landing pages to see if your initial pitch is compelling or if users are leaving immediately.
New vs. Returning Users: A healthy balance is key. New users show your reach, but returning users are a strong signal of a positive experience that keeps them coming back for more.

2. On-Site Engagement Experience: Did They Find Value?

Once visitors are on your site, are they navigating with ease and finding value? These metrics tell you if your content and design are hitting the mark.

Engagement Rate: This is GA4’s successor to bounce rate. It measures the percentage of sessions that lasted longer than 10 seconds, had a conversion event, or had at least 2 pageviews. A high engagement rate suggests visitors are an active part of your website, not just passively visiting.
Average Engagement Time: This tells you how long your website held a user’s attention in the foreground of their browser. Longer times on blogs, case studies, or product pages are strong indicators of a good experience.
Event Count by Event Name: Are users taking the actions you want them to? Track key events like form_submission, video_play, or file_download. A high count for these events shows your calls-to-action and content are effective.
Site Search Analysis (Views per user, search term): If you have a search bar, what are people looking for? A high volume of searches can reveal content gaps or navigation difficulties. The terms they use are a direct line into what they want and can't find.

3. Technical Experience: A Smooth & Fast Journey

A slow, buggy website is one of the quickest ways to ruin the customer experience. While Google Analytics doesn’t measure site speed directly, it gives you clues about technical performance.

Users by Device category: Look at your engagement and conversion rates on desktop, mobile, and tablet. A significantly lower rate on one device is a red flag that you have a major UX issue on that platform.
Users by Browser: Similar to device category, poor performance on a specific browser like Chrome, Safari, or Firefox could point to a technical bug that needs fixing.
Views by Page path and Screen class: Slow load times might become noticeable in unexpected "exit rates" from certain site pages. Note: If you want to dive deeper into performance stats like Core Web Vitals, you'll want to sync your Google Search Console to your Analytics views.

How to Build Your Dashboard in Google Analytics

In GA4, the primary reporting interface can be customized to act as your centralized dashboard. This involves creating new reports and adding them to your main navigation menu so your CX insights are always a click away.

Here’s a simplified way to create and save a new report showcasing your CX metrics:

Navigate to the Reports section in your GA4 property.
On the bottom of the left-hand navigation, click on Library. This is where all reports are stored and where you can build new ones.
Click on the + Create new report button, and then select Create detail report.
You can start from a blank template or use an existing one (e.g., "Pages and screens") as a base. Let’s start with a blank report.
Choose Your Dimensions and Metrics:
- On the right-hand panel, click Dimensions. A dimension is what you are measuring (e.g., Page path, Source / medium, Device category). Add relevant CX dimensions by clicking "Add dimension."
- Next, click Metrics. A metric is the number associated with that dimension (e.g., Views, Engagement rate, Conversions). Add your chosen CX metrics like 'Engagement Rate,' 'Users,' and 'Conversions'.
Visualize Your Data: You'll see a table automatically populate. You can change the main visualization to a bar chart or line chart at the top right of your chart area for at-a-glance analysis.
For example, you could create a simple “Landing Page CX” report with “Landing page” as the primary dimension and “Engagement rate,” “Conversions,” and “Average engagement time” as your metrics.
Click Save in the top-right corner. Give your report a descriptive name like "Customer Experience - On-site Engagement."
Add to Your Navigation: To make it a permanent part of your dashboard, find the "Life Cycle" or "User" collection (whichever makes sense for your flow), select "Edit collection" and find the new report you created to add to the dashboard navigation on your left.

Repeat this process to build several simple, focused reports that cover Acquisition, On-site Engagement, and Technical Experience. By organizing them under one Topic in your reporting collections, you've effectively created your GA4 dashboard.

Using GA4’s Built-in AI for Smarter Insights

Google Analytics isn’t just a static reporting tool. It has AI and machine learning features built-in that can help you dig deeper into your customer experience with less manual effort.

The "Ask Analytics Intelligence" Search Bar

The search bar at the top of your GA4 property is your gateway to quick, AI-powered insights. You can ask it questions in plain English instead of manually building a report.

Try asking questions like:

Show me users from the United States last month on mobile
Which landing pages have the highest engagement rate?
Compare conversions from Organic Search vs. Paid Search for January

The AI will instantly generate a report card answering your question. This is perfect for getting quick follow-up answers without having to interrupt your workflow to build a whole new report from scratch.

Anomaly Detection and Contribution Analysis

GA4's AI constantly monitors your data for you. When it finds a statistically significant spike or dip in one of your metrics, it will flag it as an "Insight".

For example, you might get a notification that "Conversions from mobile devices in London decreased by 45% yesterday." Not only does it tell you what happened, but you can also click into the insight to perform "contribution analysis." The AI will then analyze other dimensions to suggest why it might have happened (e.g., "This was largely driven by a drop in traffic from your 'Summer Sale' campaign). Anomaly Detection provides you with powerful insights that you may not have been looking for. This is extremely valuable for catching technical issues or campaign problems that are harming the customer experience.

The Limits of a GA4-Only Approach

While a GA4 dashboard is powerful, it only tells you part of the story. The customer journey doesn’t begin and end on your website. What about the email they received before they clicked? The ad they saw on Instagram? The sales call logged in your CRM?

GA4, by itself, can’t easily connect your on-site behavior to data from platforms like Shopify, Salesforce, HubSpot, or Facebook Ads. Answering a seemingly simple question like, “Which creative did most of leads that converted after 6 months view?” can quickly become a massive project involving CSV downloads, spreadsheet wrangling, and hours of manual work.

Final Thoughts

By focusing on metrics that reflect user behavior and engagement — not just traffic — you can build a powerful Customer Experience Dashboard directly within Google Analytics. Using GA4's native reporting and its AI-powered insights feature gives you a clear view of where your website is succeeding and where users might be running into friction.

As you get more sophisticated, you’ll find that connecting your GA4 data to other sales and marketing platforms is the next step. At Graphed, we built an AI data analyst to solve this exact problem. You can connect sources like Google Analytics, Shopify, Facebook Ads, and Salesforce in a few clicks. Then, you just ask questions in plain English, like, "Show me a dashboard of the full customer journey from Facebook ad click to Shopify purchase, and segment it by campaign," and we build the dashboard for you instantly. Instead of spending hours wrangling data, you can spend your time acting on insights with Graphed.