Discrepancies in the analysis of the number of clicks and user sessions

The first differences between Google Analytics statistics and Facebook statistics can already be seen in the method of counting clicks and user sessions. So let’s start by explaining these concepts.

– A click is a parameter that sums up all users’ reactions to a given ad. So if you click the ad once and then click again, Analytics counts that as two interactions with the ad.
– The session, in turn, shows how many users clicked on the ad. Two or more clicks of the same user will be considered by the system as one session, provided that they occur within a 30-minute time window. Only when the time interval between clicks is greater, will the actions be considered as two separate sessions.

Up to this point, everything is quite simple and it would seem that there is no room for discrepancies in the counts here. And yet. Because when can you start counting users who actually reacted to the ad? Google Analytics claims that only when the user is on the page to which the ad is referring him. After all, he might have clicked the ad by accident and stopped loading or closed the tab in the browser before the landing page was fully loaded, and this is hardly an ad success. Therefore, such “incomplete” transitions are not counted in the Google Analytics system.

Facebook, on the other hand, will record each click, i.e. the user’s interaction with the ad, even if the recipient does not fully see the landing page or does not go beyond the Facebook platform at all. It is true that in the Facebook Ads Manager you can measure not only all clicks, but also clicks on links that lead beyond the platform – to the advertiser’s website. However, the Facebook system will also count those clicks that did not fully load the landing page. What is the conclusion of this? The number of clicks reported in the Facebook Ads Manager may be greater than the one we see in Google Analytics.

Tracking users between devices

Analytics is therefore much more accurate when it comes to counting sessions and clicks on a single device level. What about the situation when the user is using different devices and clicks on the ad, for example, first on the phones and then on the computer? Here, Facebook is much better at counting. This is because in order to use Facebook and thus click any advertisement there, the user must be logged in to his account. Most users use the same account on all devices, so Facebook’s algorithm has no problem distinguishing when it is dealing with the same user and when not.

In Google Analytics, the default data collection is based on cookies, and these are assigned to a specific device. Hence, each change of the device by the user qualifies him as a new person.

What does this mean in practice?

If the recipient first clicks on the ad on their phones and then reacts to it again on their computer, Google Analytics will register the ad as two separate users from different traffic sources. On the other hand, Facebook, if the recipient is logged into the same account on both of these devices, will recognize him as the same person.

Differences in attribution models

Conversion may be preceded by a variety of user actions. This means that before he or she fulfills our goal, e.g. buys an item in an online store, he may deal with the website in various ways. Let’s see it with an example. The user sees an ad for shoes from your Facebook store. He clicks it, looks at the shoes, but decides not to shop. After a few days, he decides that he needs shoes and enters a query to the Google search engine, for which he will receive an advertisement in the search engine with a link to your website. He clicks on the link, looks at the same shoes again, but decides to ask his wife for opinion before buying. In the evening, he will enter the search query again, but will not click the sponsored link, but choose an organic result, and this time he will buy shoes.

So to which interaction with the website can this purchase be attributed? Did the first contact with the offer, i.e. Facebook advertising, decide that the user has performed the assumed conversion? Or maybe the user did not remember it anymore when he searched for shoes in the search engine? So then the sponsored link would make it hit your store and make a purchase there. But after all, he did not buy shoes by entering the site through an advertising link, but through an organic result, so maybe he should be “responsible” for the conversion? On the other hand, there is a chance that the user initially had no plans to buy shoes and it was only advertising on Facebook that awakened this need in him. In this situation, the first ad would do its part to persuade him to buy.

The questions are constantly multiplying and it is not easy to find an unambiguous answer to them. Therefore, individual analytical tools may adopt different methods of calculating ad effectiveness, i.e. they have different attribution models. We will now show you what it looks like in the case of the Facebook Ad Manager and Google Analytics.

Facebook Ads Manager – attribution model

If the user makes a conversion on the page within 7 days from clicking on the ad, Facebook Ads will assign it to his ad (of course, if we have a well-configured FB pixel). The same will happen if the recipient meets the target within one day of being shown the ad. It is true that the user could later have contact with ads in other channels, but Facebook will attribute this success to itself anyway. This is currently the default attribution model for this channel and may be objectionable but legitimate. Facebook is not a strictly sales channel, so the task of advertising on this platform is to arouse the user’s desire to buy. So even if an advertisement did not lead to a purchase, but sowed a seed in the user’s mind, which then germinated and gave fruit, it is also a merit of advertising on Facebook.

For example, the recipient might want to compare prices with competitors before buying, or look for opinions about the presented product in order to finally go directly to the company’s website. However, he found it through an ad on Facebook, so the system rightly recognizes its participation in such a conversion. In addition, the Facebook system is not able to control whether the user was later exposed to ads created by other systems, so the assumption that the Facebook Ads campaign influenced the recipient’s decision is the best way to count conversions.

However, is it reliable? Unfortunately not. For this system, clicking an ad is not synonymous with loading the landing page, as we have already written about above. It’s even more difficult when counting views. Facebook’s algorithms take into account whether the advertisement was displayed to the user, but they do not measure the time that the advertisement was visible on the user’s screen. So it may turn out that yes, it appeared on the page, but it was scrolled so quickly that the user did not have a chance to even notice it, let alone read its content. Nevertheless, if the user subsequently performs a conversion within a certain period of time, Facebook counts the conversion as obtained from its ad.

Google Analytics attribution models

By default, Google Analytics uses a different attribution model – the last indirect input is counted as the one that decided to convert. What is an indirect input? Simply put, it can be any way to enter a website, except for directly typing its address in the browser bar. So if, for example, a user clicks on a Google Ads ad, but does not buy anything, and then enters the page by typing its address into the browser and converts on the page, Google Ads will receive the credit for it. Comparing this counting system with the Facebook system, it is easy to notice that the results of Facebook Ads campaigns in Analytics may be weaker than in Facebook statistics.

However, Google Analytics also offers other attribution models, and changing the default settings can significantly change the results presented by this tool. We can choose models such as:

– Last interaction – then the system assigns all credit for the conversion to the channel that the user used immediately before the conversion. This setting makes sense when your ad is targeting people who are determined to buy, not those at an earlier point in the funnel.
– Last Google Ads Click – All 100% “responsibility” for the conversion is attributed to the last ad displayed by the Google Ads system that the recipient clicked before converting. It is worth using this model only when you want to compare the effectiveness of Google Ads. Does not apply to statistics for Facebook ads.
– First Interaction – In this model, Analytics considers all credit for conversion to go to the channel where the user first encountered our site. It can be used in this case when we want to build brand awareness with advertising.
– Linear – considers 1 conversion = 100% and grants equal percentage of share to all channels through which the user came into contact with the page. So if he first saw an ad on Facebook, then clicked a sponsored Google Ads link and made a purchase, he will attribute 50% of the value of this conversion to Facebook Ads, and the other 50% to Google Ads. It is best to use this model when each user contact with the website is important to us.
– Timing – assigns different conversion shares to channels, depending on how many days before the conversion was done by the user. The closer the contact with a given channel is in time, the more important that channel is.
– Including items – this model also divides the share between channels that are on the purchasing path, but does not take time into account. Most often, in this model, 40% of the conversion value of the first interaction is assigned, 40% of the last interaction, and the remaining 20% ​​is divided equally among the other channels on the purchasing path.

Google Analytics or Facebook Ads – which statistics should be taken into account?

Advertisers often try to unify the results obtained from both tools as much as possible. You can, for example, change the attribution in Facebook Ads so that conversions are counted only within 1 day of clicking on the ad. However, before taking such steps, it is worth analyzing your business and industry or tracking the average length of your audience’s conversion path. Sometimes it’s not necessarily about fixing the discrepancy, but about accepting that both Google Analytics and Facebook are complementary tools that can be used in parallel to better understand your business with web analytics and make better marketing decisions.

Search without the phrase

If we want Google to omit pages related to an issue in the search results, we can put a minus after entering the search term, and the phrase to be excluded directly after it. The text entered in the search engine should look like this:

searched phrase -omitted phrase

Using an example, if we are looking for information about Greece, and in the search results we see a lot of offers from travel agencies, we can enter the keyword: Greece -Vacations. Then Google will omit the pages related to holidays in the ranking, and thus sites referring to, for example, the history of the country or current events, will be placed higher.

Search for a specific phrase

Thanks to the use of quotation marks, Google knows that it should treat our query only as a whole and not provide results tailored to only one of the words. This type of search will be useful, for example, when we want to find a product of a specific color, and the search engine stubbornly shows us this product in different colors. In this case, enter the phrase as shown below:

“Phrase searched”

So when searching, for example, for the keyword “red kettle”, we should only receive offers from stores that offer a kettle of just such a color.

Search on a specific website

Advanced search functions also allow you to limit the results to a specific website. This option is useful, for example, when a given site does not have a built-in search engine or its use is cumbersome. To get results from one domain, we should enter the query in the model:

site:www.searchpage.com keyword

So if, for example, we would like to search our website for all the subpages where we mentioned Facebook ads, we would have to enter the following query: site:Paraphrase-Online.com facebook ads. In this case, Google will show us all offers, blog entries, guides and other content related to this type of campaign.

Search for similar pages

If it happens that we want to find a page on the Internet similar to the one we like, we can also use the advanced search. It is possible after entering the password as follows:

related:www.thepageyouarelookingfor.com

In this case, the search engine will present us with pages with a similar business profile and similar content, thanks to which we can, for example, compare competing brands or read more about a given issue in another source.

Search for incomplete phrases

This type of refining the search is especially useful when, for example, we only remember a part of the title of a book, movie or song. By entering the remembered text with the appropriate tag, we let Google know that we want it to supplement the phrase with an additional, forgotten element. In this model, the query should look like this:

Search phrase *

Search for files in a specific format

Thanks to the appropriate command, we can also search Google for files of a specific format, for example pdf or doc. This function can be useful, for example, when looking for e-books or scientific articles on the web. In order to narrow the results to files of a given genre, enter the following into the search engine:

search phrase filetype: file format

Search for images of a specific size

Also in Google Graphics, we can narrow down the search field by introducing some restrictions – for example as to the size of the image. This function can be useful, for example, when we are looking for graphics for a desktop wallpaper or when we need a high resolution image. The following command is used to conduct this type of search:

Search phrase imagesize:widthxheight

An example of a search in this model might look like this: Buckingham Palace imagesize: 800 × 450. Of course, the size of the image is always given in pixels.

Search in a URL

Google also allows us to conduct more advanced searches, such as website URLs. Thanks to this, we can, for example, find those pages from a specific category that run their blog, and therefore post content of a guide nature. The query schema here looks like this:

allinurl:search term

Suppose you are looking for pages that have a blog about tires. In this case, we can enter the password allinurl:tire blog.

Search by prices

When we want to search for products at a specific price, we should use the dollar sign in the query like this:

search term $price

Although the query includes the US currency, we do not have to worry – the search engine will show us the results in your currency, and no conversion will be needed. So if, for example, we are looking for a laptop for 2000 euros, just enter in Google: laptop $2000. We can also ask the search engine to show the product in a specific price range, then the query should be: laptop $2000..$3000.

Social media search

You cannot count on the search engine to find all posts published on social media. However, by using the @ or # tags, we can ask Google to show us those that have been indexed. Thanks to this, in order to see mentions of a given topic on social networks, we do not have to laboriously wade through unrelated results. The following in the model will help:

@phrase searched
or
#search phrase

The first method is used to search for information about a person, band, brand, etc., and the second – more detailed issues.

Search for a phrase in the text

When we simply enter a query into a search engine, we get the results that, according to the algorithms, respond best to them. This does not mean, however, that in each case the specific phrase that we entered in Google will be in the text on the page. If we want to be sure that our keywords will appear in it, we should enter the query:

allintext:search term

Then the search engine will omit from the results those pages where the phrase was found only in the address, tags or meta description.

Google Tag Manager – what is it?

Google Tag Manager is a tool that allows you to easily add scripts (or tags) to the website, remove or modify them. In other words, thanks to it, you can manage all the tags we need from one place to analyze data from the website more effectively, increase conversion, track traffic sources, etc. Using GTM, we do not have to interfere directly with the website every time we want to implement a new script. site code. It is a kind of intermediary, thanks to which you do not have to insert any tags “rigidly”, burdening and slowing down the page. It also allows you to avoid errors that may occur when you try to implement the tag manually.

Over time, we place more and more tags on websites. The most popular are the Google Analytics tag, thanks to which we can collect data on traffic and conversion on the website, the Facebook pixel that allows us to measure the effectiveness of advertisements, or the Google Ads remarketing tag. However, there are also many other scripts that are useful from a marketing point of view. Thanks to GTM, we do not have to place all of them manually on the website – we just need to implement the Google Tag Manager code once, and we can implement all other tags through it.

How is Google Tag Manager built?

In Google Tag Manager, the account is the highest in the structure – it collects all the smaller subsets in the tool. Within the account, we can create containers, i.e. figuratively speaking, separate boxes for collections of tags. Each container has its own code to be implemented in the code of the page. After its implementation, the entire collection of tags contained in it is active on the website.

The tag itself is a type of tracking code that, once installed on your website, starts collecting data – this could be information about traffic, conversions, etc. – depending on the type of tag. Each tag should have an assigned rule that says when the script should run – we can add a rule that the tag should work on all subpages or only on some of them – for example, when measuring the conversion, we will assign a rule that the script should collect data only from the purchase confirmation page.

Assigning permissions in Google Tag Manager

In Google Tag Manager, we can grant permissions both at the account level and at the level of the container itself. If we want a user to have access to all the containers we have created, we should give them account-level permissions. We have two types of permissions here: Read Only and View, Edit and Manage. However, it is worth knowing that the second type of permissions cannot be edited within the containers – it only allows you to see what settings have been selected for each of them.

If we want to give the user the ability to edit the container or do not want to give him access to the entire account, we should grant permissions at the container level. In this case, we have three options: View Only (view only), View and Edit (view and editing) and View, Edit, Delete & Publish (view, edit, delete and publish). Thanks to this, we can freely manage access to the account and maintain full control over the data it contains.

Why is it worth having a Google Tag Manager?

Facilitation when making changes to the website
Sooner or later, most pages need updating or even more radical corrections. If, however, we change the appearance of the website, CMS system or template, it is necessary to transfer all scripts implemented directly in the code. When there are a lot of them, it is easy to skip any of them or paste them incorrectly, and in addition, it is simply tedious and time-consuming. By using the Google Tag Manager, we have an easier task – you just need to move the code to the container in which we placed the tags from a given site to trigger all the scripts on a given page. Therefore, it is worth thinking about implementing GTM at the beginning of running a website – at first it may seem that there are not many scripts, so this is an unnecessary difficulty, but their number can quickly grow and make any changes difficult.

Faster website loading
Each additional script in the page code makes the site a bit slower, and the longer the page load time, the more likely the user will get impatient. Thanks to GTM, it is easier to keep order in tags and to easily remove those that we do not need, so as not to unnecessarily burden the site. However, using this solution has one more important advantage – thanks to it, tags can be loaded asynchronously. what does it mean? Simply put, faster loading scripts do not have to wait for others, which shortens the overall page loading time.

Container template import option
If we have prepared and implemented a set of tags on one page, we can easily import it to a new account. Thanks to this, we do not have to waste time creating a completely new container with scripts if we launch a second or another website.

Ability to disable tags
If we implement the scripts directly on the website, we have to completely remove them if we do not want them to collect data further. However, we do not always want to decide on such a radical solution – sometimes we are not sure whether we will need a given tag in the future. With the help of Google Tag Manager, we can simply temporarily disable a given script.

Ability to quickly verify the correctness of the script implementation
Google Tag Manager gives you the ability to preview and debug, so you don’t have to wait to see if the tag has been properly implemented. Otherwise, we would have to wait for the tag to collect the data to be sure the implementation was successful.

Possibility to implement tags without the help of a programmer
When it comes to tampering with the website code, most people prefer to seek the help of a specialist to make sure that the change does not cause problems with the website. The need to involve a programmer in the implementation not only extends the entire process, but may also be associated with an additional cost. However, if we use Google Tag Manager, we can implement new scripts ourselves, being sure that we are not threatened by a long-term failure of the website caused by the new tag. If, as a result of our actions, the website starts to work incorrectly, it is enough to return to the container settings before the last script was deployed.