How to Filter Multiple IP Addresses in Google Analytics

Cleaning up your Google Analytics data starts with filtering out your team's visits. If you don't, your own clicks, page views, and test conversions can seriously inflate your metrics and hide what your actual customers are doing. This guide will show you precisely how to filter one or more IP addresses out of your reporting in both Google Analytics 4 and the older Universal Analytics (UA).

Why Filtering Internal Traffic is Non-Negotiable

Imagine your five-person marketing team loads your company homepage 10 times a day to check on new content or test-fire a lead form. That’s 50 sessions and possibly thousands of events each day that have nothing to do with your target audience. Left unchecked, this internal traffic can wreak havoc on your data, leading to:

• Inflated Session and User Counts: Your top-line traffic numbers look better than they really are.
• Skewed Engagement Metrics: Internal users often have 100% bounce rates (if they just check one page) or extremely long session durations (if they leave a tab open), making your average engagement stats meaningless.
• Inaccurate Conversion Rates: If your team is testing goal completions, your conversion rate can appear artificially high, masking potential issues in your user funnels.

Excluding your team, your developers, your freelancers, and your own home office ensures that your reports reflect genuine customer behavior, giving you the real story behind your website's performance.

Filtering IP Addresses: GA4 vs. Universal Analytics

How you filter IP addresses differs significantly between Google Analytics 4 and the now-retired Universal Analytics. While UA sunsetted in July 2023, many people still refer to their historical UA data, so it's essential to know how filtering worked there as well.

The main difference is that in Universal Analytics, you applied filters at the "View" level. You could create different views for your data - one raw and unfiltered, another with internal IPs excluded. GA4 does away with the concept of Views. Instead, it uses a two-step process: first, you define what counts as internal traffic, and then you apply a data filter to exclude it from your reports.

How to Filter a Single IP Address in GA4

Excluding a single IP address - like from your main office - is straightforward in GA4. Just remember it’s a two-part process.

Step 1: Define Your IP Address as Internal Traffic

1. Navigate to the Admin section by clicking the gear icon in the bottom-left corner.
2. In the Property column, click on Data Streams and select the relevant web data stream.
3. Under the Google tag section, click on Configure tag settings.
4. On the next screen, click Show more if needed, and then select Define internal traffic.
5. Click the Create button to set up your first rule.
6. Give your rule a descriptive name, like “Main Office IP.” The default traffic_type value of "internal" is usually fine to leave as is.
7. Under the IP addresses section, leave the Match type as "IP address equals" and enter the single IP address you want to exclude in the Value field.
8. Click Create in the top right to save your new rule.

You have now told GA4 how to identify internal traffic, but you haven't yet told it to exclude that traffic.

Step 2: Activate the Data Filter

1. In the Admin section, navigate to Data Settings > Data Filters.
2. You will see a filter named "Internal Traffic." Click the three dots on the right side of that filter.
3. Select Activate filter from the dropdown menu. Confirm the action in the pop-up.

The filter state will now change to "Active." After this point, GA4 will permanently exclude all traffic that matches the internal traffic rules you've defined. Note that this change is not retroactive - it will not remove historical data.

The Main Event: How to Filter Multiple IP Addresses in GA4

What if you need to filter traffic from multiple office locations, or from remote employees? This is where things get a bit more involved. GA4 provides two main methods for handling multiple IP addresses.

Method 1: Create Multiple "Internal Traffic" Rules

Unlike Universal Analytics, you can't just drop in a comma-separated list of IP addresses. However, you can add up to 10 different IP addresses to a single internal traffic rule definition.

1. Follow the same path as before: Admin > Data Streams > [Your Stream] > Configure tag settings > Define internal traffic.
2. Click on the rule you created earlier (e.g., “Main Office IP”).
3. Inside the IP addresses section, you can add more conditions. Click the Add condition button.
4. Another row will appear. You can now add an additional IP address with the match type "IP address equals".
5. Repeat this for each individual IP address you need to block. You can mix and match IP addresses, or blocks of addresses (see the CIDR notation option under the match type dropdown if you’re more advanced).
6. Click Save when you are finished.

Because these are all tied to the same traffic_type of "internal," the data filter you already activated will now exclude all of them.

Method 2: Use a Regular Expression (RegEx) for Scalability

If you have many IP addresses to filter, or if you need to exclude an entire range, creating individual conditions is not practical. This is a perfect job for a Regular Expression (RegEx).

A RegEx is a special text string for describing a search pattern. For filtering multiple IPs, you can simply list each IP separated by a pipe character |, which functions as an "OR" operator. The "dots" in an IP address need to be "escaped" with a backslash \ so RegEx knows you mean a literal period.

Here’s how to set it up:

1. Navigate again to Admin > Data Streams > [Your Stream] > Configure tag settings > Define internal traffic.
2. Create a new rule or edit your existing one. Let's call it "All Internal IPs - RegEx."
3. Under the IP addresses section, change the Match type to Regular expression.
4. In the Value field, enter your RegEx pattern. For example, to block the IP addresses 88.134.55.12 and 193.1.200.56, your pattern would be:

88\.134\.55\.12|193\.1\.200\.56

You can add as many IPs as you need, each separated by a pipe | character. This approach is much cleaner for managing a long list. Once saved, the active data filter will use this RegEx pattern to exclude all matching IP addresses.

What About Universal Analytics (Legacy)?

For those checking historical data, filtering multiple IPs in Universal Analytics was much more direct.

You would navigate to Admin > [View Column] > Filters > + Add Filter. Inside the filter settings, you would:

• Choose Custom for the Filter Type.
• Select the Exclude radio button.
• Set the Filter Field to "IP Address."
• For the Filter Pattern, you'd use a RegEx pattern very similar to the one above.

This single filter would then be saved to that specific view.

Best Practices and Common Pitfalls

Setting up filters is easy, but keeping them effective requires a bit of attention. Here are a few final tips:

• What about dynamic IPs? Many home internet connections use dynamic IPs that change periodically. If you're filtering remote workers, ask them to Google "What is my IP address?" once a month and update your filter rules accordingly.
• Beware of VPNs: Traffic from a device connected to a VPN will show the VPN's IP address, not the user's. These IP filters will not catch VPN traffic unless you explicitly add the VPN's IP to your exclusion list.
• Verify Your Filters: In GA4, you can use the "Test data filter" feature. By activating this and then adding the parameter ?traffic_type=internal to your website's URL, you can then check the "Realtime" report to see if GA4 identifies your traffic correctly. Make sure you also see the tt debug parameter.
• Keep a Log: It's good practice to keep a separate document or spreadsheet listing the IPs you're filtering, who they belong to (e.g., "Main Office," "CEO's Home IP"), and when they were added.

Final Thoughts

Filtering internal IP addresses is a fundamental step toward achieving data hygiene in Google Analytics. Following these steps will help you clean up your reports, remove internal noise, and make smarter decisions based on what your actual customers are doing on your site.

Once your data is clean, the next - and most important - step is making sense of it all. Here at Graphed, we felt the friction of building the same manual reports every week. We built our platform to eliminate that completely. By connecting your Google Analytics and other data sources, you can ask questions in plain English - like "Compare organic traffic vs paid traffic from the last 90 days" - and get real-time dashboards and reports built for you in seconds. It allows you to spend your time acting on insights, not just looking for them.