Most of us are aware of Google Ads auto-tagging but don’t know how it works. What does auto-tagging do and why is it important in your Google Ads account? Auto-tagging is a way for Google Ads to communicate all the details about a user session to Analytics. In turn, we are able to use the information reported in Analytics to measure post-click behavior.
Auto-tagging is a setting in Google Ads that allows the system to append your final URLs with parameters in order to report traffic statistics into Analytics. Auto-tagging is a huge time-saver, but sometimes it breaks, creating a real challenge when trying to measure performance. Plus, whenever data is reporting inaccurately in Analytics, a considerable amount of time can be spent troubleshooting performance issues. Or worse, it can make you think your paid search traffic is not converting.
You’ll notice with auto-tagging that Google appends “gclid” to your final URLs. What does this term mean anyway? The term “gclid,” or the Google click identifier, is a way for Google Ads to communicate information about the searcher to Analytics. This data allows you to view post-click activity in Analytics, such as time spent on site, pages per visit, etc. Google Ads auto-tagging will encode the necessary tags into the URL to report on information like:
- Ad Group
- Match type
- Ad Creative
When you enable auto-tagging in Google Ads you do not have to manually set-up tags for every URL. Whenever possible it is recommended to use auto-tagging over manual tagging to avoid mistakes. Plus, manually tagging each URL can save time and reduce errors due to capitalization or misspellings.
First, check in Google Ads to see if you have auto-tagging enabled. You can do this under ” Settings > Account Settings > Auto-tagging.”
In these example tagged URLs, using capital vs. non-capital sources or mediums will cause Analytics to split up the data and report these as two independent statistics. This is another reason why auto-tagging is ideal over manual tagging.
All ad clicks will now automatically append the gclid to the ad’s URL and send all associated data to Google Analytics.
There are rare times when a Google Ads account can not be connected Analytics and we need to manually tag each URL to be able to view performance data. When you create manual tags, it is important to make sure they are identical and use the same case to make sure they appear under the same line item in Analytics
Manual Tags And Reporting
Yes, case matters when you are manually tagging URLs for your campaigns. As mentioned above, you do not want Analytics splitting up your stats because you used capitalization on half of your URLs.
You will want to make sure the source, medium, and campaigns are consistently named and using the same case. I usually prefer to capitalize my campaign names because I like how it appears under “Acquisition > Campaigns > All Campaigns.” This setup is just a preference but ensures Google Analytics naming matches the naming convention in my accounts. Here’s an example.
- Source: google
- Medium: cpc
- Campaign: CampaignName (or Campaign_Name)
If you do use capitalization on some and not others the source/medium will report separately in Analytics. You could have 2 Google Ads sources that show as such.
This makes it harder to quickly segment traffic as you now need to filter for multiple source / medium’s to see your ad performance data.
Reasons Websites Drop The Gclid
Another issue we have found for the gclid getting dropped is when final URL redirects. A website that redirects from http://www.website.com to http://website.com may drop the gclid and you will have incorrect data reporting in Analytics. This can even happen when a HTTP URL redirects to the secure HTTPS URL. Google has a help section entitled Check if Google Ads auto-tagging works to help you ensure you are using the correct URL.
Third-party payment options may also cause the gclid to be dropped. On an ecommerce site, you may see a referral from Paypal.com in Analytics. Thus, if someone clicks your ad and pays via PayPal, the referrer will be PayPal instead of Google Ads.
Troubleshooting The Gclid Issue
Unfortunately, auto-tagging settings and Gclid dropping off is a somewhat common tracking error. If you have a high volume of ads it can be tricky to make sure these are set-up properly. Every website is different, and server settings may change tracking behavior. In order for auto-tagging to work properly, you will need to make sure the Google Ads final URL and the website URLs match up.
In one case, we had a client who had all the ads pointed to http://www.website.com instead of the https:// version. Display traffic was reporting terrible metrics when it was really the URL issue causing the gclid to drop. Since we corrected the final URL, display is one of the best performing campaigns.
In another case, some of the URLs were set up with the WWW and some were not, preventing Analytics from reporting revenue associated with Paid Search. Analytics was reporting most transactions as direct traffic.
Checking The gclid In Analytics
So how do you know if you have a mismatch or if you have an issue with gclid parameters? Analytics is a good place to start. You might see a notification error that says ‘Invalid Google Ads gclid’ that will give you additional details into what is happening.
Analytics may also show you a notification error stating there are clicks and sessions discrepancies.
You can also view the clicks vs sessions data under “Acquisition > Ads > Campaigns.”
Google Ads metrics in Google Analytics
In the example above, you can see the clicks and sessions have a significant discrepancy in their data. Keep in mind, these numbers will never match up exactly, but there shouldn’t be this big of a difference in the data.
You can view all conversion paths under “Conversions > Multi-Channel Funnels > Top Conversion Paths.”
As you can see in the above example, many of our conversions are falling under direct traffic, which may be because the URL is dropping the gclid.
Next, you can visit the Google support page. Open a new window in Chrome and select “Menu > More Tools > Developer Tools” and select the Network tag. In the address bar, set up your URL like the example provided and select enter http://www.example.com/?parameter=1&gclid=TeSter-123. After the page finishes loading, you should still see the gclid in the address bar or the header. If you do not see it at all that means your website is dropping the gclid and you’ll need to work with the web team on why.
Also, keep in mind that when you add your website in the address bar and if you see a status of 302, this status means your website has a redirect and auto-tagging may not work. Make sure you follow the redirect and see the tag carried over.
A 302 status
We hope this article will help you understand how auto-tagging actually functions, the differences between auto-tagging and manual tagging and how these features can impact your Analytics data. We have also included some additional resources below to help you verify if your auto-tagging is working and additional reasons why it may not be.
Post updated by Jacob Fairclough (prior post date: 06/01/16)
The Biggest Ad Fraud Cases and What We Can Learn From Them
Ad fraud is showing no signs of slowing down. In fact, the latest data indicates that it will cost businesses a colossal €120 billion by 2023. But even more worrying is that fraudsters’ tactics are becoming so sophisticated that even big-name companies such as Uber, Procter & Gamble, and Verizon have been victims of ad fraud in recent years.
So what does this mean for the rest of the industry? The answer is simple: every ad company, no matter their size or budget is just as at risk as the big guns – if not more.
In this article, I summarize some of the biggest and most shocking cases of ad fraud we’ve witnessed over recent years and notably, what vital lessons marketers and advertisers can learn from them to avoid wasting their own budgets.
The biggest ad fraud cases in recent years
Let’s take a look at some of the most high-profile and harmful ad fraud cases of recent years that have impacted some of the most well-known brands around the world.
Methbot: $5 million a day lost through fake video views
In 2016, Aleksandr Zhukov, the self-proclaimed “King of Fraud”, and his group of fraudsters were discovered to have been making between $3 and $5 million a day by executing fake clicks on video advertisements.
Oft-cited as the biggest digital ad fraud operation ever uncovered, “Methbot” was a sophisticated botnet scheme that involved defrauding brands by enabling countless bots to watch 300 million video ads per day on over 6000 spoofed websites.
Due to the relatively high cost-per-mille (CPM) for video ads, Aleksandr and his group were able to steal millions of dollars a day by targeting high-value marketplaces. Some of the victims of the Methbot fraud ring include The New York Times, The New York Post, Comcast, and Nestle.
In late 2021, Aleksandr Zhukov was sentenced to 10 years in prison and ordered to pay over $3.8 million in restitution.
Uber: $100 million wasted in ad spend
In another high-profile case, transportation giant Uber filed a lawsuit against five ad networks in 2019 – Fetch, BidMotion, Taptica, YouAppi, and AdAction Interactive – and won.
Uber claimed that its ads were not converting, and ultimately discovered that roughly two-thirds of its ad budget ($100 million) wasn’t needed. This was on account of ad retargeting companies that were abusing the system by creating fraudulent traffic.
The extent of the ad fraud was discovered when the company cut $100 million in ad spend and saw no change in the number of rider app installs.
In 2020, Uber also won another lawsuit against Phunware Inc. when they discovered that the majority of Uber app installations that the company claimed to have delivered were produced by the act of click flooding.
Criteo: Claims sues competitor for allegedly running a damaging counterfeit click fraud scheme
In 2016, Criteo, a retargeting and display advertising network, claimed that competitor Steelhouse (now known as MNTM) ran a click fraud scheme against Criteo in a bid to damage the company’s reputation and to fraudulently take credit for user visits to retailers’ web pages.
Criteo filed a lawsuit claiming that due to Steelhouse’s alleged actions — the use of bots and other automated methods to generate fake clicks on shoe retailer TOMS’ ads — Criteo ultimately lost TOMS as a client. Criteo has accused Steelhouse of carrying out this type of ad fraud in a bid to prove that Steelhouse provided a more effective service than its own.
Twitter: Elon Musk claims that the platform hosts a high number of inauthentic accounts
In one of the biggest and most tangled tech deals in recent history, the Elon Musk and Twitter saga doesn’t end with Twitter taking Musk to court for backing out of an agreement to buy the social media giant for $44 billion.
In yet another twist, Musk has also claimed that Twitter hid the real number of bots and fake accounts on its platform. He has also accused the company of fraud by alleging that these accounts make up around 10% of Twitter’s daily active users who see ads, essentially meaning that 65 million of Twitter’s 229 million daily active users are not seeing them at all.
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6 Lessons marketers can learn from these high-profile ad fraud cases
All of these cases demonstrate that ad fraud is a pervasive and ubiquitous practice that has incredibly damaging and long-lasting effects on even the most well-known brands around the world.
The bottom line is this: Marketers and advertisers can no longer afford to ignore ad fraud if they’re serious about reaching their goals and objectives. Here are some of the most important lessons and takeaways from these high-profile cases.
- No one is safe from ad fraud
Everyone — from small businesses to large corporations like Uber — is affected by ad fraud. Plus, fraudsters have no qualms over location: no matter where in the world you operate, you are susceptible to the consequences of ad fraud.
- Ad fraud is incredibly hard to detect using manual methods
Fraudsters use a huge variety of sneaky techniques and channels to scam and defraud advertisers, which means ad fraud is incredibly difficult to detect manually. This is especially true if organizations don’t have the right suggestions and individuals dedicated to tracking and monitoring the presence of ad fraud.
Even worse, when organizations do have teams in place monitoring ad fraud, they are rarely experts, and cannot properly pore through the sheer amount of data that each campaign produces to accurately pinpoint it.
- Ad fraud wastes your budget, distorts your data, and prevents you from reaching your goals
Ad fraud drains your budget significantly, which is a huge burden for any company. However, there are also other ways it impacts your ability to deliver results.
For example, fake clicks and click bots lead to skewed analytics, which means that when you assess advertising channels and campaigns based on the traffic and engagement they receive, you’re actually relying on flawed data to make future strategic decisions.
Finally – and as a result of stolen budgets and a reliance on flawed data – your ability to reach your goals is highly compromised.
- You’re likely being affected by ad fraud already, even if you don’t know it yet
As seen in many of these cases, massive amounts of damage were caused because the brands weren’t aware that they were being targeted by fraudsters. Plus, due to the lack of awareness surrounding ad fraud in general, it’s highly likely that you’re being affected by ad fraud already.
- You have options to fight the effects of ad fraud
Luckily, as demonstrated by these cases, there are some options available to counteract the impact and losses caused by ad fraud, such as requesting a refund or even making a case to sue. In such cases, ad fraud detection solutions are extremely useful to uncover ad fraud and gather evidence.
- But the best option is to prevent ad fraud from the get-go
The best ad fraud protection is ad fraud prevention. The only surefire way to stop fraudsters from employing sophisticated fraud schemes and attacking your campaigns is by implementing equally sophisticated solutions. Anti-ad fraud software solutions that use machine learning and artificial intelligence help you keep fraud at bay, enabling you to focus on what matters: optimizing your campaigns and hitting your goals.
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