Once you’ve linked your Google Analytics and Google Ads accounts, you can import Google Analytics data into Google Ads and see this data in your Google Ads account. This data can give you insights and possible opportunities to optimize your campaign.
This article will give you an overview of how Google Analytics data can be helpful in your Google Ads account. When you’re ready, you can then follow the instructions to add Google Analytics columns to your reports.
How it works
To see Google Analytics data in Google Ads, you’ll first need to enable auto-tagging for your Google Ads account, link your Google Ads and Google Analytics accounts, and choose Google Analytics views to import site metrics from. Then, you’ll add Google Analytics columns to your Google Ads reports.
By viewing these Google Analytics site engagement metrics alongside your Google Ads performance stats, you can see what people do after clicking on your ad and reaching your landing page. Here's the kind of data you can see:
- Bounce rate: When someone sees only one page or triggers only one event, Analytics considers this a "bounce." Your site's Bounce Rate is the percentage of sessions that are bounces.
- Avg. session duration (seconds): The average time someone stayed on your site.
- Pages/session: The average number of pages viewed per session.
- % new sessions: The estimated percentage of first-time sessions.
This information helps show you how effective your campaigns and ad groups are. And that helps you make decisions about your budgets, bids, landing pages and ad text.
For example, viewing an ad group's bounce rate alongside its clickthrough rate (CTR) can give you a sense of whether your customers are seeing what they expect on your site after clicking your ad.
Ready to add Google Analytics data to your Google Ads reports? Follow the instructions to add Google Analytics data to Google Ads reports.
Dan sells flowers online. One of his campaigns is focused on birthday flowers, and he's experimenting with different keyword themes to find the one that brings him the most sales. One of his ad groups is focused on "birthday bouquets," while another contains keywords and ads related to "birthday flower arrangements."
When he looks at his clickthrough rate (CTR) for both, he sees that more people are clicking on the "bouquet" ad group's ads than those who click on the "flower arrangement" ad group's ads. At first, he thinks that the "bouquet" ad group is more successful. But once he adds the Bounce Rate column (based on Google Analytics data) to his ad group report, Dan sees a new piece of important information.
While the "bouquet" ad group ads have a higher CTR, 8%, compared with the CTR of the "flower arrangements" ads, 6%, the "bouquet" ad group also has a higher Bounce Rate (60%). This means that more than half of the people who arrive at his site from clicks on the "bouquets" ad group are not staying to explore the site or make a purchase.
In other words, the "bouquet" ad group may be getting a lot of clicks, but they may not be the kind of clicks Dan is looking for. He sees that the "flower arrangement" ad group has a lower Bounce Rate (30%), which means that people who click through to his site from those ads are more likely to stay on his site and explore.
|Ad Group "Theme"||Impressions||CTR||Ad Clicks||Bounce Rate||Users that
|birthday flower arrangements||1,000||6%||60||30%||42|
Although the "flower arrangement" ad group gets fewer clicks, for Dan, it's more valuable, because it yields clicks from people who stay to explore his website.
More about Google Analytics data in Google AdsDiscrepancies between Google Ads and Google Analytics data
There are some cases when your Google Ads data might not match your imported Google Analytics data. Here are some of the most common reasons:
- Google Ads tracks clicks, whereas Google Analytics tracks sessions. There are several reasons that these metrics may differ:
- A customer might click your ad multiple times. When one person clicks on one advertisement multiple times in the same session, Google Ads records multiple clicks while Google Analytics recognizes the separate pageviews as one session.
- A person might click on an ad, and then later, during a different session, return directly to the site through a bookmark or saved link. This would register as one click in Google Ads, but multiple sessions in Analytics.
- Someone might click on your ad, but then change her mind and prevent the page from fully loading by clicking to another page or by pressing the browser's Stop or Back buttons. In this case, Analytics won't register a session, but Google Ads still counts this as a click.
- To ensure more accurate billing, Google Ads automatically filters invalid clicks from your reports.
- Comparing long date ranges might include periods during which your accounts weren't linked.
After you import site metrics for the Google Analytics view you want to see in Google Ads, it takes some time for the data to be imported and viewable in Google Ads. You can check the status message in the “Actions” column of the reporting table found under “Linked accounts” > “Google Analytics” in Google Ads. In most cases, it takes less than an hour for the data and columns to be visible in Google Ads, but the process may take longer for larger accounts. Once the data is imported, you can add Google Analytics data to your Google Ads reports.
Google Analytics begins gathering and storing Google Ads-specific data as soon as you establish account links between Google Analytics and Google Ads. So, you can import Google Analytics data into Google Ads for as long as you've linked your Google Ads and Analytics accounts together.
If you established cost-source linking on May 1, and then began importing Google Analytics data into your Google Ads account on May 15, your Google Ads reports will include Google Analytics data going all the way back to May 1.
Only Google Analytics data collected and processed as of May 2016 may appear in Google Ads. While Google Analytics typically processes data continuously throughout the day, it can take up to 24 hours for all data to be updated. For example, if you run a report for "yesterday" at 3 p.m. today, it's possible that some data from yesterday (specifically from 3 p.m. to midnight) might not yet be fully incorporated into your report.