What’s with the Discrepancies?
By Understanding How Google Analytics and Your Ad Platform Pull Their Data, You Can Avoid a lot of Headaches
Nov 30, 2017
It’s the bane of any marketer’s existence: discrepancies between Google Analytics and their ad solution’s analytics. Google Analytics doesn’t match up with vendor reporting, which can lead to reactions ranging from confusion to frustration. This is a common problem in the industry — every vendor encounters this issue with their reporting. And while there are some technical mistakes that can lead to discrepancies (find out what they are and how to fix them here), the fact is there will always be a number of data points that won’t align properly.
There is a way to overcome this issue, however. The good news is that you can alleviate the headaches by better understanding how your vendor reporting and GA operate. Once you understand where each is pulling its information, you’ll be better setup to interpret and leverage that info to improve your marketing performance.
How Google Analytics Works
The main issue with reporting discrepancies comes down to the techniques vendors and GA use to track conversions, namely that GA measures success differently than other vendors do. While we can’t break down each vendor since they all have their own analytics approach, we can examine how Google operates. Here’s how they track performance:
> Tracked Metric | Sessions
> Tracked Metric Definition | Site visit with at least one page view, expiring after A) 30 minutes of inactivity, B) midnight in the user’s timezone, C) if the value of the UTM_campaign parameter changes
> Attribution Model | Click through conversions only. They support multiple models, but the default is last non-direct click.
> Attribution Window | Default 30 day click conversion window
> How it Works | Gives conversion credit to the most recently clicked ad; if no ad is clicked, it gives credit to “Direct”
> Cross-Device | Google Analytics does not have default cross-device tracking
Wait, No Cross-Device?
Take note of the last bullet point listed above. GA does not have default cross device tracking, meaning it defaults to attributing credit to the last click/session that GA was able to track. That’s a very important distinction to make, because that means it isn’t able to account for the vast majority (up to 90% according to Google!) of customers who begin shopping on one device, and finish on another.
This is a big deal — the average person owns nearly 4 connected devices, meaning cross-device represents true user behavior. And according to a recent study by Pew Research, American households are more connected than ever, stating “90% of U.S. households contain at least one of these devices (smartphone, desktop/laptop computer, tablet or streaming media device), with the typical (median) American household containing five of them. And nearly one-in-five American households (18%) are ‘hyper-connected’ – meaning they contain 10 or more of these devices.”
Let’s use an example that you’ve probably experienced to illustrate why GA can come up short. Imagine seeing an ad for a product on your mobile phone while in line at the bank. Do you immediately make a purchase on your phone? Probably not. But perhaps you go back to your office later that day and buy the product on your desktop computer. Such cross-device conversions are increasingly common as people move between their phones and desktop computers to interact with businesses. In this scenario, and millions of others like it, Google Analytics is only going to credit your desktop campaign, leaving mobile to look like its underperforming. While Google Analytics is one of the most substantial attribution partners in the space, this limitation must be taken into account when looking at the success of your full marketing mix.
Cross-Device & Cookies
Cookies, or a lack thereof, can also lead to discrepancies. Most analytics tools, GA included, rely on cookies to track and attribute user behaviors on a website. This is extremely limiting when you consider that cookies are not only specific to each device, but to each browser on each device. What’s more, these cookies can easily be deleted, only to be created anew upon the next site visit. What GA is left with is a gross overrepresentation of website traffic, and an inaccurate distribution of performance across vendors and channels. This where companies like Facebook have developed user based alternatives to help close the gap.
Facebook warns their advertisers that 3rd party analytics platforms like Google Analytics struggle to accurately track Facebook conversions. Because GA struggles with accurately reporting on anything that doesn’t include cookies, you end up with discrepancies between GA and your vendor.
A Difference of Scope
Discrepancies aren’t just limited to cross-device and a lack of cookies. GA and your ad platform are not only sourcing their data in different ways, they are also using different scopes of reference. For example, a display retargeting vendor will only be able to see the users they are touching, while a platform like GA can take the brand’s entire marketing mix into account. Unfortunately, the way GA tracks performance doesn’t always fairly attribute credit to all vendors.
Let’s use a hypothetical (and yet all too real) scenario to illustrate this point:
1. A retargeting vendor serves impressions to a user, who clicks the ad but does not convert immediately.
2. The brand then sends this same user an email offer, and afterwards the user converts.
3. GA gives full credit to the email campaign, and no credit to the retargeting vendor.
The problem here is that GA isn’t giving any credit to the retargeting vendor, even though the user saw and engaged with the retargeting ad. While the email campaign was the last touch point, that does not mean the display campaign did not contribute to the conversion.
Now here’s where the discrepancy comes in. The retargeting vendor can only see the user clicked the ad, and converted a short time later. This leads them to take credit for the conversion, but according to GA, the email campaign deserves the credit. The brand is then left wondering why the retargeting vendor is trying to take credit for the email’s conversion, and headaches ensue.
So How Do I Get Rid of Discrepancies?
We know Google Analytics reports in a way that can cause discrepancies between your other data. And that’s all well and good — the more you know, the better — but how do you completely remove discrepancies from your reporting?
The blunt truth is you can’t. It’s a quirk of digital advertising that isn’t going away anytime soon. The best thing you can do is understand why there are discrepancies, and where they are coming from. Thankfully there are ad platform solutions out there (the SteelHouse Advertising Suite included) that take cross-device interactions into account, giving you better insight into your true performance.
The Advertising Suite is capable of tracking cross-device user behavior because SteelHouse has partnered with analytics industry leaders like Crosswise, AdBrain, Tapad, and Drawbridge. This allows us to accurately identify cross-device conversions that often are missed by traditional multi-channel attribution platforms like Google Analytics. And by leveraging both first-party data and industry leading device graphs, we can accurately track everything needed with a combination of deterministic and probabilistic methods.
Talk to your advertising solution rep to better understand how they track performance, and understand the differences between it and GA. Once you understand those fundamental differences, those discrepancies are suddenly a lot less of a pain, and you’ll be able to better interpret and leverage that data to improve your campaign performance.
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