Google

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 "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.

metrics

All Google Analytics reports are a single dimension, and the corresponding metrics for each value of that dimension. You'll notice that most reports in Analytics use rows for dimensions, and columns for the associated metric data. When you set up configurations like Goals or Enhanced Ecommerce, those metrics will be included as well. Analytics calculates the metrics that get grouped in various dimensions in two ways. Metrics are either calculated in aggregate such as total sessions, users, or pageviews, or specific dimensions (like Sessions or New Users per country). These are based on calculations Google Analytics performed during processing when it categorized the data it collected into users and sessions. Let's look at how a few key metrics are calculated: Analytics can derive the "Time on Page" by taking the timestamp of a pageview hit and subtracting that from the timestamp of the next pageview hit. "Pages per session" is simply the average of how many unique pageview hits the user generated during their session. Average session duration is the average time spent from the first hit until the last hit before a user leaves the site or the session times out. Bounce rate is calculated by looking at users who only had one interaction on your site without a second interaction to calculate the session duration or time on page. If this occurs, the pageview of a bounced visit is assigned a session duration and Time on Page of zero.

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.

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.

Filters

As we discussed in Google Analytics for Beginners, you can set a filter on a view that can exclude particular data, only include particular data, or modify the data during processing. This helps you align the data that shows up in your reports with your business needs. Filters are essentially "rules" that Google Analytics applies to the data during processing. If the "filter type" is true, Google Analytics will apply the filter to the data. If the filter type is false, Google Analytics won't apply the filter. There are two reasons you might want to apply filters. You may need to transform the data that shows up in a view. For example, you might want to include only data from a particular country in a view devoted to reporting on that country. Or you might want to exclude any internal employee traffic from a view reporting on customer data.

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.

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."

custom metric

Custom Metrics let you collect metrics in Google Analytics that are specific to your business. This can be the number of ads that loaded on a page, the bandwidth that the page consumed when it loaded, or the total number of brand pageviews that each of your marketing channels leads to. Similar to Custom Dimensions, you collect Custom Metric data using JavaScript that's implemented on a page. When a user lands on that page or performs a specific action, the Custom Metric will be sent as an additional parameter attached to the hit. You first have to name the Custom Metric. Then you have to define its scope. This is based on how this metric data will be generated. Unlike dimensions, Custom Metrics can only have a scope of "hit," or "product." If you select "hit," the Custom Metric will be incremented with each hit sent over by the tracking code and totalled up in Google Analytics. If you select "Product," the Custom Metric can increment by whatever cost you assign to the product. We'll select "hit," since we want the Custom Metric sent over with each pageview hit of Android merchandise pages. Next, we'll need to specify the format of the Custom Metric. You can select a basic integer, a decimal value, or a time-based value. Since we want to total up pageviews, we can send a basic integer of "one" with each hit. This will then increment the Custom Metric in Google Analytics by "one" each time a pageview hit fires. You can also specify minimum and maximum values that determine whether Analytics will process this metric and include it in your reports. This can help prevent accidental large or small values from being collected and affecting your reporting. Since we know we don't want our range to exceed 1, we can set a minimum value of 0 and a maximum value of 2. When you save a Custom Metric for the first time, you'll be taken to a screen with JavaScript to include on your website. You'll need to copy the code to include on each page you want the Custom Metric to be sent. Then click "Done." You'll be taken to an overview screen where you can see all of the Custom Metrics that you have set up in the property. Notice that, similar to "Goals" and "Custom Dimensions," Google Analytics assigns an index (or slot number) for each Custom Metric you create. Notice that you cannot choose which index number is assigned; they are assigned in the order you created them. After you set up the Custom Metric, you must add the JavaScript tracking code you copied from Analytics to your website to collect the data with the hit. Like Custom Dimensions, each Custom Metric appears as a parameter of index-value pairs. "Index" refers to the index number of the Custom Metric you created in Analytics. Value is the metric that will be attached to the hit.

custom dimensions

Custom dimensions are similar to default dimensions except that you define what they are and their value. This let's you collect data that's customized specifically for your business. This can be incredibly powerful because it enables you to report on particular characteristics of your users or their behavior within the Google Analytics data you've collected. You collect data for a Custom Dimension using JavaScript tracking code that's implemented on a page. When a user lands on that page or performs a specific action, the Custom Dimension will capture that data and send it over as an additional parameter attached to the existing hit. You can then use these Custom Dimensions in your reports. You'll first have to name the Custom Dimension and then define its scope. For example, if you want the dimension to include every time a user visited a particular page or performed a singular action, you will need to set a hit-level scope. If you want the dimension to group data associated with a particular product, you will set a product-level scope. If the dimension was organizing data for the duration of a session or for a particular user, you can set session- and user-level scopes, respectively. Like standard dimensions and metrics, Custom Dimensions and Metrics can only be paired with dimensions or metrics from a similar scope. When you create a Custom Dimension for the first time, you'll be taken to a screen with JavaScript to include on your website. You can copy the code, then click "Done." You'll be taken to an overview screen where you can see all of the Custom Dimensions that you have set up in that property. Notice that, similar to Goals, Google Analytics assigns an index (or slot number) for each Custom Dimension you create. Note that you cannot choose which index number is assigned; they are assigned in the order you created them. After you've set up the Custom Dimension, you must implement the JavaScript tracking code you copied from Analytics into your website code to collect the custom data. Different businesses will do this in different ways, depending on their data collection method and what data they wish to collect. Google Tag Manager is a great option for managing Custom Dimension tracking code more easily. You can use Custom Dimensions as secondary dimensions in standard reports or as primary dimensions in Custom Reports (which we'll discuss later). For example, if the Google Merchandise Store wanted to see which products were most popular among employees and retail customers, we can open the Product Performance report under Conversions in Ecommerce and add the secondary dimension we set up of "User Category." Note that you won't be able to apply a Custom Dimension to data you have previously collected. You'll have to create the Custom Dimension first and let it be applied to your data during processing in order to use it in reports.

data import

Data Import lets you combine this offline data to the hit data that Analytics collects from your website. This will allow you to include your own business-specific data you collected independently to give you more context and insight in your reports.

dynamic remarketing

Dynamic Remarketing with Analytics lets you target remarketing ads more precisely. It enables you to target based on content or products users previously viewed on your site, related and top-performing content and products, and purchase histories and demographics. For example, the Google Merchandise Store can collect product IDs from the merchandise that users viewed on their website and later advertise those products to those same users to bring them back to the Store website and make a purchase. To set up Dynamic Remarketing, you first need to link your Google Ads and Analytics accounts, and enable Advertising features, as we've discussed previously. Retail businesses will also need to link their Google Ads accounts to their Google Merchant Center. The Merchant Center is a website that lets shoppers see your online and in-store inventory. Dynamic remarketing campaigns can use this product data to better customize ads. To enable Dynamic Remarketing, you will need to: Find your vertical attributes for Dynamic Remarketing, create your Custom Dimensions, and update your website tags, Create audiences for Dynamic Remarketing, Create attributes for Dynamic Remarketing, And create your Dynamic Remarketing campaign in Google Ads

order you apply filters

Each filter passes filtered data to the next filter in the sequence, so you'll want to be thoughtful about the order in which you apply your filters.You can adjust the order of your filters by going into "Admin" and selecting "Filters". Then select "Assign Filter Order."Note that you can use filters across multiple views, but be careful. If you edit the filter, those changes will be applied across all the different views to which you've applied that filter.Once you have set up your configuration, Google Analytics processes the data by checking each hit against your filters. If a hit matches the logic in a filter, then that filter will be applied.Remember to test out your filters in a "test" view before you apply them to the "master" view. Also, be sure to test out your filters on real-time reports to make sure they're working because they may take several hours to filter all of your data.

event tracking

Event tracking is a great way to know if users are engaging with your website and performing intended actions. The Google Merchandise Store, for instance, can track clicks on the global navigation bar to better understand how users navigate their website.To collect Event data from a website, you'll need to add JavaScript to the individual elements on the site you wish to track. When a user performs an action on an element with event tracking, the event tracking code will pass four parameters along with the event hit. These parameters are: "Category," "Action," "Label," and "Value." You can define these parameters in your JavaScript to organize the data in your event reports. "Category" lets you organize the events you track into groups. For your website, this might be "Videos" or "Social Shares." "Action" is the action the user took when they initiated the event. If you were tracking when users click a video play-button, you might have a category called "Videos" with an associated action of "Play." "Label" is an optional value used to further describe the element you're tracking like the name of a video. This can help you make your event reports more readable. "Value" is an optional numerical value like the amount of time it takes a video to load or how much a specific event action is worth. You can use Value to assign a specific dollar amount when a specific action occurs. Once the event tracking code has been added to the navigation element, every time a user interacts with that element it will pass the parameters that were assigned to Google Analytics, which will appear in the Events reports. If you click into the Category, you can see the associated Actions. This can help you view the various interaction states that were tracked for a Category in one place. If you click into the action, you can see the labels associated with that action. Another great use for events is tracking outbound link clicks that lead away from your site. For example, the Google Merchandise Store has a live chat button in their top navigation bar that opens a pop-up window when clicked. However, this pop-up window was implemented by a third-party vendor and goes to a different URL that the Google Analytics tracking code won't track by default. We can set up event tracking on this button with the category "Outbound links," an action of "Live Chat," and a label of "Home" (or wherever the live chat button was clicked from). That way, we can tell how many times the live chat button was clicked and from what page. We can then know which web pages were causing users to seek help and work to better optimize those pages.

types of filters

Filters can help refine your data and make it more readable in your reports. For example, you can use a filter to track activity in a specific website directory or track subdomains of your website in separate views. There are two kinds of filters: "predefined" and " custom" filters. Predefined filters have already been created for you in Google Analytics, you just have to select the filter you wish to use. These allow you to include or exclude data based on traffic from the ISP domain, IP addresses, subdirectories, or the hostname, and designate how the filter will match that information. Custom filters let you include or exclude hits from your data collection, format data to lowercase or uppercase, search and replace data collected in the hit. Custom filters accomplish this by matching a particular filter text-pattern that you identify. For example, let's say your business was making a push into mobile and only wanted to analyze mobile traffic in a specific view. You can set up a custom "include-only" filter on the view for Device Category and specify a value of "Mobile." The filter will look at the criteria specified and match it to any relevant hits that Google Analytics has collected for that view. If the filter can't match the criteria, the filter will not be applied to that data.Similarly, you may want to show only data for a specific campaign in a view. You can set up a custom filter to include only campaign data with the campaign name or type parameter you specified. Using view permissions, you can then share this campaign data with partners that you designate. If there was data you wanted to specifically exclude such as Paid Search (or CPC) traffic, you can set a custom "exclude" filter that will exclude all paid traffic in a particular view, as well. You can also use filters to normalize the data in your reports to make them easier to use. Google Analytics data isn't case sensitive, so pages in the All Pages report may show the same URL multiple times.You can quickly combine rows that differ only by case, by using a Lowercase or Uppercase filter. These filters will force the case to all lowercase or all uppercase, thus eliminating duplicate data.This will consolidate that page reporting and make the data in those reports a little neater.

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.

organizations

For example, if you're an agency managing marketing for multiple companies at once, you can set up different Organizations for each company with separate Google Analytics accounts under each Organization. When you create an account in Google Analytics, the account is assigned a unique ID. You can see this ID in the Analytics tracking code. This is how the tracking code knows to send hit data to the correct Analytics account. To better reflect how your business is organized, you can set up multiple properties under each Analytics account. For example, The Google Merchandise Store may want to view data from their website and data from their mobile app in separate properties to analyze each data set independently. We recommend tracking each company's website, mobile app, or other device in a separate property.

session sampling

For standard users, session sampling occurs at the property level, not the view level. This means that the sample set will be determined at the property-level before view-level filters are applied. So views that have filters applied may have fewer sessions in the sampled calculation. It's important to understand that when data is collected and processed, it can't be changed. For example, if you set a filter to exclude data on a view, that data will be permanently removed during processing from the reports in that view and cannot be recovered.After Google Analytics has finished processing, you can access and analyze your data using the reports. It's also possible to access your Analytics data using the Google Analytics Core Reporting API. This allows you to build your own reporting tools or extract your data directly into third-party reporting tools.

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.

cross domain tracking

If you have two related websites with different URLs or subdomains that you want to track in a single property, you can set up what's called "cross-domain tracking." Cross-domain tracking will recognize when a user navigates between related websites in the same session. This is also known as "site linking." To set up cross-domain tracking, you'll need to modify the Analytics tracking code on every page of every site you want to track. Google Tag Manager can make updating that code a lot easier

properties and views with multiple websites

If you use Analytics to manage multiple websites, there are a few things to keep in mind. Each Analytics account has a limited number of properties and each property has a limited number of views. For example, let's say you're the administrator of a site with multiple sub-directories based on different departments in your business. You can create different views for each department using filters and then grant access to each view for the members of those departments. To navigate to different views, in the Admin section use the View selector menu.

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.

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.

regular expressions filters

In addition to include, exclude, and lowercase filters, there are other advanced filters that allow you to remove, replace, and combine filter fields in more complex ways using what are called "regular expressions." Regular expressions (or "reg ex" for short) are characters that you can use to identify matching text in order to trigger an action. A basic regular expression on a filter can be something as simple as a word or a more complicated combination of characters. Let's say the Google Merchandise Store wants to set up a view with a filter to see all the keywords users searched for on their website for Android dolls. Because users might search for variations like "Android plush doll," or "Android stuffed doll," we can create a regular expression that identifies each of these variations. We can add an advanced filter with a regular expression that recognizes any Site Search queries that contain the terms "android" and "doll." if you have technical query parameters passed in the URL of your website, you might have identical pages with different addresses.Because the URL is different, this page will show up multiple times in your reports. But since they're the same page, it may make sense to filter out the query parameters, so that it doesn't appear multiple times in a report. You can include a regular expression that recognizes the main part of the URL before the query parameter, puts it in a variable, and overwrites the entire URL with that variable. This renders these page URLs identical in reporting.For businesses that collect data from multiple domains, it can be hard to distinguish page names in Google Analytics. In the "All Pages" report, "googlestoreamerica/index.axd" and "googlestoreeurope/index.axd" will both show up as "index.axd." You can use a regular expression to add the hostname in Analytics so that you can distinguish between multiple domains.

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.

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. Before we move on to user access permissions, there are a couple important things to note about views: 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.

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.

Steps in which GA processes data

Let's look at the first few steps in which Google Analytics 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. But 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.

How Does google analytics collect 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.

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.

roll up property

Note that roll-up properties don't include data that you import or link from another account -- like Google Ads. If you want to include linked data from your source properties into your roll-up properties, you'll need to re-link the roll-up property with the linked account. Also, when users are identified by the same Client ID across different source properties, session data for those users is usually merged; otherwise, that session data remains separate.

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.

measurement plan

Once you've defined your macro- and micro-conversions, you can start putting together a measurement plan. A measurement plan is a way for you to align your business objectives with your Google Analytics configuration settings. Your measurement plan should include an overall business objective, different strategies that support that objective, and tactics that will help you achieve your strategies. Each tactic will have key performance indicators (or KPIs) that help you measure your macro- or micro-conversions. Macro conversions usually measure the tactics that support your various strategies. Micro conversions are metrics that help you better understand the user behavior that leads to macro conversions. Once you've identified the macro- and micro-conversions, and created a measurement plan to measure your business, you can decide how to set up Google Analytics to collect these metrics. Keep in mind that this is just one example of a very abbreviated measurement plan. Yours will likely be richer and more detailed, depending on the complexity and ambition of your business. A measurement plan is a great way to document the data that is most important to your business. Use the interactive Google Merchandise Store measurement plan at the end of this lesson for an example.

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.

Remarketing

Remarketing is a powerful tool that lets you target ad content to users who have already visited your website. When a user visits your site and doesn't make a purchase, you can use remarketing to show them relevant ads on the Google Display Network, on mobile apps, or on Google Search. This can bring them back to your website and encourage them to make a purchase. To enable Remarketing in Google Analytics, you need to first enable Advertising Features in your Analytics property settings. Once you've set up remarketing, you can create specific "Audiences" that let you target groups of users based on common attributes. Audiences are made up of browser cookies from users that visited a site with Google Analytics implemented and the remarketing tracking code enabled. Audiences allow you to target ads to those users. For example you can create a Remarketing audience that includes users who visited a specific page of your website or clicked to play a video. Since website remarketing utilizes browser cookies, creating remarketing audiences in Analytics doesn't require any additional tagging on your website. But note that if a user clears their browser cookies, they will no longer be a part of the remarketing audience you created until they visit your site again.You can set how long users are eligible to be served remarketing ads using the membership duration. You can set Membership duration for your audience from 1 to 540 days. If you wish to design a more specific audience for your business, you can import a Segment to use as the basis for that audience. Click Import Segment and choose from the segments that are available in the current property or create an audience directly from the segment picker itself.

segmentation

Segmentation in Google Analytics is a way to view a subset of data in a report. You can create user segments or session segments. User segments can span multiple sessions with a maximum date range of 90 days. For example, you can build a user segment that shows data only for a specific age range, date range, gender, or a combination of these. Session segments are confined to user behavior within a single session. For example, you can create session segments for a Goal users completed during the session or the amount of revenue a user generated. A powerful part of segments is the ability to add multiple segments to a single report for comparison. You can compare segments of users who made a purchase with those that didn't, to better understand what influences people to buy. Or you might choose to build segments based on a specific traffic source like paid search and compare that to sessions that originated from email campaigns. This helps you see which types of users each source delivers. Default segments: If you select Tablet traffic, for instance, and click Apply, you'll be able to compare Tablet traffic with all of the traffic in any of your reports. These segments will be applied to every report you open until you remove the segment or exit Google Analytics.To remove a segment, click the down arrow and select "Remove."To compare new and returning users in reports, you can select the New Users and Returning Users segments. Notice that these segments will show up at the top next to the All Users segment. If we want a cleaner report for comparison, we can turn off the All Users segment and click Apply. This now compares only new and returning users. For example, under Demographics you can choose age "25 to 34" and language contains "es" for Spanish, which will filter the data for users between the ages of 25 and 34 who have their browsers set to Spanish. You can also create segments based on sequences of user interactions. For example, you can segment users that viewed a specific page and then watched a video. Sequences can be a mixture of pageviews or events. Note that segments are applied after sampling. So if the data being shown in your reports is a sample, the data shown in your segments will also be a sample. As you encounter more complex questions about your customers' behavior, you can create segments to isolate subsets of data and find opportunities to improve your website's performance.

ga content 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.

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

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.

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.

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.

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.

4 types of goals in GA

There are four types of Goals in Google Analytics: Destination (or Pageview) Goals are based on when a user views a particular page on your website. Event Goals are when a particular action defined as an event is triggered. Duration Goals are based on sessions that last over a set amount of time. "Pages or Screens per Session" Goals are based on whether a user has viewed a set amount of pages in a session.

macro vs micro conversions

There are key actions that users take on websites that fulfill your business objectives like making a purchase. We call these "macro" conversions, since they represent the broader goals of your business. But there can also be smaller goals that bring users closer to your main objectives such as signing up for an email coupon or a new product notification. We call these "micro" conversions, since they nudge users closer to your macro-conversions.Different businesses will naturally have different macro- and micro-conversions: For an e-commerce site, the macro-conversion might be to purchase a product with a micro-conversion of subscribing to a newsletter. For a lead generation site, the macro-conversion might be filling out a contact form with a micro-conversion of following the site on social media. For a content publisher, the macro-conversion might be engaging with a particular amount of content with a micro-conversion of clicking into an article. For an online information and support site, the macro-conversion might be completing a guided support flow to successfully solve an issue with a micro-conversion of rating a support article.

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.

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.

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.

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.

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.

total events

Total Events are calculated as the total number of interactions with the tracked element, while Unique Events are how many users have triggered that event. So if a user clicks on the Google Merchandise Store's navigation for "Bags" five times in a single session, the total number of link clicks for that event will be "five," but the number of Unique Events will be counted as "one." Events reports are found under Behavior. When you open the "Top Events" report, events are organized by category.

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.

How Analytics understands things

We've discussed some of the information passed in hits such as Language and Page Title. But 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.

Scopes

When Analytics creates dimensions and metrics during processing, it has to determine the scope of those dimensions and metrics in order to know how broadly applicable they are to your data. Some dimensions might organize data about a single hit, while other dimensions might apply to data across an entire session or individual user. Dimensions and metrics can have one of three scopes: hit-level, session-level, user-level. During processing, Analytics will determine which scope gets applied to each dimension and metric. You can only pair metrics with dimensions if they are both in the same scope. For example, pairing a "hit-level" dimension like "Page Title" with a "session-level" metric like "total number of Sessions," wouldn't make sense, since "Page Title" changes with each hit, but the "sessions" count changes with the completion of each session. While Google Analytics pairs dimensions and metrics of the same scope together for you in standard reports, you will have to manually set the scope for any Custom Dimensions or Custom Metrics you create.

aggregate data tables

When Google Analytics has determined the dimensions and associated metrics, it links this raw, unfiltered data with the unique property ID for your account. Each reporting view you've created adds the data (with filters and configuration settings applied) to "aggregate" data tables, which are processed daily. These aggregate tables are used to quickly display the standard reports in Analytics. But you also have the ability to generate more customized reports in Analytics using features like secondary dimensions or by creating a Custom Report. When you do this, Analytics checks to see if there is an aggregate table with the appropriate data. If the table doesn't already exist, Analytics goes back to the raw session data to process and create the report from scratch. In some instances, there is so much data to be joined that Analytics will show a sample of the data in the returned report, rather than calculating all of the data that was collected.

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 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 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.

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.

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.

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.

custom dimensions/metrics

You learned about dimensions and metrics in Google Analytics for Beginners. But you also can create your own dimensions and metrics in Analytics called "Custom Dimensions" and "Custom Metrics." Custom Dimensions help you define a group of metric data that's specific to your business and then apply that as a dimension across your reports. Custom Dimensions can be used as a secondary dimension in standard reports, a primary dimension in a Custom Report, or as a segment. We'll discuss Custom Reports and segments later in the course. "Custom Metrics" can be collected for any standard dimension or Custom Dimension that can't be measured by any predefined metric in Google Analytics.

channel vs content grouping

You may want to organize the data you collect in different ways than the standard Google Analytics reports. Channel Groupings let you organize your data into customized channels, while Content Grouping lets you aggregate metrics within reports based on the organization of your website.