Advanced Google Analytics Flashcards
How does G.A. collect website data?
Google Analytics collects data from websites using a snippet of JavaScript tracking code embedded on each page of the site.
This tracking code is responsible for monitoring user interactions on the website, such as page views, clicks, and other events.
How are users tracked?
When a user visits a website with the tracking code, Google Analytics places a cookie in the user’s browser.
This cookie is associated with the domain of the website and any related subdomains, allowing Analytics to track user activity within that domain.
How does G.A. count the users across the website and its subdomains?
The tracking code defines the website’s domain as a “site” in the reports of Google Analytics.
By default, Analytics tracks traffic on a single website URL domain or subdomain separately.
If the same tracking code is installed on pages with different domains, Analytics counts users and sessions separately.
What happens when multiple domains have the same tracking ID (Web Property ID)?
Analytics will count users and traffic sources separately for each one.
EX: If a user navigates from one subdomain to another, G.A. will consider this as referral traffic.
If a user visits both the main domain and the subdomain, they will be counted as separate users for each domain.
What is Web Property ID?
- The Web Property ID (also known as Tracking ID) is a unique identifier assigned to each property in Google Analytics.
- It is a string of characters that is used to distinguish one website or mobile app from another within a Google Analytics account.
- When you create a new property in your Google Analytics account, you are given a Web Property ID that you need to include in the tracking code installed on your website or app.
How to track users across different domains?
Cross-domain tracking
What is a domain?
Web address used to identify a specific location on the internet.
What are the 2 parts of a domain?
1) Domain name- example.com (domain name= example)
2) Top-level domain (TLD)- .com, .org, .UK etc.
What is a hit?
A “hit” is a URL string containing parameters of useful information about the user’s activity on the website.
When are hits generated?
With each user interaction, the tracking code sends a “hit” to Google Analytics.
What information is passed in hits?
Hits contain data such as the user’s browser language, viewed page name, screen resolution, and Analytics ID.
Other information, like a randomly-generated user identifier, distinguishes between new and returning users.
What are the most common hits?
1) Pageview hit- occur when a user loads a webpage with the tracking code.
2) Event hit- tracks user interaction with particular elements on the website.
3) Transaction hit/ E-commerce hit- records data about e-commerce purchases, transaction IDs and Stock Keeping Units (SKU)
Event hits pass 4 parameters of data in the URL:
- Action: if a user clicks on a “Play” button for a video, the action might be labeled as “Play Video.”
- Category: groups similar types of actions or interactions together for organizational purposes.
all video-related interactions might be grouped under the category “Videos.” - Label: additional context or description for the action being tracked.
It adds specificity to the action by providing details such as the name of the video, the URL of the clicked link, or the title of the downloaded file. - Value: quantifies the significance or impact of the event, providing a measure of its value or importance.
This parameter is optional and can be used to track metrics such as revenue, time spent, or the number of items purchased.
Enhanced Ecommerce
Enhanced Ecommerce allows passing additional ecommerce data to Google Analytics, such as:
- product category
- products added/ removed from shopping cart
- product views
Other hits
Social hits: When users engage with social sharing buttons. ex: like, comment, share
Page timing hits: time taken for certain user actions/ processes. ex: loading time etc
How does G.A. use hits?
Google Analytics combines hit data with additional sources like IP addresses, server logs, and ad-serving data.
This widened data includes user location, browser details, demographics, and referral sources.
What are dimensions?
Ways to categorise or contextualise metric data.
How does G.A. process data (3 steps)?
1) Determines New vs. returning users.
2) Categorises hits into sessions
3) Combines data from the tracking code with other data sources.
How does G.A. distinguish between new and returning users?
1) The user arrives on site with the tracking code
2) G.A. creates a unique, random ID that gets associated with the user’s browser cookie.
3) each unique code= separate user
New ID detected= new visitor
Existing ID detected= returning vistor
What are the limitations to tracking users using browser cookies?
1) Loss of user information if the user clears or blocks cookies on their browser.
2) G.A. doesn’t recognise users who visit the site from different devices by default.
each device= unique user
To track users across devices
Enable User ID feature
What are sessions?
periods of user engagement with a website
When does a session begin?
A session begins when a user accesses a page with the tracking code and generates a “pageview” hit.
What are the 2 methods by which a session ends?
1) Time-based expiration:
* After 30 mins of inactivity
* at midnight
2) Campaign change:
* if a user arrives via one campaign, leaves, and then returns via a different campaign.
What is referral traffic?
traffic that comes to your website from sources other than search engines. EX: hyperlinks from sites, blogs, social media etc
What is a campaign?
A specific set of marketing activities or initiatives that are designed to drive traffic to the website and achieve specific goals such as increasing sales, generating leads or boosting brand awareness.
What is campaign tagging?
A method used in digital marketing to track the effectiveness of marketing campaigns and traffic sources. It involves adding specific parameters (AKA UTM) to the URLs of your marketing materials, such as ads, emails, or social media posts, before they are shared or distributed.
What are UTM parameters?
UTM parameters (Urchin Tracking Module), are added to the end of a URL and provide detailed information about the source, medium, campaign name, term and content.
UTM tags:
utm_source- Identifies the specific source of the traffic, such as Google, Facebook, newsletter, or a specific website.
utm_medium- Describes the type of traffic, such as email, CPC (cost-per-click), social, or referral.
utm_campaign- Specifies the name of the campaign or promotion associated with the link.
utm_term (optional)- Optional parameter used to identify keywords associated with paid search campaigns.
utm_content (optional)- Optional parameter used to differentiate between different versions of the same ad or link.
How does G.A. combine data from the tracking code with other sources of data (2 methods)?
1) Measurement Protocol
2) Account linking
What is the Measurement Protocol?
The Measurement Protocol is a feature of Google Analytics that allows you to send data from any web-connected device or system to your Google Analytics account. It provides a way to collect and send data to Google Analytics outside of traditional web tracking, such as from point-of-sale systems, mobile applications, kiosks, or any internet-enabled device.
This requires you to construct and send hits in a URL string manually.
Account linking
Account linking in Google Analytics refers to the process of connecting your Google Analytics account with other Google products or services to enhance data integration and analysis.
What are campaign updates?
changes or additions to campaign-related data that occur when users interact with your website through various marketing activities.
What are the sources of campaign updates?
- Campaign tagged URLs
> Clicking on tagged URLs updates campaign data with details such as campaign, medium, source etc. - Search engine traffic
> When users click on search engine results (organic and paid). - Referral traffic
> clicking on links from other websites. - Google Ads autotagging
> each click on a Google ads ad generates a unique identifier (GCLID) that updates the campaign data, attributing the visit to the corresponding ad campaign. - Other advertising platforms
> Clicks on ads from other advertising platforms updates campaign data.
What is GCLID (Google Click Identifier)?
It is a unique parameter appended to the URL of a landing page when a user clicks on a Google Ads (formerly known as Google AdWords) advertisement. The gclid parameter serves as a tracking mechanism that helps Google Analytics identify and attribute website visits to specific ad clicks.
What is direct traffic?
visits to the website where the user directly enters the website URL into the browser’s address bar use a bookmark to access the site or clicks an untracked link in the email or document.
Can direct traffic update campaign info?
Direct traffic does not override existing, known campaign sources like search engines, referrals, or campaign-tagged information.
EX: if a user arrives at a website through a tracked source and later returns directly, the original campaign is maintained.
What is session timeout?
Duration of inactivity after which a session is considered ended.
What are some considerations to be made when adjusting session timeout?
1) Amount and complexity of content: Evaluate the volume and complexity of content on your website. Websites with extensive content or complex features may warrant longer session timeouts to accommodate user exploration.
2) Alignment with website: Aligning the session timeout with the automatic logout timeframe ensures consistency.
3) Cross-device sessions: consider how users interact with your website across multiple devices.
What are the limitations to session timeout?
session timeout cannot be set to less than 1 minute or more than 4 hours.
What is the automatic logout timeframe?
Automatic logout timeframe applies to user sessions across various systems and applications and focuses on security by automatically logging users out after a period of inactivity.
What is a campaign timeout?
Campaign timeout refers to the duration for which campaign-related data is retained in G.A. It determines how long G.A. continues to attribute website visits and conversions to specific marketing campaigns.
What happens when the campaign timeout period expires?
Once the campaign timeout period expires, the attribution of user interactions to that campaign ends, and subsequent interactions are not credited to the original campaign.
> users are then attributed to direct traffic not the campaign.
Benefit:
businesses can evaluate the impact of their marketing efforts more effectively. They can assess the performance of different campaigns, channels, and strategies and make data-driven decisions to optimize their marketing budget and resources.
What is the default timeout for campaigns in G.A.?
6 months
What are some considerations to be made when adjusting campaign timeout?
1) Campaign duration: Set the campaign timeout to match the duration of your marketing campaigns.
EX: if the campaign is for the weekends or a month-long, align the campaign timeout accordingly.
2) Relevance and analysis: the campaign timeout period affects how long you can analyse the performance of your marketing campaigns. If the timeout is too short, you might miss out on long-term trends and insights; too long and you end up with cluttered and irrelevant data.
When should marketers analyse the campaign’s related information?
Within the active period of the campaign.
What are the limitations to campaign timeout?
Cannot exceed 2 years.
How to adjust timeout settings?
Admin > select account and property you want to edit
> property column
> tracking info> session setting> timeout handling
What are conversions aka. Key events?
A conversion occurs when a user completes a predefined action or goal on a website that aligns with business objectives.
What are the 2 types of conversions?
- Macro conversions
- Micro conversions
What are macro conversions?
high-value actions that signal significant user engagement and lead to tangible business outcomes like revenue.
EX: Purchase completion, form submission, subscription sign-up, event registration
What are micro conversions?
smaller actions that indicate progress or engagement towards a macro conversion. May not result in revenue.
Valuable indicator of user intent and interest.
EX: adding items to cart, downloading a resource, viewing multiple pages, social media interaction
What is an e-commerce website? Give examples of conversions related to this.
An e-commerce website facilitates online transactions, where visitors purchase products or services directly from the website.
EX: Purchase, add to cart, and check out initiation.
What is a lead generation website? Give examples of conversions related to this.
A lead generation website aims to capture information from visitors interested in a product or service, typically through contact forms, subscription forms, or gated content.
EX: Form submission, email sign-up and download of resources.
What is a content website? Give examples of conversions related to this.
Content websites focus on providing valuable information, entertainment, or resources to users, often monetized through advertising, subscriptions, or affiliate marketing.
EX: Subscription, engagement metrics, social sharing.
How does G.A. count conversions?
A conversion is counted once per session per configured goal
The statement indicates that when a user completes a configured goal during their session, it is counted as a single conversion event. Even if the user performs the same action multiple times within the same session, it will only be counted as one conversion for that particular goal.
What are data configuration rules?
Data configuration rules determine how your data will be processed.
List the 6 configurations:
- data filters
- goals
- data grouping
- custom dimensions
- custom metrics
- imported data
What are filters?
Filters are settings applied to a view in Google Analytics to control or manipulate the data that appears in reports.
What are goals?
Goals are specific actions or achievements on your website or app that contribute to the success of your business. These actions, called conversions, represent completed activities that fulfill your objectives.
What are the types of goals in G.A.?
- Destination/ pageview: when a user lands on a specific page of the website.
- Event: when a user performs a particular action.
- Duration: Sessions that lasts a specific amount of time or longer
- Pages/ screens per session: A user views a specific number of pages or screens
What is goal value?
How much each goal completion is worth to your business.
How are hits matched with goals in G.A.?
In the context of Google Analytics, a “hit” refers to any interaction that is tracked on your website, such as a pageview, event, or transaction. Each time a user interacts with your site, whether it’s loading a page, clicking a link, or submitting a form, it generates a hit.
Google Analytics continuously monitors the incoming hits on your website. When a hit occurs that matches the criteria you’ve defined for a particular goal, Analytics recognizes it as a goal completion. For example, if a user lands on the thank-you page after making a purchase (as defined in your goal criteria), Analytics registers that hit as a completion of the corresponding goal.
How are goal metrics calculated?
Once a hit is matched with a goal, Google Analytics calculates various metrics related to that goal, such as the total number of completions, the value of those completions- goal value (if applicable), and the conversion rate (the percentage of sessions that resulted in goal completions).
How does Google Analytics include goal-related data in reports?
After calculating the goal metrics, Google Analytics includes the data in various reports accessible within the platform, such as Goal Overview, Goal URLs, or Funnel Visualization.
What is the conversion rate?
It measures the percentage of visitors to a website who complete a desired action out of the total number of visitors.
conversion rate= (no. of conversions/ no. of sessions)*100
What is data grouping?
Data grouping in Google Analytics refers to the process of organizing and categorizing data to make it more manageable and meaningful for analysis.
What are the types of data grouping?
- Content grouping
- Channel grouping
What is content grouping?
Content Grouping is a feature in Google Analytics that allows you to organize your website or app content into logical groups. This structure reflects how you think about your site or app and makes it easier to analyze and compare aggregated metrics for different sections of your content.
What is the purpose of content grouping?
- Logical Structure: It helps you organize your content into meaningful groups that reflect the structure and organization of your website or app.
- Comparison: You can compare aggregated metrics (such as pageviews or sales) for entire groups of content, rather than looking at individual pages or URLs.
- Drill-down Capability: While you can see aggregated statistics for content groups, you can also drill down to view data for individual URLs, page titles, or screen names within each group.
How to create content groups?
Content Groupings are created at the view level in Google Analytics, under Admin > <view> > Content Grouping.</view>
What is the general structure of creating content groups?
1) Define groups. E.X: Men, Women and Children
2) Create sub-groups within the main group.
3) Assign content to groups using one of the 3 methods:
* Group by tracking code.
* Group using extraction
* Group using rule definitions
What is Group by Tracking Code?
Group by Tracking Code is a method used in Google Analytics to organize website or app content into logical groups by modifying the tracking code on each web page. This method allows you to specify which Content Group each piece of content belongs to, providing a structured way to analyze and compare aggregated metrics for different sections of your digital property.
How do you modify the tracking code?
Once you’ve identified your Content Groups, you modify the tracking code on each web page to include additional information that identifies the content’s group membership. This modification is typically done within the Google Analytics tracking snippet that is included on every page of your site. Within the tracking code, you specify a content index number for each piece of content. This number represents the position of the content within its Content Group.
What is Group using Extraction?
Group Using Extraction is a method within Google Analytics Content Grouping that allows you to automatically assign content to groups based on patterns found in URLs, page titles, or screen names.
How does Group using extraction work?
- Pattern Recognition: With Group Using Extraction, you define regular expressions (regex) patterns that match specific characteristics or patterns in your content’s URLs, page titles, or screen names.
- Automatic Assignment: Google Analytics uses these regular expressions to automatically assign content to the appropriate groups based on the patterns identified. If a piece of content matches the defined pattern, it is grouped accordingly without manual intervention.
What is Group using rule definitions?
“Group Using Rule Definitions” is a method within Google Analytics Content Grouping that allows you to define rules to automatically assign content to groups based on specific criteria or conditions.
How does Group using rule definitions work?
1) Creation of Rules:
You create rules in the rules editor of Google Analytics.
Each rule specifies conditions that content must meet to be assigned to a particular group.
2) Conditions:
Conditions can be based on various attributes of the content, such as:
* URL: The web address of the page.
* Page Title: The title of the page as seen in the browser tab.
* Screen Name: For mobile apps, the name of the screen viewed by the user.
* Other attributes: Custom dimensions, metrics, or events.
3) Rule Criteria:
You define criteria for each rule, such as:
* Contains: Content must contain a specific word or phrase.
* Equals: Content must exactly match a specified value.
* Regular Expression (Regex): Content must match a pattern defined by a regex.
* Begins with / Ends with: Content must start or end with a particular string.
4) Assignment of Content:
When content matches the criteria defined in a rule, it is automatically assigned to the corresponding group.
Content can be assigned to multiple groups if it meets the criteria of multiple rules.
Which data does content grouping applies to once set?
Content Grouping is not retroactive, meaning that groups you create are only valid from the creation date forward.
When and where is the reporting for Content grouping available after being set or configured?
After about 24 hours, you can see Content Grouping statistics in your reports. They are available in Content reports that offer Content Grouping as a primary dimension, and you can also use Content Group as a dimension in custom reports.
What is channel grouping?
Channel grouping categorizes traffic sources into predefined or custom groups based on how users arrive at your website. This allows you to analyze the effectiveness of different marketing channels and campaigns in driving traffic and conversions.
What are custom dimensions?
It allows you to create a set of data that is unique to your business and then use it as a category in your reports.
How can you use custom dimensions in reports?
- as a secondary dimension in standard reports
- as a primary dimension in custom reports
- use custom categories to create segments.
What are custom metrics?
Additional data points or measurements that you can define and track in G.A. beyond the standard metrics provided.
What is data import in G.A.?
It is a feature in G.A. that allows you to upload and merge offline data with data collected from G.A.
What data can you upload to G.A.?
- Hit data: info about user interaction
- Extended data stored in a custom dimension or metric
- Summary data- aggregating metrics from multiple sources to provide high-level overview or analysis.
When should data configuration rules be set?
before data processing.
Once data has been processed you can’t apply configuration settings.
What are views?
It is a subset of G.A. property that can have it’s own unique configuration settings.
> You can configure each view to show a different subset of data for the property.
What is an ISP?
An Internet Service Provider (ISP) is a company that provides users with access to the internet. It could be your cable company, telephone company, or a specialized internet provider.
What is internal traffic?
Internal traffic refers to visits to your website from within your organization’s network or from devices connected to the same network.
What is external traffic?
External traffic refers to visits to your website from sources outside of your organization’s network.
What is an IP address?
An IP (Internet Protocol) address is a unique numerical label assigned to each device connected to a computer network. It serves as an identifier for communication between devices on the internet. Think of it like a phone number for devices on the internet.
What are hits?
Interaction between a user’s web browser and a website’s server. Types include event, pageview and transaction
What are log files?
Log files serve as a comprehensive record of all interactions between users (browsers or devices) and the web server.
Hits are essentially the individual entries or records within log files.
What information is captured in the log files?
1) Date and Time: The timestamp indicating when the request was made.
2) IP Address: The IP address of the client (user) making the request.
3) Request Method: The HTTP method used in the request (e.g., GET, POST).
4) Requested URL: The URL of the requested resource on the server.
5) HTTP Status Code: The status code returned by the server in response to the request (e.g., 200 for success, 404 for not found).
6) User-Agent: Information about the client’s web browser or device.
7) Referrer: The URL of the referring page, if any.
8) Bytes Transferred: The number of bytes transferred in the request.
9) Server Response Time: The time taken by the server to process the request and generate a response.
Type of predefined filters:
1) Exclude/include only traffic from the ISP domain: Exclude or include only traffic from a specific domain, such as an Internet Service Provider (ISP) or a company network.
Note: Specify the domain name without the host server label (e.g., use “example.com” instead of “www.example.com”).
> You want to exclude this internal traffic to focus on genuine visitors.
Conversely, if you’re running a marketing campaign targeting users of a specific ISP, you might want to include only traffic from that ISP to gauge the effectiveness of your campaign.
2) Exclude/Include only traffic from the IP addresses: Google Analytics will exclude traffic originating from the specified IP address range.
> Common reasons for filtering traffic by IP addresses include excluding internal traffic from company networks, blocking spam or malicious bots, and targeting analysis on specific geographic regions or service providers.
3) Exclude/Include only traffic to the subdirectories: You can choose to exclude or include only traffic to particular subdirectories, such as “/motorcycles” or “/help/content/faq”.
>
If you want to analyze traffic only to certain parts of your website, you can set up this filter to isolate that traffic.
4) Exclude/Include only traffic to the hostname: This filter allows you to exclude or include only traffic to a specific hostname. It helps you focus your analysis on traffic coming from or going to particular subdomains or hostnames within your website.
>
Imagine you have a website with multiple subdomains, such as "sales.example.com" and "support.example.com." You want to analyze traffic to each subdomain separately to understand how users interact with different sections of your website.
Types of custom filters:
1) Exclude: Its primary function is to remove or exclude certain data points from your analytics reports based on specified criteria. (allows for more customised exclusion of IP addresses)
>
Any data or hits originating from IP addresses within the specified range will be ignored or excluded from your analytics reports. This ensures that only external user traffic, representing actual customers visiting your website, is included in your analysis.
2) Include: Include filters are a type of filter used in web analytics tools like Google Analytics to focus on specific subsets of data.
They allow you to include only the log file lines (hits) that match certain criteria in your analytics reports.
3) Lowercase / Uppercase: The purpose of this filter is to convert the contents of a specified field into either all uppercase or all lowercase characters.
It helps standardize the format of the data within the selected field for consistency in reporting and analysis.
4) Search & Replace: The purpose of the Search & Replace filter is to modify or clean up data within a specific field by searching for a particular pattern and replacing it with another pattern.
5) Advanced: The purpose of the Advanced filter is to manipulate existing fields or combine them to create a new field with customized information.
Limitations of filters:
1) Destructive Nature:
Filters permanently modify incoming hits.
Always maintain an unfiltered view for full data access.
2) Time Delay:
Filters take up to 24 hours to apply.
Changes won’t reflect immediately.
3) Field Requirement:
Fields in filters must exist and not be null in hits.
Missing fields ignore filter conditions.
4) Account-Level Impact:
When you edit a filter at the view level, it also affects the filter at the account level. Any changes made to a filter in one view will automatically apply to all other views that use the same filter.
If you need to customize a filter for a specific view without affecting others, you’ll need to create a new filter specifically for that view.
5) Post-Processing Application:
Filters applied after data processing.
Can’t modify dimension scope.
6) Exclusion from Data Import:
Filters not applied to product-scoped dimensions from data import.
> Imported data remains unaffected by filters.
if you’ve imported data into specific dimensions (such as product-related dimensions) using Data Import, any filters you set up won’t modify or impact that imported data.
Field requirement (explained)
When you create a filter in Google Analytics to modify your data, you specify certain conditions that need to be met for the filter to apply. For example, you might create a filter to include only hits from a specific domain or to exclude hits from a particular IP address.
Now, for that filter to actually work, it needs to look at specific pieces of information in each hit, like the domain name or the IP address. These pieces of information are called fields. So, if you create a filter that looks at the domain name of each hit, but some hits don’t have that information, the filter won’t do anything to those hits. It’s like trying to use a filter to catch fish, but some of the fish don’t have the right markings to be caught by the filter.
In technical terms, if the fields specified in your filter don’t exist in a hit or are empty (null), the filter won’t be applied to that hit. It’s like trying to apply a rule to something that doesn’t have the necessary parts for the rule to work.
What are Smart goals?
An alternative tracking method designed for Google Ads advertisers who lack enough conversions for automated bidding.
Automatically evaluates visits and assigns scores to identify the best visits as “Smart Goals.”
What is a funnel?
It can only be set for destination goals.
A funnel is a series of steps or pages that users are expected to go through before reaching the final destination, which represents the completion of the goal. Each step in the funnel represents a page or screen that users should ideally visit in sequence.
What are Goal IDs?
- Every goal you create in Google Analytics is assigned a unique numeric identifier known as the Goal ID.
- Goal IDs range from 1 to 20.
- These IDs are used internally within Google Analytics to differentiate between different goals.
- They help identify and track specific conversion actions on your website or app.
What are Goal sets?
- Goal sets allow you to group related goals together for better organization and analysis.
- Each goal set can contain up to 5 individual goals.
- Grouping goals into sets makes it easier to categorize and manage your goals within Google Analytics.
Which reports can you analyse goal completions and conversion rates?
1) Conversion > goals report
2) conversions > multi channel funnels
3) conversions > attribution
4) Acquisition reports
Limits of goals:
1) Limited to 20 goals per reporting view. To track more goals, create additional views or edit existing goals that are unnecessary.
Apply only to data collected after the goal is set up. Goals are not applied to historical data.
Cannot be deleted but can be stopped from recording data.
Goal IDs and sets cannot be changed after you create them.
3 best practices for goals:
1) Use intuitive names for goals.
2) Assign goal values to help monetize and evaluate conversions.
3) Keep track of changes to avoid confusion in reports.
What are Channel groupings?
Channel Groupings in Google Analytics offer a way to organize and categorize your traffic data based on specific criteria, allowing for more customized analysis and reporting.
What is the default channel grouping?
Default Channel Groupings are predefined sets of traffic sources that categorize user interactions into broad channels like organic search, paid search, direct, referral, etc.
What are Custom Channel Groupings?
Custom Channel Groupings allow users to define their own sets of traffic sources based on specific criteria or rules that they set.
What are ways for the user to customise channel groupings?
1) Create a Custom Channel Grouping (User Level):
Allows you to define your own channels based on criteria that suit your analysis needs.
Custom Channel Groupings are visible only to the user who creates them.
2) Create a New Channel Grouping (View Level):
Similar to Custom Channel Grouping but visible to all users of a specific view.
Offers flexibility in defining channels based on the requirements of that view.
3) Edit the Default Channel Grouping (View Level):
Provides the ability to modify the predefined channels at the view level.
Changes affect how incoming traffic is labeled for new sessions in that view.
How to create a custom channel grouping?
sign in to G.A. > Admin > select desired view > personal tools and assets- custom channel grouping > +new channel grouping > name grouping > +define a new channel > enter name and define rules > save
Who is custom channel grouping visible to? Max amount?
Only visible to the creator.
Max: 100 per user
Creating a new channel grouping for a view:
Visible to all users of that view.
Steps: Sign in, Admin, view, Channel Settings, +New Channel Grouping, define channels, order them, save.
Limit: Max 50 per view.
How can you make a custom channel grouping visible to all users?
Promoting a Custom Channel Grouping to the view level in Google Analytics is a process that allows you to make a copy of a Channel Grouping that you’ve created at the user level and apply it to a specific view within your Analytics account.
Promoting the Custom Channel Grouping to the view level extends its visibility and usability to all users with access to that particular view.
Who can promote a custom channel grouping to the view level? Max limit of channel groupings?
Editors.
max. 50 channel groupings per view
What happens to the custom channel grouping at the user level?
Despite promoting the Channel Grouping to the view level, you still maintain control over the original Custom Channel Grouping created at the user level. This means that you can continue to make changes to the original Channel Grouping without affecting the promoted version in the view.
Copy, share or delete custom channel grouping.
Sign in to G.A. > Admin > view > custom channel groupings > select copy, share or delete from the actions drop-down menu.
Why would you want to edit the Default Channel Grouping?
Editing allows you to customize how traffic is categorized, defining new channels or modifying existing ones to better suit your analysis needs.
What are the implications of editing the Default Channel Grouping?
Changes made are permanent and affect how Analytics classifies traffic. They’re visible to all users but don’t apply retroactively to historical data.
What happens if you want to revert to the default channel definitions?
You can click “Reset channels,” but note that it won’t change historical data, only new sessions going forward.
What is MCF?
MCF stands for Multi-Channel Funnels. It’s a feature in Google Analytics that helps you understand the full customer journey by tracking interactions across multiple channels and touchpoints leading to conversions.
MCF (explained simply)
In Google Analytics, Multi-Channel Funnels (MCF) help you understand the various touchpoints or interactions users have before they convert on your website. This includes interactions with different marketing channels like organic search, paid search, social media, etc.
What are Channel Groupings in Multi-Channel Funnels (MCF)?
Channel Groupings in MCF help analyze the paths users take before converting, categorizing touchpoints into channels like organic search, paid search, direct, etc.
These groupings help you analyze the contribution of different channels to conversions.
What’s the default Channel Grouping used in this report?
The default Channel Grouping used in the Multi-Channel Funnels report is called the Default MCF Channel Grouping. This grouping categorizes user touchpoints into different channels such as organic search, paid search, direct, referral, and others to help you understand the customer journey leading to conversions.
Are there any limits to creating Channel Groupings?
Yes, each user can make up to 100 Custom Channel Groupings, and each view can hold a maximum of 50 Channel Groupings excluding the default.
How do Channel Groupings interact with view filters?
They use filtered dimension values, meaning if you change how data appears with a view filter, it affects how sessions are categorized into channels.
What is a channel definition?
A channel definition refers to the criteria used to categorize incoming traffic into different channels within Google Analytics. These criteria typically include various dimensions such as source, medium, campaign, and other user interactions. Each channel definition specifies rules for classifying sessions based on specific attributes or behaviors of the incoming traffic.
How do Channel Groupings interact with view filters?
They use filtered dimension values, meaning if you change how data appears with a view filter, it affects how sessions are categorized into channels.
EX: If you change a campaign name from “Campaign A” to “Campaign B” with a filter and include “Campaign B” in a channel definition, sessions from clicks on “Campaign A” will now be grouped under “Campaign B.”
What is cost data in MCF?
Cost data refers to the expenses associated with each marketing channel. For example, how much you spend on advertising for paid search campaigns or social media ads.
Why Does Cost Data Matter?
Cost data tells you how much money you’ve spent on different marketing channels, like advertising on Google Ads or promoting posts on social media. It helps you understand the return on investment (ROI) for each channel.
Do all dimensions reveal cost data?
Some dimensions in Google Analytics don’t include information about how much money you’ve spent.
EX: Let’s say you have a dimension called “Social Media Source” that shows which social media platform users are coming from (e.g., Facebook, Twitter, Instagram). This dimension doesn’t include cost data, so you can’t see how much money you’ve spent on ads for each platform.
Impact of non cost data dimensions on Channel groupings:
When you create Channel Groupings in Google Analytics, you might use these dimensions to classify your traffic sources. if you’re using dimensions in your Channel Groupings that don’t track costs, you won’t be able to see how effective your spending is on those specific channels. It’s like trying to budget for your marketing efforts without knowing how much you’re actually spending on each advertising platform.
Scenario: If you create a Channel Grouping called “Social Media Channels” and include all traffic from social media platforms, Google Analytics won’t be able to tell you how much money you’ve spent on ads for each platform within that grouping.
What are Campaign Manager 360, Display & Video 360, and Search Ads 360?
These are advertising platforms offered by Google that allow advertisers to manage and optimize their campaigns across various channels like display, video, and search.
What are dimensions in the context of these platforms (Campaign Manager 360, Display & Video 360, and Search Ads 360)?
Dimensions are attributes or parameters used to segment and analyze data. In the context of advertising platforms, dimensions can include things like campaign names, ad groups, keywords, etc.
What’s the limitation regarding dimensions from these advertising platforms in Channel Groupings?
The dimensions available in Campaign Manager 360, Display & Video 360, and Search Ads 360 are not automatically included in the Default Channel Groupings provided by Google Analytics.
How can these dimensions be used in Channel Groupings then?
Users have the flexibility to create Custom Channel Groupings where they can include dimensions from these advertising platforms. This means they can define their own channels based on the specific attributes or parameters provided by these platforms.
This allows for more granular analysis and reporting on the effectiveness of their advertising campaigns across different channels.
What are Channels Report and Google Ads Reports?
- The Channels Report in Google Analytics shows how traffic to your website is categorized into different channels such as organic search, paid search, direct, referral, etc.
- Google Ads Reports provide insights into the performance of your Google Ads campaigns, including metrics like clicks, impressions, conversions, and more.
What are dimension values in Google Ads Reports?
Dimension values in Google Ads Reports are specific attributes or characteristics of your ad campaigns, such as campaign names, ad group names, keywords, and more. These values provide context and details about your campaigns.
What happens if dimension values change over time?
Once traffic from Google Ads campaigns has been categorized into specific Channel Groupings based on certain dimension values (such as campaign names), those categorizations remain unchanged historically, even if the dimension values associated with Google Ads campaigns change in the future.
E.X: Initial Google Ads Campaign Setup:
You launch a Google Ads campaign named “Outdoor Adventure Sale” targeting keywords related to hiking and camping gear.
Over the course of a month, this campaign drives a significant amount of traffic to your website, resulting in numerous conversions.
Dimension Value Change:
After a month, you decide to rename your Google Ads campaign from "Outdoor Adventure Sale" to "Spring Camping Gear Sale" to better reflect the season.
You make this change directly in your Google Ads account.
Analysis in Channels Report:
In your Google Analytics Channels Report, you notice that traffic from the "Outdoor Adventure Sale" campaign is still being categorized under the same Channel Grouping, despite the campaign name change.
Conversions and other metrics attributed to this channel continue to accumulate under the original name, "Outdoor Adventure Sale."
Google Ads Reports:
However, when you check your Google Ads Reports, you see the updated campaign name reflected as "Spring Camping Gear Sale," indicating that the change has been implemented in Google Ads.
The metrics in Google Ads Reports accurately reflect the performance of the campaign under its new name.
What is regex (regular expressions)?
Regular expressions, often abbreviated as regex, are powerful tools for pattern matching in strings. They allow you to define search patterns using symbols and characters to match specific text patterns within a larger body of text.
How are regular expression used in in Channel groupings?
In the context of Channel Groupings in Google Analytics, regular expressions are used to define rules for categorizing traffic based on specific criteria. By default, when you define a rule using a string in Channel Grouping definitions, it’s treated as a full match. This means it only matches the exact string you provide.
Example:
Let’s say you want to define a channel to include traffic from campaigns containing the term “January.” If you specify the rule as “January,” it will only match sessions where the campaign exactly matches “January.”
Using . to Enable Regular Expression Behavior:*
To make the Channel Grouping editor interpret the rule as a regular expression search instead of a full match, you can add .* at the beginning and end of the string. This wildcard symbol .* represents any sequence of characters (including none). It allows for more flexible matching of patterns within the string.
Continuing the Example:
If you want to include traffic from campaigns containing the term “January,” such as “January1,” “2ndJanuary,” or simply “January,” you would define the rule as .January.. This pattern will match any campaign name that contains the substring “January,” regardless of what comes before or after it.
What regular expression to use for specific matches?
If you need to make a specific match, you can construct your regular expression accordingly. For instance, if you want to match only the exact string “site,” you would use ^site$, where ^ indicates the start of the string and $ indicates the end.
What is rich media in digital advertising?
Rich media refers to digital advertising that includes advanced features like video, audio, or interactive elements beyond standard static images or text. Examples include expandable banners, interactive ads, and video ads that offer more engaging experiences for users.
What are impressions?
Impressions in digital advertising refer to the number of times an ad is displayed or shown to users. Each time an ad appears on a webpage or within an app, it counts as one impression, regardless of whether the user interacts with the ad. Impressions are a key metric for measuring the reach and visibility of advertising campaigns.
What are custom dimensions?
Custom dimensions are additional attributes or characteristics that you can assign to your data in Google Analytics to provide more context and insights. They allow you to collect and analyze data beyond the default dimensions provided by Google Analytics.
What are custom metrics?
Custom metrics are numerical values that you define to track specific interactions, behaviors, or events on your website or app. They enable you to measure and analyze data points that are not covered by the standard metrics in Google Analytics.
What is CRM?
CRM stands for Customer Relationship Management. It refers to a technology system or strategy that businesses use to manage their interactions and relationships with current and potential customers. A CRM system typically stores and organizes customer data, including contact information, interactions, purchases, and preferences, in a centralized database.
How can custom dimensions and metrics be used?
- CRM Integration: Custom dimensions can be used to enrich Analytics data with CRM data, enabling deeper analysis and segmentation based on customer attributes.
- Game Development: For game developers, custom metrics can track in-game events such as level completions or high scores, which are more relevant than standard metrics like pageviews. This allows developers to monitor progress and performance against key objectives.
What is an index in G.A.?
Custom dimensions and metrics are assigned an index number, which serves as their unique identifier within Google Analytics.
What are the limits of custom metrics and dimensions?
- Indices Limit: Each property has a limit of 20 indices available for custom dimensions and 20 indices for custom metrics. This indicates the maximum number of custom dimensions and metrics you can create and use within your property.
- Deletion and Disabling: Custom dimensions cannot be deleted but can be disabled. Once a custom dimension is created, it becomes a permanent part of your property configuration.
- Reporting constraints: Certain custom dimensions may not be usable in reporting when combined with demographic information. This limitation can result in thresholding or incompatibility issues in reporting or with the API when requesting custom dimensions along with demographic data.
Why is it advised to avoid reusing custom dimensions?
The reason to avoid reusing custom dimensions is simple: it prevents confusion in your data analysis.
When you reuse a custom dimension by changing its name, scope, or value, both the old and new configurations can be paired in your reports. This means that data collected using the old configuration will be mixed with data collected using the new configuration. As a result, it becomes challenging to accurately interpret and analyze your data, leading to potential inaccuracies in your reports.
E.X: Custom Dimension: A custom dimension named “Purchase Channel” tracks the channel through which purchases are made (e.g., Direct, Organic Search, Paid Search).
Usage: Over time, the website decides to change the definition of the “Purchase Channel” custom dimension to include additional channels or rename existing ones.
Consequences: By editing the existing “Purchase Channel” custom dimension, both the old and new definitions are paired in reports. This may lead to confusion in analyzing purchase behavior across different channels, as data from before and after the change are combined.
What is the lifecycle of custom dimensions and metrics?
1) Configuration: you define your custom dimensions and metrics with an index, a name, and other properties like scope.
2) Collection: act of automatically gathering data from your website or app and sending it to Google Analytics for analysis.
3) Processing: the data collected with custom dimensions and metrics is processed by Google Analytics servers.
4) Reporting: you build new reports using your custom dimensions and metrics in the Analytics user interface.
What is a scope?
Scope defines the level at which the custom dimension or metric is applied, such as hit-level, session-level, or user-level.
What are configuration values of custom dimensions?
1) Name: Specifies the name of the custom dimension as it will appear in your reports, helping you identify and analyze specific aspects of user behavior or website content.
2) Scope: Determines the scope or context in which the custom dimension will be applied. It specifies the level of data aggregation, such as hit, session, user, or product scope.
3) Active: Indicates whether the custom dimension will be processed. Inactive dimensions may still appear in reporting but will not have their values processed.
What are the configuration values for custom metrics?
1) Name: Defines the name of the custom metric as it will appear in your reports, providing a clear label for the data being measured.
2) Determines how the custom metric value will be displayed in reports, such as currency, time, or integer.
3) Minimum/ Maximum values: Specifies the range of acceptable values for the custom metric. Values outside this range may not be processed or displayed accurately.
4) Active: Indicates whether the custom metric value will be processed. Inactive metrics may still appear in reporting but will not have their values processed.
What is advised upon the creation of custom dimensions or metrics?
Once a custom dimension or metric is defined, it’s advisable to avoid editing the name or scope whenever possible.
Changes to these values can impact your reporting and may require adjustments in your implementation.
How are custom dimensions and metrics data sent to G.A.?
- When sending custom dimensions or metrics to Analytics, we use a pair of parameters: the index and the value.
- custom dimensions and metrics are sent as parameters attached to other hits, such as pageviews, events, or ecommerce transactions. (It is not tracked independently)
E.X: Suppose we want to track the user’s membership level on a website. We would set up a custom dimension for “Membership Level.” Then, whenever we send a pageview hit or event hit, we include the membership level information as a parameter along with the hit.
What are the types of custom metrics?
- Integer
- Time
- Currency
What is a scope?
Determines where the custom dimension values will be applied (e.g., to hits, sessions, or users).
What are the levels of scope?
1) Product-level Scope: This scope applies the custom dimension value only to the specific product with which it’s associated (Enhanced Ecommerce only).
2) Hit-level Scope: Custom dimension values are applied only to the single interaction (hit) with which they are set.
3) Session-level Scope: Custom dimension values are applied to all interactions (hits) within a single session.
4) User-level Scope: Custom dimension values persist across all sessions for a specific user until the value changes or the dimension is made inactive.
How are custom dimensions and metric values associated with hits?
Custom dimension and metric values are tied to the hit (user interaction) with which they were received, regardless of their scope. This means that each hit carries its associated custom dimension and metric values.
How do view filters affect custom dimensions and metrics at hit scope?
If a hit is filtered by a view filter, both custom dimensions with hit scope and all custom metrics associated with that hit will be filtered as well. In other words, if the hit is excluded by a filter, its associated custom dimensions and metrics are also excluded from the reporting.
How do view filters affect custom dimensions and metrics at session or user scope?
Custom dimensions with session or user scope, however, are not affected by view filters applied to individual hits. Even if the hit they were attached to is filtered out, these dimensions’ values will still be applied to all hits in the current session. Additionally, for user-scoped dimensions, their values will persist into future sessions for that user, unaffected by the filtering of the hit that initially set them.
What is reporting?
Reporting is the stage in the data processing pipeline where collected and processed data is presented to users for analysis and insights.
How can custom dimensions and metrics be used?
- Custom Reports: Users can create custom reports using custom dimensions and metrics, allowing them to analyze data tailored to their specific needs and objectives.
- Advanced Segments: Custom dimensions and metrics can be used to create advanced segments, which enable users to isolate and analyze specific subsets of data for deeper insights.
- Secondary Dimensions: Custom dimensions can also be used as secondary dimensions in standard reports, providing additional context and granularity to the data presented in those reports.
How is data collected and transformed in G.A.?
After you’ve configured your Google Analytics account with settings such as filters, goals, and enhanced ecommerce, the data collection process begins.
Once data is collected, Google Analytics transforms it into dimensions and calculates associated metrics.
How are dimensions and metrics stored in G.A.?
Google Analytics stores transformed data in aggregate database tables.
Each dimension has its own table for fast retrieval of data when generating reports.
For example, there may be separate tables for dimensions like location, device type, and browser type.
How are reports organised in G.A.?
- Google Analytics reports consist of dimensions and their associated metrics.
- Each report focuses on a single dimension, and metrics are displayed for each value of that dimension.
- Reports typically use rows for dimensions and columns for metric data, providing a structured view of the data.
- Configuration settings such as goals or enhanced ecommerce metrics are included in reports when relevant.
2 ways of metric calculation in G.A. reports:
- Aggregate/ Overview totals: These metrics are displayed as summary statistics for your entire site, such as bounce rate or total pageviews.
- Specific to dimensions: Metrics can also be qualified by selected dimensions, providing more specific insights into user behavior. For example, analyzing “Time on Site” via the “New User” dimension can reveal differences in behavior between new and returning users.
What are ‘aggregate metrics’?
Aggregate metrics represent total values across all dimensions without considering any specific attributes.
Examples: Total sessions, total users, total pageviews, total revenue, etc.
Calculation: Aggregate metrics are calculated by summing up the corresponding values across all data points in the dataset.
Purpose: Aggregate metrics provide an overview of overall website performance or specific aspects without segmenting the data by dimensions.
What are ‘metrics specific to dimensions’?
Metrics specific to dimensions focus on particular attributes or characteristics (dimensions) of user interactions.
Examples: Sessions per country, new users per device type, pageviews per landing page, revenue per traffic source, etc.
Calculation: These metrics are calculated based on the values of the associated dimensions. For each dimension value, the metric is calculated individually.
Purpose: Metrics specific to dimensions allow for deeper analysis and segmentation of data, providing insights into how different attributes impact user behavior and website performance.
What is the benefit of storing data in aggregate tables?
Storing data in aggregate tables allows Google Analytics to retrieve information quickly when generating reports.
How to calculate Time on Page (Key metric)?
Time on Page=Timestamp of Next Pageview−Timestamp of Current Pageview
This measures the duration a user spends on a specific page before navigating to another page.
How to calculate Pages per session (Key metric)?
Pages per Session= total uniques pageview hits/ total sessions
This metric indicates the level of engagement or browsing activity within a single session.
How to calculate Average session duration (Key metric)?
Average session duration= sum of time spent in sessions/ total sessions
It provides insights into the overall duration of user sessions on the website.
