Google Ads vs Google Analytics Conversion Tracking Explained

It’s just one of those days, we have all been there. You check your campaigns and see 50 conversions in Google Ads, but Google Analytics shows only 45. The plot thickens! In this article, I will play the detective and explain the differences between Google Ads and Google Analytics Conversion Tracking. By the end of this article you will understand the differences and have the knowledge to make informed decisions for future projects.

Counts only Google Ads touch points

The first and most important part is that Google Ads takes into consideration only clicks on ads when attributing conversions. This means that if a users clicks your Search Network ad, checks our your website but leaves, and the next day comes directly to the website and buys, Google is going to say “oh yeah, this is my doing”. This is a standard way advertising platforms work. Same for Facebook, Twitter, LinkedIn and others.

One vs every conversion counting

In Google Ads we have some flexibility to decide if we want to count the conversion once or various times. Lets present a few scenarios that will help you understand what this means. This is the scenario:

A user clicks an Ad, makes a purchase, then comes back to to the website to make another purchase

Count once

In this method there will be only one conversion reported. This situation is good for business that for example want to know if the keywords convert but don’t care if they do it once or several times.

Count every

When we count every conversion, we will then see two purchases. This is a preferred option when we optimize for ROAS. We get two purchases for one click.

In Google Ads, the model is by default Last Google Ads Click. This means, that the conversion will be assigned to the last Google Ads click. There are several other attribution models that are available but I will not get into them now, but there is one incredible option available, DDA (Data-Driven Attribution). It uses the Shapely model to estimate the impact of each click on partial level. In the end there can be 0.5 conversions assigned to one ad, and 0.5 conversions assigned to another.

Attribution goes to the date of the click

This a Google Ads specific thing. If you clicked an ad on Monday, but you make a conversion on Friday, Google Ads will assign the conversion to the click on Monday. This is one of the big reasons why there might be discepencies between the number of conversions for the same period in Google Ads

Google Analytics Conversion Tracking Explained

Counting all touch points

Google Analytics takes into consideration all click touch points, which includes: social clicks, referrals, paid social and Google Ads. The result is that you get a big picture overview of how the user interacted with the website from all of the sources. It’s mostly click based but with GA360 and programmatic campaigns you can also get View-Through Conversion Data that adds another layer of complexity to the user journey.

Google Analytics default attribution

By default Google Analytics is using the “last non-direct click” as an attribution model. This means it assigns the conversion to the last touch point that was not a direct entry to the website. There is also a possibility to compare different models and their impact on the campaigns in the Model Comparison Tool report in the Multi-Channel Funnels section.

Google Analytics reporting delay

It can take several hours or even days for Google Analytics to attribute the conversion. A frequent situation is to see the conversion in Analytics the following day. This means you should not treat analytics as a real-time dashboard.

Attributed on the date of conversion

Google Analytics attributes the conversion to the date when it had happened. This is different to Google Ads which attributes the conversion to the day of the click.

Google Ads vs Analytics conversion discrepancies

There might be several reasons for discrepancies and lets put all of them out there.

  • Technical issues – the conversions are configured incorrectly. An incorrect trigger is all that is needed
  • Date of the conversion vs date of the click – Both tools attribute the number of conversions differently. I would go as far as saying, you should see different number!
  • Attribution – Google Analytics uses “last non-direct click” while Google Ads uses “last Google Ads click”.
  • Recency – Some conversions get attributed after several days. If you are checking a recent period, it is possible that Google Ads has already picked it up and Analytics will need a few hours to see the same conversion
  • Order ID de-duplication – If we are talking about transactions and you import the order ID as a parameter Google Ads will de-duplicate it, and Google Analytics will just duplicate the same conversion with the same order.

If you want to learn more I advise to read through this Support Page.

Should I use Google Ads or Analytics conversion tracking?

The million dollar question. To be honest, for the performance campaigns purposes I always recommend using Google Ads conversion tracking.

It attributes more conversions to your campaigns, omits all other channels and uses data-driven attribution for search. What you need to understand is that thanks to this data Google can improve the end result of your account as a whole. This means if you select correct biding strategies they will maximize the return on your ad spent. In the end you squeeze the lemon a bit harder to get more juice thanks to algorithms that take into consideration more things than we do.

Let’s bring this one home

For optimization, I always recommend using Google Ads conversion tracking. For reporting, it depends. When for example you are reporting various channels and using their own attribution like for example Facebook Ads, then I recommend also using Google Ads conversion to make the playing field more even. On the other hand, it will never be even because the models are different and for example Facebook can attribute impressions whereas Google Ads is not the best for this.

In this article, I highlighted the most important differences in the attribution models and gave you the knowledge to make an informed decision. In the end, the final decision is up to you.

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