Do you ever open Google Ads and Google Analytics side-by-side and wonder why the conversion data is not the same? Well, so have we. Some small discrepancies are normal due to the nature of both platforms, but sometimes the differences can become quite large. No need to worry. There are steps you can take to minimize them. In this article, I will look into what causes data discrepancies between the two platforms, and how to minimize them. Let’s go!
Why data discrepancies are normal
All reporting tools are designed differently, so they also report differently. For this reason, you can always expect data differences when comparing data from different sources. The issue with advertising platforms like Google Ads is that, because you pay for clicks and conversions, the platform wants to give you as much value as it can. So, those platforms will generally attribute conversions to themselves. Because Google Ads is also a Google tool, it is usually represented quite well in Analytics. Social media advertising platforms like Meta or Tiktok are usually portrayed worse.
A web analytics tool like Google Analytics is usually a reliable, neutral source to report on all traffic that is sent to your website. It reports where the user came from, as long as this information is passed along correctly. But, data might be attributed incorrectly, and create data discrepancies between the tools that you use. These discrepancies fall into two categories: faulty/ blocked tags, and differences in attribution/ reporting methods.
How Google Analytics identifies Google Ads traffic
Before we start looking at probable causes, you need to understand how both platforms identify where the user came from. This can be done in two different ways. With auto-tagging from Google Ads, which uses the gclid parameter, or with manual or other UTM tagging.
Analytics uses the gclid parameter in your final URLs to identify traffic from Google Ads. The gclid parameter shows up in your landing page URL when a user arrives at your site from your ad. The same is true for UTM parameters. Maybe you can already see how discrepancies might arise.
Discrepancies exist between the number of clicks in Google Ads and the number of sessions in Analytics. Also, conversion data will be different between the two platforms. Both types of discrepancies influence each other, so if you are facing this issue, be sure to check all the possible causes mentioned below.
The discrepancies between sessions and clicks
Let’s first have a look at the differences between the number of clicks that Google Ads reports, and the number of sessions that arrive in Analytics. To make this a practical guide, that can help you to find the cause of the discrepancies, I have categorized the issues into two sections. More clicks than sessions, and the other way around. We will start with the latter.
What causes you to see more sessions than clicks?
- Google Ads filters invalid clicks from your report. Analytics doesn’t.
Google Ads filters invalid clicks from your reports and refunds them. Analytics reports on all the resulting sessions. Invalid clicks are those made by bots or competitors to drive up your costs.
- Returning users
During the lifetime of a Google Ads campaign, a returning user to your site is attributed to that campaign.
- Users return to your site via bookmarks.
If users bookmark your website with the gclid parameter, Analytics records traffic from these bookmarks as coming from your Google Ads ads. But, Google Ads doesn’t record clicks.
What causes you to see more clicks than sessions?
- Clicks and Sessions are different metrics
Google Ads tracks Clicks, but Analytics tracks Sessions. If a user clicks on your ad 2 times within the duration of a session (by default 30 minutes) without closing the browser, this is counted by Analytics as one session, even if the user left your site and then returned later.
- Auto-tagging is turned off in your Google Ads account.
If auto-tagging is turned off, and you didn’t tag the final URLs with UTM’s, the traffic isn’t recorded as Google CPC, but instead may be attributed to Google Organic.
- Make sure your Google Ads account is linked
If you’re sure the accounts are linked and you still don’t see click or cost data, check that you have selected the option to import the data from the linked account to the view in question.
- Redirects remove correct UTM tagging
If your website redirects the user from for example the HTTP version to the HTTPS version of your site, proper tagging will get lost. So Analytics will not attribute this session to Google Ads. Also, redirects on landing pages can keep the Analytics code from launching and identifying the traffic as having come from Google ads.
- Adblockers or certain browsers might block Analytics from firing
There is a possibility that users entering your website through Google Ads have JavaScript or images turned off. They might also use other technologies to prevent Analytics from collecting data about them. Occasionally, Analytics can’t report these users, but Google Ads does.
- Make sure your landing page loads the tracking code
Something might be causing the tracking code on your website not to fire. So, Analytics cannot record a session.
- A user leaves before the tag is loaded
If a user comes to your site from an ad, and then leaves the landing page before the tracking code loads, then the gclid parameter is never passed to Google Analytics, and that click isn’t associated with the session.
Conversion discrepancies between Analytics & Google Ads
Now we will have a look at the differences between the number of conversion goals or transactions that Google Ads reports, and the number of goals or transactions reported in Analytics. Because these can have a more direct impact on your bottom line, it is crucial to have as little discrepancies as possible. We will start with the most common scenario, you seeing more conversions in Google ads than in Google Analytics.
What causes you to see more conversions in Google Ads?
- Attribution differences
Google Ads attributes conversions to the last Google Ads click, by default. But, in all reports except the Multi-Channel Funnels report, Analytics uses a last-non-direct-click attribution model. For example, let’s say a user clicks on your Google Ad, returns the next day via Google organic search, and completes a transaction. Analytics will attribute the purchase to Google/organic. Google Ads will, by default, attribute the conversion to itself.
- Click-time vs. conversion-time reporting
Google Ads reports conversions on the date of the click that led to the conversion, not against the date of the conversion itself. For example, when a user makes a purchase on the 25th of April but clicked on the ad three days earlier. In Google Ads, the conversion would be attributed to April 22th, the day of the click. In Analytics, the conversion is attributed to the 25th of April, the day of the conversion.
- Reporting freshness
Google Ads conversion tracking gets reported faster (about 3 hours later) than transactions in Analytics (about 9 hours later).
- MCC-level conversion tracking
If you have multiple Google Ads accounts sending traffic to your website, you may see more conversions in Google ads. This depends on what type of conversion goals you are using.
If you set up Google Ads conversion tracking at the account level, then each Google Ads account might report the same conversion. If you implement MCC-level conversion tracking, it will be assigned to the right account. Analytics de-duplicates imported transactions.
- Conversion counting in Google Ads
In Google Analytics, a goal completion is recorded once per session. Because Google Ads is not based on sessions, a goal completion can be counted multiple times for every ad click. You can change this setting in the conversion from “one” to “every” if you want to track all transactions for example.
- Cross-device conversions
Conversion tracking in Google Ads supports cross-device conversions that appear in the Conversions and All conversions columns. These are, by default, not visible in Analytics.
- View-through conversions
Google Ads has the ability to track conversions based on impressions of an ad. They are called view-through conversions. These conversions are not available in Analytics.
- Phone call conversions
If you use call extensions, calls that last longer than a configured duration are counted as call conversions. These conversions cannot be tracked using Analytics.
What causes you to see more conversions in Analytics?
- Imported transactions
Imported transactions get an Order ID in Google Ads. It de-duplicates transactions based on Order ID, so each transaction will be counted once. But, multiple transactions with the same ID could be counted in Analytics if a user loads a conversion page with the same Transaction ID in another session.
How to minimize discrepancies between Google Ads and Analytics
So we have looked at what causes data differences between the two platforms. With this list, you can identify if you are reporting correctly or if something is going wrong. To have the most accurate data available, there are some general reporting best practices to adhere to.
- Always compare data from at least 1 conversion period ago. Usually, 2 weeks is fine.
- Compare large periods of time for more significant data
- Make sure the lookback window is the same for both sources
- Use both click and session metrics in your reports
- Use the same attribution model for both sources
From the list of possible causes, we can also derive a list of actions that you can take to improve data accuracy. Be sure to check them all for minimal data discrepancies.
- Ensure your Google Ads and Analytics accounts are linked
- Enable auto-tagging again and avoid manual tagging
- Make sure the analytics tag fires on all pages
- Make sure there are no redirects on your landing pages
- Ensure that your website loads fast
- When you have multiple Google Ads accounts, use MCC-level goal tracking
- Invest in call-tracking solutions to measure your call conversions
The takeaway
As you have read, there can be many causes for differences in your data between Google Ads and Analytics. This can be quite frustrating but, as I stated in the introduction, discrepancies of around 10% are normal. So, you should also accept some in your data. You can assume that the truth is somewhere in the middle between Ads and Analytics.
You can use this guide as a checklist to spot probable causes of your data discrepancies. If you cannot seem to figure it out or you want help with your tracking setup, you can always reach out to us. Happy analyzing!
