Qujam’s geofence advertising platform operates on a Demand Side Platform (DSP) structure. The targeting, reporting, and capabilities are ideal for hyper-location based targeting for programmatic advertising strategies. We’ve worked closely with our internal team and external technology partners to help us get to the bottom of a very complex question:
Why Are There Discrepancies Between GA4/Google Analytics data and Geofencing (Programmatic DSP) data?
As advertising experts, we believe that we are obligated to push the boundaries and answer some difficult questions. One common and frustrating question we’ve faced from Qujam users is: Why Are There Discrepancies Between GA4/Google Analytics data and Geofencing (Programmatic DSP) data?? As we dig into this concern, we firstly confirmed that GA4 (Google Analytics) does appear to have reporting discrepancies when compared to Geofencing data. If fact, all programmatic digital advertising reporting have noticeable differences in data to GA4/ Google Analytics. So, we’ve scoured blogs, articles, video content, consulted with experts, and ran internal experiments on our own advertising campaigns to try to find a formulaic approach on how to cross-reference these two sets of data.
How Come The Date Doesn’t Match:
1. Attribution and Geographic Inaccuracies: Google Analytics is a great tool, but a free tool. Google Analytics originally came out in 2005, and GA4 was officially released in 2020. GA4/Google Analytics is a great resource and tool; but, it has flaws, and Google is transparent about that (supportive resource links are available at the bottom of this article which expand on this subject). What we, at Qujam, believe to be the main issue(regarding the topic of this article) is that GA4/Google Analytics accounts for every user that navigates to a website. Many would say, “Isn’t that a good thing?” In our opinion: Not necessarily. This means that GA4/Google Analytics is counting human and non-human users (i.e. test clicks from ad campaigns and bots, to name a couple). Non-human users impact every GA4/Google Analytics account and can skewed information in multiple intendances.
Additionally, GA4/Google Analytics often doesn’t always know where users are specifically physically located and channel based. However, because GA4/Google Analytics takes into account every “user,” the system’s solution is to do an educated guess as to what location and channel to apply the user to. This sometimes means that users’ geographic location and channel of entry are incorrectly assigned. For example, if GA4/Google Analytics identifies that website traffic is coming from the United States, but it is unable to identify an other more specific information, Google will often give Coffeyville, KS the geographic credit for the user because Coffeyville is in the center of the United States. Other geographic misattribution can also happen which cause users’ geographic location traffic data to be inaccurately in GA$/Google Analytics. Here is a wonderful, brief Forbes article on the subject.
GA4/Google Analytics users can sometimes be placed in an incorrect attribution channel. As an example, a user of unknown attribution origin may get attributed to a programmatic advertising campaign when, really, that user arrived via another channel.
Regulations around privacy additionally make it problematic to capture all data accurately within GA4/Google Analytics. As an example, Safari and similar apps make it very difficult to track activity due to their company’s privacy-focused setups. Despite these limitations around privacy, GA4/Google Analytics will still records all website activity and then it allocates a best guess on where that traffic physically and digitally came from. This can create a significant amount of guessing and inaccurate GA4/Google Analytics data from advertising campaigns (taking into account that Safari is the #1 web browser for Apple/IOS products, and mobile apps can easily account for around 50% of banner advertising campaign traffic).
The technology that Qujam leverages for reporting is on the other end of the scale because our technology actually is set up to exclude data attributed to test clicks, fraud prevention, or that have not enough or missing data. We believe and endeavor to only trying to report on data that is believed to be true human activity. Not only is “bad” data filtered from reporting, but Qujam users are not charged for impressions that are identified as non-human. In other words, GA4/Google Analytics is non-discriminatory about the data it reports on resulting in everything being included, but Qujam’s technology (and other programmatic DSP ad platforms) is significantly more conservative and takes measure to try to only report on clean data.
2. Test Clicks: Qujam’s technology runs automated test clicks on every campaign potentially multiple times through out a geofencing campaign ensure things are working properly. The Qujam technology also removes test clicks from the data reporting. However, GA4/Google Analytics does not.
Just the element of test clicks cause noticeable discrepancies between the Qujam (other programmatic platforms) and GA4/Google Analytics. The most noticeable issue is that GA4/Google Analytics can often report on inflated user and new-user data compared to the programmatic provided information. In our deep dive tests conducted by Qujam for this article, we found that 24.97% of GA4/Google Analytics users were attributed to our campaigns were identified as test clicks. This resulted in an over-inflated number of users reported by GA4/Google Analytics, but it also had a noticeable on the bounce rate and average session data in GA4/Google Analytics. Test clicks are tracked by GA4/Google Analytics with a 0 seconds spent on webpage time. This, in turn, affected GA4/Google Analytics’ bounce rate and average session numbers in a false, negative manner.
Let’s zip through some math on an average landing page session to bring in a bit more context. Let’s imagine we have 150 real, human users on a webpage, averaging 45 seconds per session. Now, assume to say GA4/Google Analytics reports 50 more users to the page that are actually programmatic test clicks. These 50 test clicks would have an average of 0 seconds per session on the website. That would be a total of 200 reported users in GA4/Google Analytics. Google Analytics will imply that your website had 200 users (but this is technically false) who spent an average time of 33.75 seconds on the webpage (also false). In reality, you had a few less people on your website, but the real people that were there spent an average for 45 seconds.
In addition, user traffic from the advertisement preview screen within a campaign will also be counted in GA4/Google Analytics, but not in Qujam’s reporting. This would happen if a human ad op professional (i.e. a Qujam team member) tests the ad from our backend dashboard during any customer assistance or quality assurance events. These clicks tend to result in a short amount of time on site, which negatively impact the bounce rate and the average-time-on-site data in GA4/Google Analytics. We have found that these points of entry into a website tend to be placed under “Referral” user-traffic in GA4/Google Analytics and often accompanied by the a title like: eastads.simpli.fi, westads.simpli.fi, or centralads.simpli.fi…which leads us to our first GA4/Google Analytics data scrubbing tip…
Data Scrubbing Tip #1: If you are running advertisements on Qujam and see “Direct” user traffic in GA4/Google Analytics from a UTM code that includes the word “scrub” in it—or, if you notice “Referral” user traffic from something called eastads.simpli.fi, westads.simpli.fi, or centralads.simpli.fi–then thpse data points are either a result of test clicks or advertising preview clicks and should be calculated out of your GA4/Google Analytics data analysis.
Another important thing to note about test clicks from Qujam is that the amount of automatic test clicks often significantly increases whenever new creative advertisements are added or replaced in a campaign. If you are adding a lot of creative and/or replacing it frequently, then you will experience more test clicks than a campaign with less creative items and alterations. This is because Qujam, our technology partners, and publishers all have quality accordance protocols/automations to do extra tests clicks or reviews when new advertising creative is updated to a campaign. We know that test clicks and review can make the GA4/Google Analytics a little off, but we believe it to be important to the quality and functionality of our customers’ campaigns.
3. The Complexities of the Cookies: GA4/Google Analytics relies on cookies for the tracking of data. We’re not going to get into how cookies and GA4/Google Analytics work with digital advertising in this article too much, but for more information we found this solid article with images for you. What we do want to mention about this subject is this: A big portion of digital programmatic advertising (primarily banner/display advertisements) appears in apps. Examples are weather app, games, news apps, etc… While apps are a wonderful advertising resource for distribution and audience attention, they can be a bit of a nightmare for cookie-based tracking because apps are cookie-free environments. Despite these limiting factors, in-app traffic is recorded in GA4/Google Analytics no matter what, and GA4/Google Analytics, again, makes an educated guess as to where the traffic is coming from.
Additional issues, like double-counting users, can happen due to cookies. If GA4/Google Analytics “cookies” a user from a UTM code and then that same user comes back to the website, then they will most likely be attached to the last known campaign and counted twice in GA4/Google Analytics. This leads us to our second GA4/Google Analytics data scrubbing tip…
Data Scrubbing Tip #2: While advertisers have the option to set up a digital programmatic campaign to exclude in-app inventory, we found that to be against best practices and don’t include it as an option on the Qujam interface. At Qujam, we tested this ourselves with a multi-targeted banner advertising campaign to see if it helped clean up data discrepancies in GA4/Google Analytics. Unfortunately, it did not make a noticeable difference if any. It did, however, hurt the success of the campaign due to it’s access to less inventory. The Cost Per Thousand (CPM) increased a little bit (+0.7%), the Cost Per Click (CPC) increased a lot (by +132.9%), and the Click Through Rate (CTR) significantly decreased (by -56.8%). The juice was not worth the squeeze when we removed in-app advertising inventory.
4. Difference in Data Language: GA4/Google Analytics and programmatic advertising data such ad Qujam are essentially speaking two different data languages. Front-end Demand Side Platforms and Saas options like Qujam reports primarily on what is happening before a user gets to a website (such as advertisement impressions, clicks, view through rates (CTR), etc…). Additionally, you are able to track some conversion data on the programmatic advertising side; however, all other programmatic based data reports on the pre-website activity. Qujam for example tracks physical conversions (AKA someone sees an ad and then they physically show up at a designated conversion zone.) GA4/Google Analytics’ data, in comparison, primarily reports on data regarding what is happening when a user is already on your website. A click (programmatic talk) doesn’t equal a user (Google talk) and vice versa…so you often cannot compare the two data sources as apples-to-apples.
5. People Don’t Stay in One Spot and Have Multiple Devices: When it comes to a geofence advertising campaign, the targeting collects devices because it was in a hyper-specific location, and then ads are served to that device for up to 30 days. In that time, that device and person could be traveling. If so, then their location data on GA4/Google Analytics would should where the are when they navigate to a website even if they were collected from a geofence in another state.
Additionally, Qujam geofencing used cross-device matching to serve ads. This means that if the device that was collected from entering a geofence is connected to another device like a cell phone, tablet, TV, or computer, the system will serve ads on those devices as well. Sometimes those connected devices are in other geographic areas.
Why You Should Get Completely Caught Up on Ad Clicks Alone.
We hope this article provides a useful guide on how to read between the ad and website data lines. That said, when it comes to programmatic advertising, it’s important to keep the following in mind: Most people don’t click on the ads! However, that does not mean that the advertising isn’t working. How you might ask? Let’s add some perspective:
The United States national display ad Click Through Rate (CTR) is .05% – .08% (self-promoting sidenote: Qujam’s geofence advertising tends to be 2x to 3x higher than this average). Using theses national averages though, this means that 99.92%-99.95% of the times that a display advertisement is served, a click does not occur. So, if you run a geofencing campaign that delivers one million impressions, then it is not uncommon for 999,500 of those impressions to not result in a click Does that mean those 999,500 impressions had zero value? Of course it had value! Otherwise, any non-clickable format of advertising would be considered to have no value (i.e. TV, radio, print, out-of-home, transit, and even other digital options like OTT, digital audio, and more). It’s makes sense that advertisers can get so caught up in the click information that they forget that most of the value happens outside of the direct clicks. Having your message be experienced thousands or millions of times has a lot of value if it’s a compelling message and in front of the right audience!
You may be asking, “But aren’t clicks all we have to base the success of the campaign on.” Of course not. Not only does the Qujam platform provide other valuable data points like impressions, view through completion rates, CPMs, and physical conversions, but there are multiple tracking tools available, but we’re going to provide you two key, free data points to look at when analyzing programmatic digital advertising success which includes geofencing campaigns.
- Monitor paid and organic search traffic. It is common and desired for target audiences whom see any type of digital ad to not click on it and then do a search engine search for the service, product, or brand, instead. We have noticed a 10%-50% average increase in search traffic when a Qujam campaign is launched. Analyzing and comparing the search based and direct traffic tells an important part of the story
- Leads and Sales Fluctuation: It’s quick unlikely that a prospective customer says they saw your display ad, video pre-roll ad, OTT/CTV ad, or digital audio ad. While lead tracking poles are excellent information to gather, we don’t recommend customer-polling as your only means of analyzing data because often the last point of contact (often Google) or the most memorable creative (video or audio) gets mentioned. Additionally, we highly recommend to look for correlating preforming trends in website and store traffic, leads, and sales comparing the beginning of a digital (or any) advertising campaign, media shift, and/or creative change to a similar time period. You will ideally be able to collect and compare this data over an extended period of time to help identify more reliable and meaningful patterns. If you track this macro-data, a story of what is/isn’t working should emerge.
Although we always encourage Qujam users to revise and compare sales data as one key performance indicator, it’s important to share that completed sales are not always the perfect indicator of any advertising effort’s success. Traffic and leads are considered truer metrics because advertising does not completely sells a product or service, but alternatively it provides the brand opportunities to sell their product or service. This might be through their website, sales department, or other avenues. Due to these factors that are outside of the advertising control, that’s why we recommend analyzing advertising results when it comes to sales against close sales, leads, and traffic. We have found multiple times that if leads are up and website traffic is up but sales are not tracking at the same rate, then there is often and issue deeper within the sales funnel as opposed to an problem with the advertising.
Case Study: Why Ad Clicks Aren’t the Most Important Metric of Success, Anyway
We had a new business to business client that ran a geofencing display campaign. They were super intelligent and analytically focused, so the GA4/Google Analytics versus programmatic/geofencing data was something they wanted to get their heads wrapped around. After walking them through the information in this article, below is how they where able to assess their campaign:
The advertiser compared the prospects that were not being served geofencing display campaign versus the prospects that were being targeted with the banner ad campaign at a sales opportunity level. They discovered that their prospective customers who received geofence banner ads were about 4x more likely to turn into a lead than those that weren’t getting served ads. Additionally, they saw a 60% increase in search engine traffic to their website (+1,334 users) when compared to the prior month, and the comparison to the same period last year was an even larger increase as +123.3% in total search traffic (+1,965 users). This jump correlated to the time of their geofencing campaign and is one of multiple stories we’re heard.
Additional Resources:
- Simpli.fi: Mobile & Google Analytics (Analysis) – James Moore, CRO: https://simpli.fi/wp-content/uploads/2017/04/Mobile-and-Google-Analytics.pdf
- Simpli.fi: ADTECH MYTHBUSTER SERIES: DISCREPANCIES WITH GOOGLE ANALYTICS: https://simpli.fi/adtech-mythbuster-series-discrepancies-google-analytics/
- Centro: Why do I see discrepancies in my reporting? https://dspsupport.basis.net/hc/en-us/articles/115013104327-Why-do-I-see-discrepancies-in-my-reporting-
- Cogei: Data Discrepancies: DSPs vs Google Analytics: https://www.coegipartners.com/blog/2020/01/15/data-discrepancies-dsps-vs-google-analytics/
- Smart Insight: The mystery of data discrepancies finally solved: https://www.smartinsights.com/digital-marketing-platforms/big-data-digital-marketing-platforms/the-mystery-of-data-discrepancies-finally-solved/
- JR’s Growth Tips: 3 Biggest Mobile Ad Tracking Pitfalls Explained & How to Deal With Them: https://www.growth-consultant.com/3-biggest-pitfalls-of-mobile-ad-tracking/#rqsa1nzcutiqsrg6u77aso
- Analytics Edge: Misunderstood Metrics: Google Analytics Users: https://help.analyticsedge.com/article/misunderstood-metrics-users/
Google Support Links:
- Common questions about Google Ads Clicks and Analytics Sessions: https://support.google.com/analytics/answer/4588454?hl=en#:~:text=Google%20Ads%20account%3F-,Why%20do%20I%20have%20more%20sessions%20than%20clicks%3F,gclid%20value)%20to%20that%20user.
- The difference between Google Ads Clicks, and Sessions, Users, Entrances, Pageviews, and Unique Pageviews in Analytics: https://support.google.com/analytics/answer/1257084?hl=en
- Data discrepancies between Google Ads and Analytics: https://support.google.com/analytics/answer/1034383
Troubleshoot Google Ads clicks vs. Analytics sessions: https://support.google.com/analytics/troubleshooter/7400792
If you have additional questions, please feel free to contact us. You can also create your own Qujam account here to start geofencing on your own.
