The sunset of Universal Analytics in June marks a significant shift in how businesses manage and analyze their website data. As Google transitions to its GA4 platform, preserving historical data and ensuring its accessibility for future analysis becomes crucial. Failing to backup your Universal Analytics data risks losing valuable insights that could inform strategic decisions and hinder your ability to track long-term trends.
However, backup is just one part of the solution. To continue deriving meaningful insights from your data, you need a well-structured data model. This data model acts as a bridge between raw data and actionable insights, enabling business and marketing teams to access and interpret information easily. By having data structured effectively, you can recreate the vital aspects of Universal Analytics, allowing you to visualize past trends, analyze user behavior, and track key performance indicators.
To address this challenge, Maya has developed a Power BI template that empowers businesses to unlock the full potential of their backed-up Universal Analytics data. This template serves as a comprehensive solution for analyzing and visualizing your historical data, enabling you to gain actionable insights and make data-driven decisions with ease.
Why Should you Use a Power BI Template for Universal Analytics from Maya?
Our Power BI template is designed to make the transition from Universal Analytics a breeze, ensuring that your historical data remains safe and accessible while enabling you to continue deriving meaningful insights.
- Save time and resources: Say goodbye to the hassle of extensive manual setup and hello to efficiency. Maya’s Power BI template eliminates the need for you to start from scratch, allowing you to quickly access and analyze your data.
- Ensure continuity with Ease: Maya’s BigQuery flow automatically backs up your Universal Analytics data, giving you peace of mind knowing that your historical insights are secure in Maya’s or your own database. It’s like having a secret vault where you can store all your precious data, without worrying about losing it in the midst of the Universal Analytics sunset.
- Visualize Your Data Like a Pro: But what good is backed-up data if you can’t make sense of it? That’s where Maya’s Power BI template comes in. We’ve crafted a data model with visualizations that feel as familiar as your favorite pair of jeans. The intuitive design mimics the look and feel of your old analytics reports, so your business and marketing teams can continue their workflows without missing a beat.
- Integrate More Data for Deeper Insights: While having the Universal Analytics data is a powerful play on its own, with Maya, you can easily connect data from other sources, such as advertising platforms, CRM systems, or e-commerce platforms, to gain a more comprehensive view of your business performance.
By following these step-by-step instructions, you’ll be well-equipped to navigate the Universal Analytics sunset and continue deriving value from your historical data.
Step 1: Backup Your Universal Analytics Data
Before you even think about diving into the world of Power BI templates and fancy visualizations, there’s one crucial step you can’t afford to skip: backing up your Universal Analytics data.
Our UA data backup solution is designed to make the process as painless as possible, so you can focus on more important things (like sipping your coffee and basking in the glory of your data-driven decisions).
But why did we choose BigQuery as our backup destination? It’s simple: BigQuery is incredibly easy to set up, and GA4 already sends data to it natively. By backing up your Universal Analytics data to BigQuery, you’ll have everything in one place, making it a breeze to analyze and visualize your data. Plus, anyone with a Gmail address can have a BigQuery instance, making it accessible to everyone.
Here’s how it works: Maya’s flow connects to your Universal Analytics account and backs up all your data—we’re talking events, dimensions, metrics, to Mayas’s or your very own BigQuery instance.
And here’s the kicker: you can effortlessly export your last 14 months of Universal Analytics data to BigQuery for free. Yes, you read that right — no credit card required, no subscription, no hidden costs. And if you want to go the extra mile and backup 5 years of historical data, it’s just a single one-time fee of $300.
For some more reading head over to our comprehensive guide on Maya’s UA data backup process to learn more about how it works, why it’s essential, and how you can get started today.
Step 2: Access Maya’s Power BI Template
With your Universal Analytics data securely backed up, it’s time to move on to the exciting part: accessing Maya’s Power BI template.
Getting started with Maya’s Power BI template is a breeze. Simply click the button on the left sidebar to download the Power BI data model. The downloaded file contains the templates and instructions on how to connect to your data in BigQuery.
Once you have the file, open it in Power BI Desktop. The template is pre-configured with default parameters, making it easy to connect to your data. If you have access to the dataset in BigQuery, you can load the data and save the file as a .pbix file, then upload it to your Power BI tenant.
If you don’t have access to the dataset in BigQuery or want to avoid loading the data locally, you can use the “Universal Analytics SM” .pbix file provided in the download. Simply upload this file directly to your Power BI tenant.
After uploading the file, go to the dataset settings in Power BI and set up the gateway connections for BigQuery.
Next, navigate to the parameters section and update the Project and Database settings according to your instructions.
Finally, on the Power BI workspace main page, click the “Refresh Now” button to start the data refresh process.
The downloaded file also includes the main reports you’ll need for your Power BI data model, such as Acquisition, Audience, Behavior, and Conversions. When you open each report, you may encounter an error because they are configured to have direct access to our demo Power BI, which you don’t have access to. Simply click “Edit” immediately after opening the report and select the relevant Power BI model present in your tenant. This will create a live connection to your Power BI data model. Save each report and push it to the same workspace.
Using the Power BI template online is straightforward. Once you’ve uploaded the reports to your workspace, you can access them from any web browser. Simply log in to your Power BI account, navigate to the workspace containing the reports, and click on the desired report to view it. You can interact with the visualizations, filter the data, and share insights with your team, all within the Power BI online interface.
Step 3: Exploring the Power BI Universal Analytics Template (and try our embedded live version)
Now that you have Maya’s Power BI template downloaded and ready to go, it’s time to start exploring your Universal Analytics data. But…
First a look around in the UI
Here are a few tips on the UI to show you around.
On the left side of the screen, you’ll find the Navigation Panel. This is your central hub for accessing your workspaces, reports, and other Power BI resources. Simply click on a workspace to view its contents, and then select a Report to open it.
When you open a report, you’ll see a collection of interactive visualizations that bring your data to life. These visualizations are designed to help you gain insights and make data-driven decisions quickly and easily.
In all the templates you will find settings like Set Bars and Set Lines. These options allow you to customize the metrics displayed in your visualizations. With Set Bars for instance you can choose the bar metrics e.g. Users, New Users, Pageviews etc. Set Lines can help you “draw” lines on another metric that you need to see concurrently.
All the reports include a date range selector to focus on specific time periods. To change the date range, simply click on the date selector and choose the desired start and end dates.
In all the reports , you’ll find options to select Primary and Secondary Dimensions or Measures. Dimensions are attributes that describe your data, such as page or location. Measures, on the other hand, are quantitative values, such as pageviews or number of events. WE have chosen the right combinations so you can have a familiar UI to Universal Analytics.
Finally the Filters. Filters allow you to narrow down the information displayed in your reports based on specific criteria. For example, you might want to view data for a specific campaign or focus on a particular channel. To apply a filter, simply click on the filter icon in the top-right corner of the report and select the desired criteria.
As you will see below we also embed the Power BI reports for you to tinker around. They share similar UI with what we explained earlier. You may change templates through the Pages (from Overview, to Channels etc.). You may find that towards the bottom.
About Filter and the Semantic Clustering
This is just an explainer for our clustering feature. If you noticed the screenshot above the Channel Grouping is not the vanilla grouping we know. Seeing it from up close you see that you can create groups that fit your business need. In the example below we have grouped certain domains as affiliates to track them separately, there is a branded paid search which is paid search but for branded keywords and so on.
Acquisitions > Overview Google Analytics 3 (Universal Analytics) View
The first section we’ll dive into is the Acquisitions Overview, which closely resembles the Universal Analytics interface you’re already familiar with.
The Acquisitions Overview provides a high-level view of how users are finding and engaging with your website. It’s like a snapshot of your website’s performance, giving you a quick and easy way to gauge the effectiveness of your marketing efforts.
When you open the Acquisitions Overview in Maya’s Power BI template, you’ll feel right at home. The layout and visualizations are designed to mimic the Universal Analytics interface, so you won’t have to spend hours trying to navigate a new system. It’s like putting on your favorite pair of jeans—comfortable, familiar, and ready for action.
The Acquisitions Overview is divided into several key sections, each providing valuable insights into your website’s performance. At the top, you’ll find an overview of your website’s traffic, including the Top Channels, number of Users, or Conversion. This is like the executive summary of your website’s performance, giving you a quick and easy way to see how your site is doing at a glance.
You may choose your Primary Dimension, then select a Set Metrics (for example in the image below you see Users) and on the right side you can filter the Conversions.
As you scroll down, you’ll find more detailed information on your website’s traffic sources where you may select the Secondary Dimension like the Channel Grouping we have. The Channel Grouping section breaks down your traffic by source, such as organic search, direct traffic, and referrals. This is incredibly useful for understanding where your users are coming from and which channels are driving the most engagement.
Do you remember the Conversions dimension we mentioned above? Set a Conversion and you will see the values change in the Channel Grouping section.
Give it a whirl on your own.
Acquisitions > Channels Google Analytics 3 (Universal Analytics) View
Moving on to the next page of the Acquisitions section in Maya’s Power BI template, we come to the Channels view. This powerful tool provides a detailed breakdown of your website traffic by channel, helping you understand which channels are driving the most traffic, engagement, and conversions.
Just like the other subsections in the Acquisitions section, the Channels view is designed to look and feel just like the Universal Analytics interface. You’ll find the same familiar layout and visualizations, making it easy to navigate and understand your channel data.
At the top of the Channels view, you’ll find the bar chart of your channel performance, where you may configure your metrics (as bars or lines for example) and include number of sessions, bounce rate, or conversions. This high-level view is perfect for quickly assessing the overall effectiveness of your channels and identifying areas for improvement.
As you scroll down, you’ll find more detailed information on individual channels. The Channels table provides a breakdown of each channel, including the channel name, sessions, bounce rate, and conversions. This is where you can really start to dig into the details and understand which channels are driving the best results.
You may also add more Secondary Dimensions and make it even granular or even filter it and understand how your channels are performing on a daily, weekly, or monthly basis, making it easy to identify trends and patterns in your channel data.
Check the embedded template below…
Acquisitions > Source / Medium Google Analytics 3 (Universal Analytics) View
Continuing our exploration of the Acquisitions section in Maya’s Power BI template, we arrive at the Source / Medium Page. This view provides a detailed breakdown of your website traffic by source and medium, helping you understand which specific sources and mediums are driving the most traffic, engagement, and conversions.
As with the other subsections in the Acquisitions section, the Source / Medium view is designed to mirror the look and feel of the Universal Analytics interface. You’ll find familiar layout and visualizations with easier dimension and filtering selections, making it easy to navigate and understand your source and medium data.
At the top of the Source / Medium view, you’ll find an overview of your source and medium performance. As previously you may select your bars with any metric or Set Lines with another.
As you scroll down, you’ll find more detailed information on individual sources and mediums. The Source / Medium table provides a breakdown of each source and medium. And if you want to get even more granular, the Source / Medium table provides a deep dive into each individual source and medium with filtering. Here, you can see exactly how each source and medium is performing, including the specific campaigns, keywords, and ads that are driving the most traffic and conversions.
Check this embedded template
Acquisitions > Campaigns Google Analytics 3 (Universal Analytics) View
Diving into the last part in the Acquisitions section in Maya’s Power BI template, you’ll find the Campaigns subsection. This powerful tool provides a detailed look at the performance of your marketing campaigns, helping you understand which campaigns are driving the most traffic, engagement, and conversions.
Just like the rest, the Campaigns subsection is designed to mirror the look and feel of the Universal Analytics interface.
At the top of the Campaigns subsection, you’ll find an overview of your campaign performance, including the number of sessions but you can select any metrics you like. This high-level view is perfect for quickly assessing the overall effectiveness of your campaigns and identifying areas for improvement.
As you scroll down, you’ll find more detailed information on individual campaigns. The Campaign table provides a breakdown of each campaign, including the campaign name, source, medium, and key performance metrics like sessions, bounce rate, and conversions. This is where you can really start to dig into the details and understand which campaigns are driving the best results.
Now that you learned the ins and outs have a look…
Audience > New and Returning Google Analytics 3 (Universal Analytics) View
Moving on to the Audience section of Maya’s Power BI template, we come across the New and Returning page. This insightful view allows you to analyze the behavior and engagement of your new and returning website visitors, providing valuable information to optimize your user acquisition and retention strategies.
The New and Returning subsection in Maya’s Power BI template is designed to closely resemble the Universal Analytics interface, ensuring a familiar and intuitive user experience.
Upon entering the New and Returning subsection, you’ll be greeted by an overview of your visitor performance metrics. This high-level summary provides a quick glance at User Sessions and Bounce Rate but as with previous reports you can customize it.
As you scroll down the subsection, you’ll discover the new and returning visitors along with a comprehensive breakdown of visitor behavior, including metrics like sessions, bounce rate, pages per session, or average session duration.
One of the standout features of the New and Returning subsection is the ability to apply advanced filtering options. By leveraging the filtering capabilities, you can drill down into specific segments of your audience, such as visitors from particular geographic locations, devices, or marketing channels. This level of granularity enables you to uncover valuable insights and tailor your strategies to specific audience segments.
To further enhance your analysis, the New and Returning subsection has all the filters you need and make it it easier to identify past trends, seasonality, and the impact of historical marketing campaigns on new and returning visitor engagement.
Check out the embedded template below to see the New and Returning page in action.
Audience > Country, Device, Language Google Analytics 3 (Universal Analytics) View
Continuing our journey through the Audience section of Maya’s Power BI template, we come across a trio of insightful subsections: Country, Device, and Language. These views provide a comprehensive look at your website’s audience demographics, enabling you to understand the geographic distribution, device preferences, and language diversity of your visitors.
Upon entering each subsection, you’ll find an overview of the respective demographic metric, showcasing the top countries, devices, or languages contributing to your website traffic. The interactive visualizations enable you to quickly identify the most significant segments and their associated performance metrics, such as sessions, bounce rate, and conversions.
The Country subsection provides insights into the geographic distribution of your audience, allowing you to identify past top-performing regions and potential growth opportunities. The Device subsection offers a clear picture of the history of devices your visitors use to access your website, helping you optimize your site’s responsiveness and user experience across different platforms. The Language subsection reveals the linguistic diversity of your audience, enabling you to tailor your content and future communication strategies to better engage with your multilingual visitors.
Check out the embedded templates below to see the Country, Device, and Language pages in action.
Behavior > Landing Page Google Analytics 3 (Universal Analytics) View
Diving into the Behavior section of Maya’s Power BI template, we find ourselves exploring one of the most popular views in original Google Analytics 3 – Landing Pages.
The Landing Page subsection in Maya’s Power BI template takes inspiration from the Universal Analytics interface, providing a familiar yet enhanced user experience. The intuitive layout and visuals are designed to make data analysis a breeze, while the advanced filtering options allow you to dig deeper into the performance of individual landing pages.
As you scroll this section the Landing Page table provides a comprehensive breakdown of performance metrics, allowing you to compare and contrast the effectiveness of different pages. You can easily identify which landing pages are resonated with your audience and which ones may require optimization.
One of the standout features of the Landing Page subsection is the ability to segment your data based on various Secondary Dimensions, such as traffic source, device, or user demographics. You may apply filters, to gain a more nuanced understanding of how different audience segments interacted with your landing pages, enabling you to tailor your future content and design to better meet their needs and preferences.
Check out the embedded template below to see the Landing Page subsection in action.
Behavior > Events Google Analytics 3 (Universal Analytics) View
Let’s see the Events subsection within the Behavior section of Maya’s Power BI template. This view offers a comprehensive view of user interactions on your website, enabling you to track and analyze events and have their historical performance.
The Events subsection in Maya’s Power BI has a better usability vs the limitations of vanilla Google Analytics.
As you enter the Events subsection, you’ll be greeted by a top-level overview that showcases the total number of the Total Events tracked on your website, conveniently displayed in a yearly granularity (configurable of course). This bird’s-eye view allows you to quickly assess the overall volume of user interactions.
But the real magic happens when you dive into the detailed event table. What we did here is that we made it easier to understand your events. The first column, Event Category, has the highest level of categorization of your user interactions. Then we subgroup with Event Action, enabling you to drill down into specific actions within each category. And the third column, Event Label, offers the Label layer of granularity of your events.
As to metrics, whether you’re interested in total events, unique events, or any other relevant metric, you have the flexibility to tailor your analysis to your specific needs.
Conversions > Goal Completions, Transactions, Product SKU, and More
Lets talk about the Conversions pages, which – as always – closely resemble the familiar Universal Analytics interface.
First up, let’s take a look at the Goal Completions page which provides a comprehensive overview of your website’s historical conversion goals. The top of the page features an overview, displaying the number of conversions (goals) in bars and the conversion rate (CVR) in a line graph, all conveniently broken down by month (configurable).
As you scroll down, you’ll find a detailed table that breaks down each conversion goal. The first column lists the name of the conversion, while the second column displays the number of conversions achieved. The third column shows the conversion value, providing valuable insights into the monetary impact of each goal.
Next, the Transactions page with details of your past online transactions and e-commerce performance. Similar to the Goal Completions page, you’ll find a top-level overview displaying the number of transactions and CVR. As you dive deeper, you’ll find a detailed table that breaks down each transaction per Campaign, including information like the number of transactions, CVR, cost, and revenue generated.
But wait, there’s more! The Product SKU page provides past insights into the performance of individual products. This page mirrors the Product Category and Coupons sections found in Universal Analytics, giving you a familiar and intuitive interface to work with. You’ll find a top-level overview displaying key metrics like product views, add-to-cart actions, and purchases, along with a detailed table that breaks down each product SKU.
Step 4: Customize the Template to Your Needs
Now that you’ve explored the key sections of Maya’s Power BI template lets see how you can go a step further.
One of the greatest strengths of Power BI and of course Maya’s Power BI template is its flexibility. While the template comes pre-built with a wide range of visualizations and metrics, you have the power to customize it to suit your unique requirements. Whether you want to create new visualizations, add custom metrics, or modify existing reports, Power BI gives you the tools you need to make it your own.
Although this article is not meant to be a Power BI tutorial, if you want to create a new visualization, simply select the data you want to visualize and choose the appropriate chart type from the “Visualizations” pane. Power BI offers a wide range of chart types, from simple bar and line charts to more advanced visualizations like scatter plots.
If you want to add custom metrics – although we have you covered with the existing as they derive from our hard worked data model – to the template or dashboard, you can do so by creating new calculated columns or measures in the data model. For example, if you want to track the percentage of sessions that result in a conversion, you can create a new measure that calculates this metric based on the existing data in the model.
When it comes to modifying existing reports, the process is just as simple. Simply select the report you want to modify and begin making changes. You can add or remove visualizations, change the layout and formatting, and even add new pages to the report to create a more comprehensive view of your data.
Step 5: Share Insights and Collaborate with Your Team
Once you’ve customized Maya’s Power BI template to your specific needs and gained valuable insights into your Universal Analytics data, it’s time to share those insights with your team and collaborate to drive better decision-making.
One of the key benefits of using Power BI is the ability to easily share dashboards and reports with your team members. With just a few clicks, you can publish your customized template to the Power BI service and share it with your colleagues. This allows everyone on your team to access the same data and insights, regardless of their location or device.
To share your template, simply open it and click on the “Publish” button. You can share the template via email, or you can embed it in a webpage or SharePoint site for easy access.
When sharing your template, it’s important to set up user permissions and access controls to ensure that only authorized users can access the data and insights. Power BI offers a range of security options, including the ability to set up role-based access control and data-level security. This allows you to control who can see what data and ensures that sensitive information is kept secure.
To set up user permissions, simply navigate to the “Manage Permissions” section of the Power BI service and add the appropriate users and roles. You can also set up data-level security by defining roles and filters in the data model itself. This ensures that users only see the data that is relevant to their role and responsibilities.
Once you’ve shared your template and set up user permissions, it’s time to start collaborating with your team. Collaboration is one of the key benefits of using Power BI, as it allows everyone on your team to work together to gain insights and make data-driven decisions. With Power BI, you can leave comments on specific visualizations or reports, tag team members to draw their attention to important insights, and even co-author reports and dashboards in real-time.
Secure Your Universal Analytics Data and Unlock Insights with Maya’s Power BI Template
If you haven’t already, now is the time to take action and secure your Universal Analytics data before it’s too late. With the sunset deadline fast approaching, it’s crucial that you backup your data to ensure that you don’t lose access to valuable insights and historical data.
Maya’s Universal Analytics backup solution makes it easy to secure your data and ensure that you have access to it for years to come. With just a few clicks, you can connect your Universal Analytics account to Maya and start backing up your data to Maya’s or your own BigQuery. And with our special offer of 14 months of free data backup, there’s no reason not to get started today.
But backing up your data is just the first step. Get Maya’s Power BI template, with pre-built dashboards and visualizations, customizable metrics and dimensions, and seamless integration with your backed-up data.
Don’t let the sunset deadline catch you off guard. Secure your data and start using Maya’s Power BI Universal Analytics template today to ensure that you have access to the insights you need to drive your business forwar