How to Create a Website Dashboard in Google Analytics with AI
Building a useful website dashboard doesn't have to be a frustrating, time-consuming task. Instead of getting tangled up in complex menus or fumbling with spreadsheet exports, you can use AI to build exactly what you need with simple, everyday language. This article will show you how to move past the manual grind and create an insightful Google Analytics dashboard that tells you what’s actually happening with your website.
Why You Need a Website Dashboard in the First Place
Diving into Google Analytics can sometimes feel like trying to find a needle in a digital haystack. There are hundreds of reports, dimensions, and metrics. A dashboard solves this by bringing all your most important data into one place for a quick, at-a-glance health check of your website.
A good dashboard helps you:
Track KPIs without the hassle: See your most critical metrics - like traffic, conversions, and revenue - in one view, without having to navigate to five different reports.
Spot trends (good and bad) instantly: Is traffic suddenly dropping from a key channel? Are conversions on the rise? Visualizations make these patterns jump out immediately.
Make data-driven decisions faster: When your data is organized and easy to access, you spend less time gathering it and more time acting on it.
The problem is that traditional methods for building these dashboards are often clunky. GA's built-in dashboard feature is limited, and tools like Google Looker Studio, while powerful, have a steep learning curve. Many marketers find themselves resorting to the same old routine: download a few CSVs, wrangle them in Excel or Google Sheets, and build charts manually. This process is tedious and prone to human error, and by the time you're done, the data is already old.
What Key Metrics Should You Include?
Before you build anything, you need to decide what you want to measure. A dashboard is only as useful as the metrics it contains. While every business is different, here’s a solid starting point for a high-level website performance dashboard using Google Analytics data.
Acquisition Metrics: How People Find You
These metrics tell the story of where your website visitors are coming from. They help you understand which marketing channels are working and which ones need attention.
Users & New Users: Users shows the total number of unique people who visited your site, while New Users isolates those who have never been there before. Tracking both helps you gauge audience growth and loyalty.
Sessions by Channel: This is a must-have. It breaks down your traffic sources into categories like Organic Search, Paid Search, Direct, Social, and Referral. You can immediately see which channels drive the most traffic.
Top Referring Sources: For referral traffic, which specific websites are sending you the most visitors? This can help you identify partnership opportunities or successful PR placements.
Engagement Metrics: What People Do On Your Site
Once visitors arrive, are they sticking around and interacting with your content? These metrics tell you how engaging your website actually is.
Average Engagement Time: In Google Analytics 4, this metric measures the average length of time your website was the main focus in a user's browser. A higher number generally means your content is compelling.
Views: The total number of website screens or pages your users saw. It helps you understand overall activity on your site. This metric was previously known as 'Pageviews' and 'Bounce Rate' in Universal Analytics.
Top Landing Pages: These are the first pages visitors see when they arrive at your site. Knowing your top entry points helps you understand which content or campaigns are attracting the most attention.
Event Count: GA4 is built around events - clicks, form submissions, video plays, etc. Monitoring your key event counts lets you know if users are taking the actions you want them to take.
Conversion Metrics: Are They Achieving Your Goals?
This is where the rubber meets the road. Traffic and engagement are great, but you need visitors to take valuable actions, whether that's making a purchase, filling out a form, or signing up for a newsletter.
Conversions: Formerly "Goal Completions," this metric tracks the total number of times users completed an action you've defined as important. This is one of the most critical metrics for measuring success.
Conversion Rate: This percentage shows you how effectively you're turning visitors into leads or customers. It provides context that raw conversion numbers alone can't.
Total Revenue & Transactions (for ecommerce): If you sell products online, these are vital. They show the direct monetary impact of your website and marketing efforts.
Your Options for Building a Google Analytics Dashboard
1. The Classic GA Custom Dashboards
Google Analytics has a built-in feature for creating custom dashboards. You can find it under Reports > Library and then by creating a new blank report. It’s a decent starting place for basic monitoring. You can add widgets to display metrics like Users, Sessions, and Conversion Rates.
The Catch: The customization is fairly basic. Your visualization options are limited, you can only add so many widgets, and they aren't as interactive or shareable as modern alternatives.
2. Google Looker Studio
Looker Studio (formerly Data Studio) is Google's more advanced, free data visualization tool. You can connect it directly to your Google Analytics account and build much more sophisticated and visually appealing dashboards. It offers superior customization, a wide range of chart types, and better sharing capabilities.
The Catch: There is a significant learning curve. To become proficient, you might need to invest hours, if not days, watching tutorials to learn about data connectors, calculated fields, filters, and design settings. For a busy marketer, founder, or analyst, this is often a major roadblock.
3. Using Natural Language AI (The New Way)
A new, much simpler approach is emerging: using AI tools that connect to your Google Analytics account and allow you to build reports and dashboards with simple, conversational language. Instead of clicking through menus or configuring charts manually, you just type what you want to see.
This method removes nearly all technical barriers. If you can ask a question, you can build a dashboard. It combines the power of a tool like Looker Studio with the ease of use of a simple chat interface.
How to Build a GA Dashboard with AI: Step-by-Step
Building a dashboard with an AI-powered analytics tool completely changes the workflow from being a technical task to a creative one. Here's a general guide for how it works.
Step 1: Securely Connect Your Google Analytics Account
First, you'll need to grant the AI tool access to your GA data. Modern tools use a secure, one-click authorization (OAuth) process. This means no digging around for API keys or complicated setup procedures. You simply log in with your Google account, select the GA property you want to work with, and you’re ready to start analyzing. The tool will begin syncing your historical data in the background.
Step 2: Start Asking Questions in Plain English
This is where the magic happens. Instead of dragging and dropping components, you simply describe the chart or report you want. You don't need to know technical jargon or data-speak, just ask a question as if you were talking to a data analyst.
Try prompts like these:
"Create a KPI dashboard for last month showing total users, revenue, and conversion rate."
"Show me a line chart of daily sessions from organic search over the last 90 days."
"Build a bar chart of my top 5 landing pages by conversions this quarter."
"I need a pie chart breaking down my website traffic by device category."
"Make a table comparing revenue and transactions by source/medium for this year."
The AI will interpret your request, query the GA data, and generate the appropriate visualization - whether it's a scorecard, a line chart, a table, or something else - instantly.
Step 3: Refine and Dig Deeper with Follow-Up Questions
A great dashboard almost always sparks more questions. This conversational approach makes it incredibly easy to explore your data further. Once the initial chart is created, you can continue the conversation to tweak it or uncover more details.
For example, if you created a chart of traffic sources, you could ask:
"Okay, now filter that for mobile traffic only."
"What caused the traffic spike last week?"
"Change that to a week-over-week view."
"Show this as a percentage of total traffic instead of a raw number."
This iterative process allows you to start broad and then drill down into specific segments and insights that you might have otherwise missed. It turns analysis into an interactive conversation, not a static report-building exercise.
Final Thoughts
Creating a website performance dashboard no longer has to be a chore you put off until the end of the month. Using AI and natural language completely reimagines the process, allowing you to move from a raw question to a polished, professional dashboard in minutes instead of hours.
At Graphed, we built our platform specifically to solve this problem. We provide the AI data analyst that lets you connect your Google Analytics account in seconds and create live, real-time dashboards just by asking questions. Instead of wrestling with clumsy interfaces or spending a weekend learning a complex BI tool, you can simply describe what you want to see, and our tool builds it for you. This frees you up to spend less time on manual reporting and more time making decisions that will actually grow your business.