What is Google Analytics, and Why Can’t We Easily Troubleshoot GA Inaccuracies?
Google Analytics (GA) is a free web analytics service inside the Google Marketing Platform brand that tracks and reports on website traffic, allowing you to analyze in-depth detail about the visitors on your website.
Google Analytics’ metrics are based on client site performance and not on campaign or ad performance. Often, we see inaccurate reporting metrics between Demand Side Platforms (DSPs) and GA.
It is important to keep in mind that one will not equal the other and we need to look at the big picture when viewing GA data.
In this guide, you will find:
- How Site Latency Factors Into DSP vs GA Reporting
- Google Analytics (GA) Inaccuracies in Geo/Locations Reporting Explained
- Sessions vs Users in Google Analytics (GA) Explained
- Clicks vs Sessions in Google Analytics (GA) Explained
- Clicks vs Users in Google Analytics (GA) Explained
- Why are Sessions Showing up in Google Analytics on an Inactive Campaign?
- Why am I seeing high bounce rates in my Google Analytics (GA) on my Display campaigns?
- What are the Differences Between a Click-through URL, a UTM Code and a Conversion URL?
- Google Analytics (GA) FAQ and Helpful Links
How Site Latency Factors Into DSP vs GA Reporting
Most technical discrepancies in reporting stem from how and when each system counts an interaction. A media platform report may note a viewable impression served when over 50% of an ad is onscreen for more than one second. If the ad is clicked, the ad server will immediately register the action. However, site analytics (like GA) won’t count the action until the landing page fully loads.
This disconnect in reporting time frames is a common problem for sites with a high latency, or long page load times. For example, when someone clicks an ad but bounces from the site before the page completely loads, the website tracking code may not register the visit. In this case, media reports show a click, but site analytics do not show a corresponding session.
Minimizing page load time will help increase customer engagement as well as how well the analytics might match up to campaign reporting. But remember, latency isn’t the only technical problem to watch out for. Cookie blockers, setup mistakes and other errors can also impact how different systems interpret whether or not an action took place.
Google Analytics (GA) Inaccuracies in Geo/Locations Reporting Explained
Unfortunately, there is no way to guarantee that certain clicks, users, or sessions will not show up in GA as being out-of-area. However, geo reporting can be pulled directly from the DSP and is typically included in most reporting dashboards.
Due to measures put in place to protect individual user data, location data in Google Analytics can be inaccurate at the city level. Google only acknowledges that their location data in Analytics isn’t quite accurate in the far corners of their support pages, so it wouldn’t be surprising if the majority of business owners and advertisers are unaware of these inaccuracies. It is important to note how user location is determined in GA vs our DSP, The Trade Desk (TTD):
One of the best ways to make the inaccuracies of user location data in Google Analytics evident is to compare it to Trade Desk data. They each use different tools to determine user location because of Google’s policy on Personally Identifiable Information (PII). Precise location data, such as latitude/longitude data from GPS, sometimes falls under PII depending on the specific product being used.
In other words, Trade Desk can use precise location data because it publishes its location data in a way that cannot be connected to individual users within their platform. Conversely, precise location data would break the PII policy in Google Analytics because of how its location data can be connected to the actions individual users take.
Trade Desk has a variety of tools (listed below) it can use to determine a user’s physical location. However, it will always use the most-accurate tool to decide if a user is within the location targeting when multiple tools can be used.
- IP Address
- Device location: Device location can be determined in multiple ways:
- GPS – GPS uses satellites to derive lat/longs of a device
- Wi-Fi – Location is anywhere within the effective access range of the Wi-Fi router. The location of the router is only as accurate as the IP Address.
- Bluetooth – Short-range beacons are placed in fixed locations that can be used to determine the location of nearby devices, though this is not a common location identifier.
- Cell Tower – In the absence of GPS and Wi-Fi, Trade Desk will use cell tower data to determine the location. The accuracy of cell towers varies. It is possible that a cell phone can be connected to a tower within our geographical targeting, but the user and phone are located outside of it.
Google Analytics uses only the recorded IP address to estimate user location based on third party geolocation databases. The Google support page explains more on how the IP data in DSPs (like TTD and Google Ads) and Google Analytics can yield disparate results. IP addresses are routinely re-assigned, and DSPs like The Trade Desk update their IP data regularly to reflect these changes. The third-party data sources that GA uses may update their IP data on a different schedule, and might not reference the most current IP data. GA's third-party data source isn’t guaranteed to be 100% accurate, and little is known about which providers Google uses and how they use them. Incorrectly-entered data and recently-moved Wi-Fi routers can also contribute to the inaccuracy of IP data within the third-party database that GA gets its data from.
Sessions vs Users in Google Analytics (GA) Explained
Analytics measures both sessions and users in your account. Sessions represent the number of individual sessions initiated by all the users to your site. If a user is inactive on your site for 30 minutes or more, any future activity is attributed to a new session. Users that leave your site and return within 30 minutes are counted as part of the original session.
The initial session by a user during any given date range is considered to be an additional session and an additional user. Any future sessions from the same user during the selected time period are counted as additional sessions, but not as additional users.
Clicks vs Sessions in Google Analytics (GA) Explained
There is an important distinction between clicks (as in TTD reporting) and sessions (as in Audience reports). The Clicks column in DSP reporting indicates how many times advertisements were clicked by users. In GA, Sessions indicate the number of unique sessions initiated by a site’s visitors. There are several reasons why these two numbers may not match:
- A user may click an ad multiple times. When one person clicks on one advertisement multiple times in the same session, TTD records multiple clicks while Google Analytics recognizes the separate pageviews as one session. This is a common behavior among users engaging in comparison shopping.
- A user may click on an ad, and then later, during a different session, return directly to the site through a bookmark. The referral information from the original session is retained in this case, so the one-click results in multiple sessions.
- A user may click on an advertisement, but prevent the page from fully loading by navigating to another page or by pressing the browser's stop/back button. In this case, the Analytics tracking code is unable to execute and send tracking data to the Google servers. However, TTD still registers a click.
- To ensure more accurate billing, TTD automatically filters invalid clicks from your reports. However, Analytics reports these clicks as sessions on your website in order to show the complete set of traffic data.
Learn more about the differences between clicks and sessions.
Clicks vs Users in Google Analytics (GA) Explained
There are an important distinction between clicks (as in TTD reporting) and users (as in your Audience reports). The Clicks column in TTD reporting indicates how many times advertisements were clicked by users, while Users indicates the number of unique (deduplicated) users who clicked ads. There are several reasons why these two numbers may not match:
- A user may click on an ad multiple times. When one person clicks on one advertisement multiple times in the same session, TTD records multiple clicks while Analytics recognizes a single user. This is a common behavior among users engaging in comparison shopping.
- A user may click on an advertisement, but prevent the page from fully loading by navigating to another page or by pressing the browser's stop/back button. In this case, the Analytics tracking code is unable to execute and send tracking data to the Google servers, and no user is counted. However, TTD still registers a click.
- To ensure accuracy, TTD automatically filters invalid clicks from reports. However, Analytics reports all users who clicked ads in order to show the complete set of traffic data.
Why are Sessions Showing up in Google Analytics on an Inactive Campaign?
It’s possible to see inactive UTMs in GA reporting after a campaign is ended because creatives continue to be scanned, even when a campaign is not running, for creative verification processes initiated by DSPs and inventory suppliers. In order to stop UTMs from being scanned further, creatives can be archived upon request.
However, AdCellerant does not recommend archiving creatives unless absolutely necessary, as creatives can be shared across multiple campaigns and used for future campaigns.
Why am I seeing high bounce rates in my Google Analytics (GA) on my Display campaigns?
Display is considered a high-funnel product in advertising. High funnel marketing is in reference to strategies that target brand awareness over direct conversions. This might mean promoting the client's offerings through display ads as we are discussing here. It’s about getting the client's name out there, and serving the client's ads to an interested audience where they live.
Because display is higher up in the marketing funnel, the bounce rate can be high. This is because the user is not actively searching, but rather clicking on an image ad as they browse other content. The average bounce rate for a display campaign can range between 50-90% depending on the type of program that’s running. This can also depend on the amount of traffic that is being sent to the site. Since paid search campaigns are capturing users who are actively searching for exactly what the client has at that moment, they will typically have a lower bounce rate than display traffic. This is why it’s best practice to look at campaigns separately in GA. In launching a display program, it would be very typical to expect an increase in your overall bounce rate.
That being said, to help mitigate these high bounce rates, AdCellerant recommends changing the creatives every month to six weeks. A good ad should be a snapshot into what the client is promoting on their site. They should think about what the ad says or shows that makes the person want to click through. For example, if the ad has an image of a cute dog and then they click through and are taken to the client's site and see bicycles listed, they may not stick around. And while it’s good to get traffic to the client's site, the goal should be quality traffic that will spend time there and convert.
Speaking of the client's site, it is vital to consider the user experience. User experience can have a huge effect on bounce rate. Because so much time is spent making sure the traffic that is being pushed to the site is qualified, it’s really important to make sure that qualified users stick around and have a good experience.
- Does the client's website have enough content to answer the questions that users may have?
- Are pop-ups turning people away?
- How fast is the page load speed?
- Has the client optimized their site's mobile experience?
- Is the information users need easy to find?
- Is the site aesthetically pleasing, but does not necessarily cater to the user experience?
All of these items can impact the overall bounce rate, even if the traffic that is being sent to the site is very high quality. For example, if the client has a lifestyle video of a woman walking and drinking coffee in a park, but the product is a coffee shop, it would be best to show her interacting in the shop itself before she leaves on her walk.
When the client is looking at their marketing campaigns, it is important to remember that bounce rate is not a direct metric of campaign success.
What are the Differences Between a Click-through URL, a UTM Code, and a Conversion URL?
Click-Through URL (CTURL):
A click-through URL is a destination webpage (URL) that the user is directed to when they click on your ad. For example, your ad for Baby Clothes clicks through to the CTURL https://www.babyclothes.com.
UTM Source, Medium, and Campaign Codes:
A UTM code is a snippet of simple code that you can add to the end of a URL to track the performance of campaigns and content through Google Analytics (GA). There are 5 variants of URL parameters you can track - source, medium, campaign, term, and content. Dimensions you track via UTM codes show up in your analytics reports to give you a clearer insight into marketing performance.
UTM stands for "Urchin Traffic Monitor". This name comes from Urchin Tracker, a web analytics software that served as the base for Google Analytics.
***AdCellerant adds default UTM Source, Medium, and Campaign codes to all CTURLs we receive in our support portal for tracking purposes in the client’s Google Analytics (GA), if the CTURL does not already have UTM codes applied when submitted to us. The UTM Source, Medium, and Campaign codes we apply are Source: 3461, Medium: display/video/IP/email (depending on the product that’s ordered), and Campaign: the ticket number associated with that particular campaign from our support portal.
The UTM Source parameter allows you to track where the traffic originated from. The parameter added to your url is utm_source. Sources you may track could be Facebook, Google, bing, inbound.org, or the name of an email list.
Our UTM Source code looks something like this (in bold below):
The UTM Medium parameter tracks what type of traffic the visitor originated from – cpc, email, social, referral, display, etc. The parameter is utm_medium.
Our UTM Medium code looks something like this (in bold below):
The UTM Campaign name parameter allows you to track the performance of a specific campaign. For example, you can use the campaign parameter to differentiate traffic between different Facebook Ad campaigns or email campaigns. The parameter is utm_campaign.
Our UTM Campaign code looks something like this (in bold below):
- http://yourwebsite.com/your-post-title/ utm_source=3461&utm_medium=display&utm_campaign=12345
In addition to Google Analytics, “Conversion URLs'' are specific webpage URLs of the client’s site that the client wants to track pageviews on, specific to users who have been served an ad, whether or not the user clicked on the ad. The TradeDesk can track up to 5 conversion URLs per display campaign. Example conversion URLs are listed below:
Conversion tracking on conversion URLs can only be done if a Trade Desk pixel is placed on each webpage of the client’s site. We are able to track the clickthrough URL as a conversion URL.
The difference between a conversion URL and a clickthrough URL is that conversion URLs track general site activity (pageviews on various webpages of the client’s site as listed above) and a clickthrough URL is the landing page URL of the client’s site where the ads click through and immediately direct users to.
Google Analytics (GA) FAQ and Helpful Links
Setting Up Goals:
Best Practices (checklist):
GA & GAds - Data Discrepancies Issues:
Goal Creation (WordPress):
Goal & Funnel Creations: