Google Analytics Study Guide 1

Basic purchase funnel
In marketing, we have the concept of a purchase funnel. There are different stages within the funnel that describe customer interactions. A basic purchase funnel includes the following steps:

Acquisition involves building awareness and acquiring user interest

Behavior is when users engage with your business
Conversion is when a user becomes a customer and transacts with your business

But in the online world, we can measure many different aspects of the funnel using digital analytics. We can track what online behavior led to purchases and use that data to make informed decisions about how to reach new and existing customers.

Digital analytics
Think about an online store, such as the Google Merchandise Store. It might have a goal to sell more t-shirts. Using digital analytics, the store could collect and analyze data from their online advertising campaigns to see which are most effective and expand those marketing efforts. For example, the store could analyze geographical sales data to understand if people in certain places buy a lot of shirts and then run additional advertising campaigns in those areas.

Different kinds of businesses can benefit from digital analytics: Publishers can use it to create a loyal, highly-engaged audience and to better align on-site advertising with user interests.Ecommerce businesses can use digital analytics to understand customers' online purchasing behavior and better market their products and services. Lead generation sites can collect user information for sales teams to connect with potential leads.

How to track (GA)
To track a website, you first have to create a Google Analytics account. Then you need to add a small piece of Javascript tracking code to each page on your site. Every time a user visits a web page, the tracking code will collect anonymous information about how that user interacted with the page. For the Google Store, the tracking code could show how many users visited a page that sells drinkware versus a page that sells houseware. Or it could tell us how many users bought an item like an Android doll by tracking whether they made it to the purchase confirmation page.

Keep in mind that every time a page loads, the tracking code will collect and send updated information about the user's activity. Google Analytics groups this activity into a period of time called a 'session.' A session begins when a user navigates to a page that includes the Google Analytics tracking code. A session ends after 30 minutes of inactivity. If the user returns to a page after a session ends, a new session will begin.

When the tracking code collects data, it packages that information up and sends it to Google Analytics to be processed into reports. When Analytics processes data, it aggregates and organizes the data based on particular criteria like whether a user's device is mobile or desktop, or which browser they're using.

Google analytics organization
All of your Google Analytics accounts can be grouped under an 'Organization,' which is optional. This allows you to manage multiple Google Analytics accounts under one grouping. Large businesses or agencies could have multiple accounts, while, medium to small-sized businesses generally (only) use one account. When you create an account, you also automatically create a property and, within that property, a view for that account. But each Analytics account can have multiple properties and each property can have multiple views. This lets you organize your Analytics data collection in a way that best reflects your business.

GA properties
The Google Analytics Account determines how data is collected from your websites and manages who can access that data. Typically, you would create separate Analytics accounts for distinct businesses or business units. Each Google Analytics account has at least one 'property.' Each property can collect data independently of each other using a unique tracking ID that appears in your tracking code. You may assign multiple properties to each account, so you can collect data from different websites, mobile applications, or other digital assets associated with your business. For example, you may want to have separate properties for different sales regions or different brands. This allows you to easily view the data for an individual part of your business, but keep in mind this won't allow you to see data from separate properties in aggregate.

GA Views
Just as each account can have multiple 'properties,' each property can have multiple 'views.' You can use a feature called Filters in your configuration settings to determine what data you want to include in the reports for each view. For example, The Google Store sells merchandise from their website across different geographical regions. They could create one view that includes all of their global website data. But if they wanted to see data for individual regions, they could create separate views for North America, Europe, and Asia. The view level also lets you set Google Analytics 'Goals'. Goals are a valuable way to track conversions, or business objectives, from your website. A goal could be how many users signed up for an email newsletter, or how many users purchased a product.

- New views only include data from the date the view was created and onwards. When you create a new view, it will not include past data.
- If you delete a view, only administrators can recover that view within a limited amount of time. Otherwise, the view will be permanently deleted.

GA assign permissions
You can assign permissions to other users at the account, property, or view level. Each level inherits permissions from the level above it.By clicking 'Admin', Google Analytics lets you set user permissions for: 'Manage Users,' 'Edit,' 'Collaborate,' or 'Read and Analyze.'

'Manage Users' lets users add or remove user access to the account, property, or view.

'Edit' lets users make changes to the configuration settings.

'Collaborate' allows users to share things like dashboards or certain measurement settings.

And finally, 'Read and Analyze' lets users view data, analyze reports, and create dashboards, but restricts them from making changes to the settings or adding new users.

audience report
Audience reports are located under 'Audience' in the left-hand navigation. These reports can help you better understand the characteristics of your users. This can include what countries they're in, what languages they speak, and the technology they use to access your site. But it can also include data like age and gender, their engagement and loyalty, and even some of their interests.

active users report
Let's begin with the 'Active Users' report. This can show you how many users had at least one session on your site in the last day, seven days, 14 days, and 30 days. We call this 'site reach' or 'stickiness.' If your marketing activities and site content encourage users to visit and return to your site, the active users in each time frame should grow.

GA 'Demographics' and 'Interests' reports
. The 'Demographics' reports provide information about the age and gender of your users. The 'Interests' reports show your users' preferences for certain types of web content like technology, music, travel, or TV. This information is useful in two ways. First, if you know your target audience, it can help verify that you're reaching the right people. Second, it can help guide decisions about your marketing and content strategy.

GA location reports
The 'Location' report under 'Geo' is one of the most useful Audience reports. Google Analytics can anonymously determine a user's continent, sub-continent, country, and city through the IP address used by their browser. Notice the geographic heat map at the top of the report, which you can adjust to display different metrics. For example, switching the map to show 'percent of New Visits' lets you identify potential new markets based on new user traffic to your website. This can help you decide whether to build awareness or invest in customer loyalty in particular locations. You could also use the table below the visualization to identify areas that have a high number of conversions (or transactions), but low traffic rates. That could indicate untapped markets to target with advertising. Another analysis technique is to identify the regions where you already have a large audience, but lower than average performance. For example, if certain regions have a higher than average bounce rate (or users that leave after viewing a single page), you might need to optimize your advertising or website. Perhaps you need to translate your ad or site into the local language or add geographically-specific content.

Below 'Geo,' are a set of behavior reports that help you understand how often users visited and returned to your website. The 'New vs Returning' report breaks out acquisition, behavior, and conversion goal metrics for new and returning users. You can look at this comparison over time to see how audience loyalty may be shifting. Consider your website objectives, as well as your marketing activities, when evaluating the mix of new and returning users to your site.

Technology' and 'Mobile' reports
Underneath Behavior reports, the 'Technology' and 'Mobile' reports can help you understand what technologies your audience uses to consume your site content. These reports can help you fine-tune your site to make sure it's fully functional on different devices and browsers. For example, you can use the 'Browser and Operating systems' report to quickly identify issues with certain browsers on your site. If your site has a comparatively high bounce rate on a mobile browser, you may need to create a mobile-optimized version of your website with streamlined content and simpler navigation. It's also a good idea to understand if users are migrating from desktop to mobile and plan your development accordingly. You can use the 'Overview' report under 'Mobile' to see a breakdown of your traffic based on smartphones, tablets, and desktop devices. Check this report to see how quickly mobile usage of your site has grown over time. The 'Devices' report lets you see additional details about the devices used to browse your site. This includes the mobile device name, brand, input selector, operating system, and other dimensions like screen resolution. These reports can give your developers and designers direction on how to create a mobile-optimized experience to best suit your users.

GA traffic medium
When a user lands on your site, the Google Analytics tracking code automatically captures several attributes (or dimensions) about where the user came from. This includes the traffic medium, source, and marketing campaign name.

You can think of the medium as the mechanism that delivered users to your site. Some common examples of mediums are 'organic,' 'cpc,' 'referral,' 'email,' and 'none.' Let's look at these different types of mediums: 'Organic' is used to identify traffic that arrived on your site through unpaid search like a non-paid Google Search result. 'CPC' indicates traffic that arrived through a paid search campaign like Google Ads text ads. 'Referral' is used for traffic that arrived on your site after the user clicked on a website other than a search engine. 'Email' represents traffic that came from an email marketing campaign. '(none)' is applied for users that come directly to your site by typing your URL directly into a browser. In your reports, you will see these users have a source of 'direct' with a medium of '(none)'.

GA source
'Source' provides more information about the medium. For example, if the medium is 'referral,' then the source will be the URL of the website that referred the user to the site. If the medium is 'organic,' then the source will be the name of the search engine such as 'google.'
To identify effective traffic sources, we can look at the source/medium combinations with the most users, but that doesn't necessarily mean this was the best traffic. Ideally, traffic should be 'high quality,' meaning that users who arrive from a source engage with the website or complete a conversion. A good indicator of traffic quality can be bounce rate.

There are other ways to view which traffic sources bring the most engaged users to the site. Using the 'Channels' report, we could view traffic by channel, which bundles the sources together under each medium. Traffic sources are automatically grouped into basic categories (or channels) like Organic, Social, Direct, Referral, Display, etc. Clicking into each channel will break out the individual sources for that channel. If you want to group your sources differently, you can create your own channel groupings in Google Analytics. We'll cover this more in an advanced course.

GA referrals report
If you want to view your traffic organized by which sites have linked to yours, you can look at the 'Referrals' report. You can even click into individual referrals to see which specific web pages link back to your site. If you want to understand which specific pages of your site are being linked to, you can add a secondary dimension of 'landing page' to the report. This will show you which external sites are sending traffic to each of your specific pages, and potentially offer you a source of new advertising partnerships with those referring websites.

pageview method
You can find the 'Behavior' reports under 'Behavior' in the left-hand navigation. It's important to understand how Google Analytics calculates behavior data. If you recall, Analytics uses a small piece of Javascript code on your website to collect data. Every time a user loads a page on your website, this tracking code creates a 'pageview' that is reported in Google Analytics. Analytics uses this to calculate many of the metrics in the Behavior reports. For example, the 'Total Pageviews' metric is simply the sum of each time a user loaded a page on your website.

The 'Pageviews' metric shows how frequently each page on your site was viewed. By default, this report will show data by the page URI. The URI is the part of the URL after the domain name in the location bar of the browser. If you switch the primary dimension of the report to 'Page Title,' you can view this report by the title listed in the web page's HTML. Other metrics in the 'All Pages' report like 'Average Time on Page' and 'Bounce Rate' indicate how engaged users were on each page of your site. You can sort the report by these metrics to quickly find low-performing pages that need improvement or high-performing content to guide future content decisions.

GAcontent drilldown report
The 'Content Drilldown' report under 'Site Content' groups pages according to your website's directory structure. You can click on a directory to see the pages of your site within that directory. This is especially useful if you're trying to understand the performance of content in a particular section of your website. If you switch to the pie chart view, you can quickly see which sections of your site are most popular with your users.

GA landing pages report
The 'Landing Pages' report under 'Site Content' lists the pages of your website where users first arrived. These are the first pages viewed in a session. You can use this report to monitor the number of bounces and the bounce rate for each landing page. A high bounce rate usually indicates that the landing page content is not relevant or engaging for those users.

exit pages report
The 'Exit Pages' report under 'Site Content' shows the pages where users left your site. Because you don't want users exiting from important pages like a shopping cart checkout, it's a good idea to periodically review this report to minimize unwanted exits.

events reports
The 'Events' report tracks how users interact with specific elements of your website. For example, you can use this report to track when users click on a video player or a download link

marketing campaign tagging
Marketing campaigns can take several forms. Your business may want to advertise using text ads on search engine results, banner ads placed on strategic publisher websites, or you may have social media or email campaigns that communicate your brand and products to customers. It's common to use a combination of these marketing activities to drive sales and website conversions.

Marketing campaigns are tracked in Google Analytics through 'campaign tagging.' Campaign tags are extra bits of information that you add to the URL links of your online marketing or advertising materials. These include tracking parameters followed by an equals sign and a single word or hyphenated words that you designate.

GA campaign tags
When users click on a link with added parameters, the Google Analytics tracking code will extract the information from the link and associate that user and their behavior with your marketing campaign. That way, you can know which people came to your site through your various marketing activities. For example, the Google Store has a monthly email newsletter it sends to its customers with links back to the Google Store website. Adding a campaign tag of 'email' to these links allows the store to easily identify the users that came to the website from the email newsletter in Google Analytics.

Here are five different campaign tags that help you identify specific information about your campaign traffic. Medium, Source, and Campaign are required campaign tags. You can also add tags for Content and Term. We discussed medium and source when we introduced you to Acquisition reports.

'Medium' communicates the mechanism, or how you sent your message to the user. You could include 'email' for an email campaign, 'cpc' for paid search ads, or 'social' for a social network.

'Source' communicates where the user came from. This could be a specific web page or a link in an email. Source could also differentiate the type of medium. So if the medium was 'cpc' (or 'cost per click' paid traffic), the source might be 'google,' 'bing,' or 'yahoo.' If the medium was 'email,' the source might be 'newsletter'.

'Campaign' can communicate the name of your marketing campaign such as '2015-Back-To-School' or '2015-Holiday-Sale'.

'Content' can be used to differentiate versions of a promotion. This is useful when you want to test which version of an ad or promotion is more effective. If you're running a test between two different versions of a newsletter, you might want to label these tags 'v1-10dollars-off' and 'v2-nopromo' to help differentiate which newsletter the data is associated with in Google Analytics.

'Term' is used to identify the keyword for paid search campaigns. You would only use this field if you are manually tagging a paid search campaign like Bing or Yahoo!. We'll talk about the best way to track Google Ads in a later lesson.

GA URL builder
To navigate to the URL builder in the Help Center click the link at the end of this lesson and scroll down to the URL builder form. In the first step, type in the URL of your website (or where you want your ad or campaign link to take users). Then fill out fields for the campaign, source, and medium. Optionally, you can fill out the fields for term, content, and name. Term, content, and name can be any values you want, just make sure that they're descriptive enough to recognize when they appear in your Google Analytics reports.

A quick note about naming conventions. Typically, you'll use single words to name your tags. If you use phrases, then the URL builder will add underscores between the words to avoid spaces in the URL. Be sure to use consistent spelling and capitalization when entering tag values. Since Google Analytics is case sensitive, a campaign named 'PROMO1' in all uppercase will show up separately from a campaign named 'promo1' in all lowercase. Also, make sure that you use consistent medium names like 'display' for banner ads and 'email' for email campaigns.

When you click 'Generate URL' at the bottom, you can see that the URL Builder generates the link with all the correct campaign parameters attached. This provides an easy way to quickly generate campaign tags for tracking. But keep in mind, you can only use it to build out one URL at a time, so you probably won't want to use it to build each URL if you have a large campaign. Instead, you can use a spreadsheet to simplify the process. We've provided an example template at the end of this lesson that you can use to manage your campaign values for bulk URL-building.

If you click on the campaign name, you can see the source and medium data that you entered into the URL Builder. If you want to verify the other campaign tags you added to your URL, add a secondary dimension such as 'ad content.' This lets you view the primary dimension of 'Source/Medium' broken down by the 'content' tag you added to your links. The Google Store differentiated the 'content' tag for their email newsletters by whether they were offering promotions or not. By adding the secondary dimension of 'Ad Content,' we can see which promotions were most effective at driving people to the website.

business goals vs GA goals
Before we set up a goal in Google Analytics, let's draw a distinction between two types of goals: business goals and Google Analytics Goals. Business goals are actions you want your user to take on your website. Each time a user completes one of your business goals, we call this a 'conversion.' This could be signing up for a newsletter or buying a product. But in Google Analytics, you use a feature called 'Goals' to track these conversions. Once you configure Goals, Analytics will create conversion-related metrics. like the total number of conversions, as well as the percentage of users that converted. We refer to this as the 'conversion rate.'

GA goal funnel
When you set up a Goal in Google Analytics, you can also set up a 'goal funnel.' This is a data visualization of the different steps needed to complete the goal. This visual helps you identify where users are dropping out of the conversion process. Ecommerce businesses could use goals and funnels to see whether users are able to complete a multi-step checkout process. Other businesses could track newsletter sign-ups, contact form completions, page navigations, number of pages viewed in a session, or time on site. You must be an Administrator on the View in which you want to enable Goals in Analytics. Also note that you can only set up to 20 goals per view, so be thoughtful about which goals are most important to your business. First, you'll need to decide what you want to track based on your business goals. Since The Google Store is an ecommerce store, one goal they could track is successful checkouts. So, let's set up a goal every time a user reaches the checkout confirmation page. We'll also set up a funnel visualization, so we can see if users are dropping off on their way to the confirmation page. Note that this Goal won't track actual revenue; it will simply track how far users get at each stage of the goal and where they might abandon the process. Creating a funnel visualization to track goal completions is completely optional, but it can add a lot of visibility into each step of the conversion flow.

GA goal setup
To get started, we'll go into the Admin section. Then, under 'Views,' we'll click 'Goals.' Then we'll click 'New Goal.' Note that your Goal set-up may look a little different than the one for The Google Store, depending on your business type. Analytics provides you with some pre-set business goal templates. Since we want to track whether users made it to the checkout page for The Google Store, we'll choose 'Buy merchandise' and click 'Continue.' Because we want to track checkout confirmations, we'll name the goal: 'Checkout Complete.' Each goal uses a particular 'Goal Slot ID' that are numbered from one to twenty. The Goal Slot ID is a simple way to organize your goals. The default slot will always be the next slot available. If you're creating your first goal, the Goal Slot ID will be '1,' but you can choose a different slot if you have certain goals that you wish to group together.

Next we'll choose one of four Goal types. Each of these types is triggered by a particular user action. 'Destination' is when a user reaches a specific page on your site such as a thank-you page 'Duration,' is based on the length of a user's session; 'Pages or Screens' is based on how many pages a user views in a session. 'Events,' is for tracking specific actions on a site. We'll cover events more broadly in an advanced course.

Next, we'll enter the destination URL of the 'Order Complete' page in the 'Destination' field. The destination URL is the URL of the page that is shown when the user converts or completes the conversion process. Rather than enter the entire URL, we want to look for something distinctive in that URL that will allow us to track our goal using only this page.

Goal Value GA
If you want to assign a monetary amount to the conversion goal, you can flip the 'Value' toggle to 'On' and type in the amount that each conversion is worth. You would only use this if each conversion was worth a consistent amount to your business. For example, if each newsletter sign-up was worth 1 dollar to your business, you could set a goal value equal to '1.' Since we're tracking Google Store order completions and each order is a different amount, we'll leave this Value set to 'Off' for now. If we wanted to track actual revenue made from purchases, we would need to turn on ecommerce tracking, which we discuss in our Ecommerce Analytics course.

Goal Funnel GA)
Once you've verified your settings, flip the Funnel switch to 'On' to add the funnel steps. Each funnel step represents an action on your website that needs to be taken in order to accomplish the Goal. In this case, we'll need to include a unique part of the URL for each page the user has to view in order to check out and make a purchase. We can name each step in our funnel and add the unique part of the URL. If a step is required to complete the goal, move the 'Required' toggle to 'Yes.' For example, if we only wanted users who entered the funnel on the first step to show up in our funnel visualization report, we could set the first step to required.

GA and Google ads
Google Ads is Google's advertising system that allows businesses to generate text and display ads. Text ads show up next to Google search results by matching keywords you can bid on with users' search queries. Display ads are advertisements consisting of text, images, animation, or video that show up on a vast collection of websites called the Google Display Network. When people search Google for a particular product like 'a really cool Google t-shirt,' Google Ads will show a relevant text ad for the Google Store if the ad meets Google Ad's quality guidelines. This type of advertising can help attract customers from the millions that use Google Search and the Display Network every day.

When you link your Google Analytics account to your Google Ads account, you can: view Google Ads click and cost data alongside your site engagement data in Google Analytics; create remarketing lists in Analytics to use in Google Ads campaigns; import Analytics goals and transactions into Google Ads as conversions; and view Analytics site engagement data in Google Ads.

When you link your Google Analytics and Google Ads accounts, campaign data is shared between the two systems, but it still requires campaign tracking. Although you can manually add campaign tracking tags to Google Ads URLs using the URL Builder as we did earlier, there is a better option. Google Ads can automatically add a special campaign tag to your Google Ads URLs through a feature called auto-tagging. Auto tagging is required to get specific Google Ads dimensions into Google Analytics. These are some of the Google Ads dimensions available: Query match type shows how a Google Ads keyword is matched to a user search query. Ad Group shows the ad group associated with the keyword/creative and click. Destination URL shows the Google Ads destination URL configured in your Google Ads ads. Ad Format describes whether the ad is a text ad, display ad, or video. Ad Distribution Network shows the network used to deliver your ad. Placement Domain is the domain on the content network where your ad was displayed. And Google Ads Customer ID is the unique ID assigned to your Google Ads account.

Ad format dimension== GA/google ads
All of this data can help you better analyze the performance of your Google Ads campaigns. For example, you can quickly compare the performance of different ad formats using the Ad Format dimension. You can also fine-tune your keyword matching strategy by analyzing the performance of your keywords based on their match type. Note that these additional dimensions and reporting features are only available when you link your Google Analytics and Google Ads accounts.

GA/ads keywords report
Now let's look at the 'Keywords' report. This can help you understand how well keywords and individual ads are performing. For example, if a keyword is bringing in a lot of traffic but has a high bounce rate, it might indicate a disconnect between the ad and landing page content. If you have a keyword with a high conversion rate but low number of impressions (or number of times an ad was shown), you may want to raise your bid for that keyword, so the ad is shown more often and reaches a larger audience. You could also add 'Device Category' as a secondary dimension to break out these keywords by the kinds of devices that users were on when they clicked your ad and visited your site.

GA/Ads bid adjustment report
Finally, let's look at the 'Bid adjustments' report. Bid adjustments are a Google Ads feature used to automatically adjust keyword bids based on a user's device, location, or time of day. For example, if the Google Store opens a temporary location during the holidays to sell merchandise, they might want to add a bid adjustment to increase ad visibility on mobile devices within three miles of the store during the hours of operation.

The Bid Adjustment report in Analytics lets you analyze Google Ads performance for the bid adjustments you've set for your campaigns. You can use the selector at the top of the table to evaluate campaign performance by the device, location, time of day, and remarketing list bid adjustments.

How Does google analytics collects data
Let's start by showing you some specifics on how Google Analytics collects data. Remember that website data collection begins with a snippet of JavaScript tracking code that's included on every web page of the site where you want to collect data. The goal of the tracking code is to track each user interaction that occurs on your website. These interactions can be as simple as loading a page or something more specific like clicking a video play button or a link. The Analytics tracking code uses the domain of the website you are tracking to define it as a 'site' in your reports. With the tracking code installed, Google Analytics will drop a cookie in the user's browser for that website and any related subdomains. This makes it easy to track traffic on a single website URL domain or subdomain by default.

A hit
With each user interaction on your website, the Analytics tracking code sends what's called a 'hit' to Google Analytics. A 'hit' is a URL string with parameters of useful information about your users.

If we break down the URL string, you can see that it's passing some useful information to Analytics about the user that triggered the hit. For example, we can see things like: the language the user's browser is set to, the name of the page they're viewing, the screen resolution of the user's device, and the Analytics ID that associates that hit to the correct Analytics account.

Most common forms of hits
This is just some of the information passed in the hit, depending on the user interaction with the site and what is being tracked. The hit will also include other information like a randomly-generated user identifier. This will allow Google Analytics to differentiate between new and returning users. The three most common types of hits are: 'pageview' hit''event' hits and 'transaction' hits.

A 'pageview' hit is triggered when a user loads a webpage with the tracking code. This is the most common type of hit sent to Analytics. Every time a user opens a page with the tracking code, a new pageview hit will be sent.

An 'event' hit lets you track every time a user interacts with a particular element on your website. For example, you can track whether users click a video Play button, a particular URL, or a product carousel. Event hits pass four parameters of data in the URL: event action, category, label, and value. You can use these to categorize interactions in reports that are specific to your website. We'll go into more detail on event tracking a little later.

A 'transaction' hit (also called an 'ecommerce' hit) can pass data to Analytics about ecommerce purchases such as products purchased, transaction IDs, and 'stock keeping units' (or SKUs).

There are additional hits such as 'social hits' that can pass likes, shares, or tweet data; and 'page timing hits' that allow you to report on page timings, but the Pageview, Event, and Transaction hits are the three most common.

How Analytics understands things
 Google Analytics widens that data using other sources such as IP address, server-log files, and other ad-serving data. Using this additional information, Analytics can understand things like: a user's location; specifics about their browser and operating system; their age and gender; and the source/medium that referred them to a site.

Steps in which GA processes data
First, Analytics determines new vs. returning users. Then it categorizes hits into session (or periods in which the user engaged with the site). Next, it joins data from the tracking code with other data sources.

In the first step, Google Analytics differentiates new from returning users. When a user arrives on a page with tracking code, Google Analytics creates a random, unique ID that gets associated with the user's browser cookie. Analytics considers each unique ID to be a unique user. Every time a new ID is detected, Analytics counts a 'new user' and sends it over with the hit. When Analytics detects an existing ID, it sends a 'returning user' value with the hit. There are a couple of limitations to note about differentiating users. Since Analytics uses a browser cookie to determine unique users over a given session, this information will be lost if a user clears or has blocked that cookie in their web browser. If a user clears their browser cookies, Google Analytics will set a new unique ID the next time a browser loads a tracked web page. Analytics will then count that user as 'New,' rather than 'Returning.' Google Analytics can identify users over multiple sessions, as long as the sessions happen in the same browser on the same device. Analytics doesn't recognize users who visit your website from different devices by default and will count each device as a unique user.

Next, in order to understand a user's level of engagement with a website, Google Analytics groups user hits based on the time in which they were generated. To measure these periods, Analytics uses a metric called 'sessions. 'Remember that on websites, a session begins when a user navigates to a page that includes the Google Analytics tracking code and generates a 'pageview' hit. It will end after 30 minutes if no other hits are recorded. If a user returns to a page after a session ends, a new session will begin. For our first example, If a user visited the homepage of the Google Merchandise Store and then left immediately without clicking on anything, Google Analytics will record one 'pageview' hit for that user in a single session.

Let's take a look at a second example: A user lands on the homepage of the Google Merchandise Store. The session begins with a 'pageview' hit. Then the user clicks the play button for a video that is being tracked with event tracking. This triggers an 'event' hit. Google Analytics will record two hits for that user in that session: a 'pageview' hit for the home page, and an 'event' hit for clicking the play button. While sessions time out after thirty minutes of inactivity by default, you can change this setting in your configurations to better align with user behavior on your site. For example, a site with a goal to get users to watch videos may not want sessions to timeout after thirty minutes. They can extend session timeout to the average watch time of the videos on the site.

In the third step of processing, Google Analytics will join the data collected by the tracking code with other sources that you've specified. Let's look at two ways to add data from external systems using the measurement protocol and linking to other Google accounts. The measurement protocol lets you send data from any web-connected device like point-of-sale systems or web-connected kiosks to Google Analytics. Unlike the tracking code which sends hits automatically, if you want to collect data from a system outside of Google, you must pass the data collection hits manually in a URL string. The measurement protocol defines how to construct your hits using a customized tracking ID and send those hits to your designated Google Analytics account. You can find more information about the Measurement Protocol in the Analytics Developer documentation linked at the end of this lesson. Google Analytics can also link data from other Google marketing tools like Google Ads, AdSense, or the Google Search Console. This allows information like Google Ads clicks, impressions, and cost data to be viewed in your Analytics account.
 

(Contd. - Part 2)