How to Create a View in Google Analytics

Setting up Google Analytics is just the first step, getting clean, actionable data requires a bit more configuration. One of the most important components for keeping your analytics tidy is using Views correctly. This guide will walk you through exactly what Google Analytics Views are, why you need them, and how to create them step by step.

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What is a Google Analytics View?

Think of the structure of Google Analytics as a hierarchy. At the top, you have your Account (your business). Within that account, you have one or more Properties (your website or app). And within each property, you have one or more Views.

A View is a specific lens through which you see the data for your property. Each View can have its own unique configuration, including goals, filters, and user access settings. This allows you to create different reporting perspectives without altering your raw data.

Because filters and settings applied to a View permanently alter the data shown within it, it's considered a best practice to have at least three fundamental views for any property:

• A Raw Data View: This is your backup. It should have absolutely no filters or custom configurations applied. If you ever make a mistake with another View's settings, you'll always have this original, unaltered dataset to fall back on.
• A Master (or Main) View: This is a copy of your raw view but with essential filters applied. This is where you’ll filter out internal traffic from your company, known spam bots, and other noise. This will be your primary View for day-to-day analysis and reporting.
• A Test View: Another copy of the raw view, used specifically for testing new filters, configurations, or goals before you apply them to your Master View. This is your sandbox, preventing you from accidentally breaking your primary reporting view.

Why You Need Multiple Views

Setting up multiple views might seem like extra work, but it's a foundational step for effective analytics that saves countless headaches down the road. Here's why they are so important.

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Data Safety and Redundancy

The most crucial reason for multiple views is data safety. Any filter you apply to a view is destructive and permanent. For example, if you create a filter to exclude traffic from Canada, that data is gone from that view forever. You can't go back and recover it later. Your unfiltered Raw Data View acts as a failsafe, preserving every single hit your property collects, so you always have a complete historical record.

Focused and Cleaner Analysis

Most businesses don't need to look at all of their data all at once. Views allow you to create focused reports for specific needs. You can isolate data to answer very specific questions.

For example, you could create views for:

• Specific Subdomains: Create a view that only shows traffic to blog.yourwebsite.com.
• Geographic Regions: Isolate data to see how users interact with your site in just the "United States" or "Europe."
• Device Types: Build a "Mobile Traffic Only" view to analyze user behavior on smaller screens.
• Marketing Channels: Set up a view that only includes traffic from your paid ad campaigns.

Filtering out irrelevant data (like your internal teams visiting the site) makes your reports more accurate and your insights more reliable. You're making decisions based on real customer behavior, not your own.

Granular User Access Control

Not everyone on your team needs access to all of your website's data. You can set user permissions at the View level, granting team members or external partners access only to the information they need. For instance, you could give your content team access to the "Blog Traffic View" without showing them overall company revenue data.

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How to Create a New View in Google Analytics (Step-by-Step)

Creating a new view only takes a few moments. We'll start by making a simple "Raw Data View." Since the default "All Web Site Data" view that Google Analytics creates often has some settings tweaked, it’s best practice to create a brand new raw view from scratch when you first set up your property.

1. Navigate to the Admin Panel: Log in to your Google Analytics account and click the 'Admin' gear icon in the bottom-left corner of the page.
2. Select Your Account and Property: Ensure you have the correct Account and Property selected in the first two columns.
3. Create the New View: In the third column, labeled "View," click the blue "+ Create View" button.
4. Configure Basic Settings:
5. Create the View: After filling in the settings, click the "Create View" button at the bottom.

Heads Up: A new view will only start collecting data from the moment it is created. It will not contain any of your property's historical data.

Now, repeat these steps to create your "Master View" and your "Test View." For now, they will all be identical. In the next section, we’ll configure your Master and Test views.

Essential Filters for Your New Views

With your three core views created, it’s time to apply some basic filters to clean up the data in your Master View. Remember to always apply a new filter to your "Test View" first to make sure it's working correctly before adding it to your Master View.

How to Exclude Internal IP Traffic

One of the most common and important actions is to exclude traffic generated by your own team, agency, or anyone else who works on your site regularly. This prevents your own activity from skewing your user metrics.

1. Go back to your Admin panel.
2. Make sure your "Test View" is selected in the View column, then click on 'Filters.'
3. Click the red '+ ADD FILTER' button.
4. Give your filter a name, like "Exclude Office IP Traffic."
5. Keep Filter Type as "Predefined."
6. Under "Select filter type," choose "Exclude."
7. Under "Select source or destination," choose "traffic from the IP addresses."
8. Under "Select expression," choose "that are equal to."
9. In the text box, enter your IP address. You can find this easily by opening a new tab and Googling "what is my IP address."
10. Click "Save."

If you have remote team members, you can repeat this process to add filters for their IP addresses, or use a more advanced custom filter to exclude a range of IPs.

After a day or two, check your reports for this filter. If it is working properly, add it to your Master View.

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How to Exclude Known Bots and Spiders

Google maintains a list of common bots and spiders that crawl the web. Excluding them is an easy way to clean up your data. This setting isn’t a filter, but rather a simple toggle in your view's settings.

1. Go to your Admin panel and select your Test View (and later, your Master View).
2. In the View column, click on 'View Settings.'
3. Scroll down to the bottom to a section called 'Bot Filtering.'
4. Check the box labeled "Exclude all hits from known bots and spiders."
5. Click 'Save.'

Best Practices for Managing Your Views

Maintaining a clean analytics setup is an ongoing process. Following a few simple best practices will ensure your data remains useful and reliable for years to come.

• Consistent Naming Conventions: As you create more views, use a clear and consistent naming style. A name like "[PROD] Master - Excludes Internal" is much better than "Copy of All Website Data." This helps everyone on the team understand the purpose of each view at a glance.
• Always Test First: Never apply a new filter directly to your Master View. Use your Test View to verify that the filter behaves exactly as you expect before rolling it out to your main reporting view.
• Use Annotations: Annotations let you leave short notes on your timeline within Google Analytics. Use them to mark when you added a new filter, launched a marketing campaign, or redesigned a major part of your website. This provides critical context when analyzing data spikes or drops in the future.
• Perform Regular Audits: At least once a quarter, review your views, filters, and user permissions. Do the filters still make sense? Do the right people have the right level of access? This housekeeping keeps your setup from becoming cluttered and confusing.

Final Thoughts

Setting up Google Analytics Views is a foundational task for anyone who wants to rely on their data. By creating dedicated raw, master, and test views, and applying basic filters, you establish a reliable system for collecting clean data. This small upfront investment in organization pays huge dividends by enabling more accurate analysis and confident, data-driven decisions.

Once your Google Analytics data is clean and organized, the next step is often to combine it with data from other platforms - like your ad accounts on Facebook or Google Ads, your sales CRM, or your e-commerce platform. At Graphed, we make this part easy. In seconds, you can connect tools like Google Analytics, Shopify, Salesforce, and HubSpot. Instead of wrangling CSV files, you can just ask questions in plain English, like "Show me a dashboard comparing Facebook Ads spend vs. Google Analytics sales by campaign," and we'll instantly build a live, updating dashboard for you. To see how it can save you hours of manual reporting work, you can get started with Graphed{:target="_blank" rel="noopener"} for free.