Many marketing professionals are getting certifications to enrich their knowledge and boost their career potential. The Google Analytics Individual Qualification certification focuses on both basic and advanced Google Analytics concepts, including planning and principles, implementation and data collection, configuration and administration, conversion and attribution, and reports, metrics, and dimensions. In this guide we’re going to tell you what you need to know to pass the Google Analytics IQ certification.
Why Become Google Certified?
The Robert Half Technologies’ 2021 Salary Guide indicated that the difference between the salaries of an entry-level Marketing Manager with no certifications and that of an experienced Marketing Manager with professional certifications is approximately $43,000, with the entry-level position making $67,000 and the certified position making $116,500. For a Digital Marketing Specialist, the entry-level position makes $47,750 and the certified position makes $94,000.
Google certifications are very much in demand — on an average day there are approximately 220 job listings on SimplyHired and 125 on LinkedIn Jobs with Google AdWords and Analytics IQ certification prerequisites. Google Analytics Academy provides background material for students to study before taking the exam: Google Analytics for Beginners and Advanced Google Analytics.
Google Analytics for Beginners
The Google Analytics for Beginners course, which consists of 4 units and 17 lessons, each with its own video, teaches new students how to create a Google Analytics account, and set up tracking code data filters.
Students are also taught how to navigate the Google Analytics user interface and reports, along with how to set up shortcuts and dashboards. Additionally, the course teaches students how to analyze basic Audience, Acquisition, and Behavior reports, as well as how to set up campaign tracking and goals.
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Unit 1: Introducing Google Analytics
Lesson 1: Why digital analytics?
Most marketers are familiar with the concept of a purchase funnel, and the different stages within the funnel that describe customer interactions. The acquisition stage includes building awareness and acquiring user interest. The behavior stage refers to people engaging with a business. Finally, the conversion stage refers to the point when users become customers and actually do business with a brand. Using digital analytics, brands are able to measure many of the various aspects of the purchase funnel, including the online behavior that led to purchases, which enables brands to make informed decisions about how to best reach both new and current customers.
Lesson 2: How Google Analytics works
Lesson 3: Google Analytics setup
Google Analytics accounts are able to be grouped under an optional « Organization » which enables users to manage several Google Analytics accounts under one grouping. When an account is created, a property is also automatically created, and within each property is a view for that account. Each Analytics account is able to include multiple properties and each property is able to have multiple views. Every Google Analytics account has at least one property and every property is able to collect data by using a unique tracking ID. Each property is able to have multiple views. Filters in the configuration settings narrow down the data that is included in each view’s reports.
Lesson 4: How to set up views with filters
When a property is initially built, Google Analytics automatically creates an unfiltered view it names, All Web Site Data, which contains all of the raw, unchanged data that has been collected for the property. Google recommends that the name should manually be changed to « Raw data, » to reference the fact that the data has not yet been filtered. They also recommend setting up a « test view » to test the settings, and adding a setting to the test view that filters the data for automated bot and spider traffic to the website. Finally, they recommend creating a Master view, which is created by simply copying the test view. This way the user is able to test new analytics configurations in the test view before adding them to the Master view. Other filters can be added to exclude internal traffic, which excludes website traffic from one’s own IP address. Once it’s been tested and verified in the test view, it can be added to the Master view.
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Unit 2: The Google Analytics Interface
Lesson 1: Navigating Google Analytics
For a brand with multiple accounts, properties, or views set up, users are able to move from one to another by clicking on the pulldown menu with the title of the View in the upper-left corner of the interface. By opening the account picker, users can select an account, property, or view. In order to navigate between reports, the navigation on the left is used. Each section provides access to the reports that are associated with each section. Real-Time reports enable brands to view live user website behavior such as where website users are coming from. Audience reports provide user characteristics such as age and gender, location, interests, engagement, if they are a returning user, and the technology that is being used. Acquisition reports indicate the channels that brought people to the brand’s website. Behavior reports indicate how users engaged on the website, the pages that were viewed, and the specific landing and exit pages that were used. Finally, conversion reports enable brands to track website goals that are centered around a brand’s objectives.
Lesson 2: Understanding overview reports
For each report, users can select a specific date-range which lets them set the time period that is analyzed and described in the report. The date-range selector opens up a calendar where the date range is selected and applied to all of the reports in a view. A date-range can also be compared to another date-range. Users can also select a specific segment by using the segment picker, which enables them to view a specific data set that can then be used to compare metrics. A duration selector can also be used to change the data points to show hourly, weekly, or monthly. Additionally, the metric selector is used to change the metrics being displayed, such as average session duration, bounce rate, pageviews, etc. Users can also view the top ten dimensions and metrics, such as language, country, city, browser, OS, screen resolution, and more.
Lesson 3: Understanding full reports
The previous lesson delved into the Audience Overview report, and this lesson will discuss how to use the full report. To get to the full report, click the link to « view full report » at the bottom of the Audience Overview report, which shows expanded versions of each Audience report. Underneath the segment picker, users can access the Summary view, which is a summary of the dimension categorized by the Acquisition, Behavior, and Conversion metrics. Site Usage, on the other hand, lets brands see behavior metrics including users, average session duration, sessions per user, sessions, new users, and pages per session. As one would suppose, Goals enables a brand to view metrics based on the number of goals that have been configured. Ecommerce provides details about transaction metrics if they have been set up. When a user switches dimensions, and transitions from Country to City, for instance, the data from that metric will show up underneath the graph. Users can also switch between different visualizations, including data tableview, pie chart, performance view, comparison view, and the Pivot view, which creates a pivot table that can show different dimension values of rows and columns for comparison.
Lesson 4: How to share reports
Google Analytics provides users with many ways to share a report, or refer back to it under the report name at the top of the interface. Users are able to Save, Export, Share, and Edit reports. Often, there is so much data that Google Analytics only analyzes a sample of the data that has been collected, and this is referred to as « sampling. » This only returns an estimate of the exact count based on the sample. The sampling rate can be changed using the green data quality icon by setting it to Greater Precision, which will take longer to generate a report, but provides more precise metrics.
Lesson 5: How to set up dashboards and shortcuts
This lesson goes into dashboards and shortcuts, which can be used to quickly find the metrics that are most important to a brand without the need to navigate to a specific report. Dashboards can be shared or private, and are useful for many things, such as displaying summaries of various reports on a single page as widgets. Visualizations can be added for standard or real-time metrics, and filters can be added to the report widget once it’s been brought into the dashboard. Additionally, users can customize the dashboard by selecting a layout, and existing widgets can be dragged and dropped to different locations within the dashboard.
Unit 3: Basic Reports
Lesson 1: Audience reports
Audience reports assist brands to better understand the characteristics of their customers, including the country they are located in, the languages they’re using, the technology they’re using to access the brand’s website, and can also include their age and gender, how engaged they are, and their loyalty to the brand.
The Active Users report shows how many users had at least one session on a brand’s website in the last 24 hours, 7 days, 14 days, or 30 days. The Demographics reports tell brands about the age and gender of its customers, while Interests reports inform brands about its users’ preferences for specific types of web content such as music, technology, TV, or travel.
Geographics reports provide details that have been gathered anonymously about a user’s continent, sub-continent, country, and city through the IP address that is used by their web browser. Behavior reports tell a brand how often users visited and returned to their website. Finally, Technology and Mobile reports help brands to determine which technologies are being used to access their websites, as well as if users are visiting their sites via smartphones, tablets, or desktop devices.
Lesson 2: Acquisition reports
Acquisition reports enable brands to compare the performance of their different marketing channels in order to determine which sources provide them with the highest quality traffic and conversions. Google Analytics uses its tracking code from the website to capture attributes such as traffic medium, source, and marketing campaign name. The medium is the mechanism that drives visitors to a website, and includes organic search engine traffic (non-paid), CPC (Google Ads) traffic, referrals, email, and none (which indicates that a user directly typed in a brand’s domain name into a browser). Source tells brands the specific URL or search engine of the medium.
The Channels report allows brands to view traffic by channel, which aggregates sources together under each medium, and traffic sources, such as organic, direct, referral, etc. are also grouped together. Finally, the Referrals report allows brands to view traffic by which sites have linked to the brand’s website. It even allows brands to drill down to see which specific pages have linked back to the brand’s website.
Lesson 3: Behavior reports
Behavior reports are generated by Google Analytics which uses the tracking code to create a pageview each time a user visits a page on a brand’s website. The Total Pageviews metric is the sum of all the times a user loaded a page on the brand’s website, for instance. The Pageviews metric indicates how frequently each page on the site was viewed, while Average Time on Page and Bounce rate are both indications of how engaged users were on each page on the site.
Other valuable reports in this section include the Landing Pages report, which lists the pages on the brand’s website where users initially entered the website, the Exit Pages report, which shows which pages users were on when they left the website, and the Events report, which indicates how users interact with specific elements on the website, such as videos or downloads.
Unit 4: Basic Campaign and Conversion Tracking
Lesson 1: How to measure Custom Campaigns
Marketing campaigns are tracked through campaign tags, which refer to the extra bits of information that are added to the URL links of online marketing or advertising content. The extra bits include tracking parameters followed by an equal sign and a single word or hyphenated words that the brand has decided upon.
When users click on a link that has these added parameters, Google Analytics extracts the information from the link and associates the user and their behavior with the brand’s specific marketing campaign, which then enables brands to recognize which users came to their site through which specific marketing campaign.
Campaign tags include the following: medium, source, campaign, content, and term. These tags are added as parameters in URLs that are associated with the brand’s ads, and are created using Google’s URL Builder tool.
Lesson 2: Tracking campaigns with the URL Builder
Google URL Builder is used to add campaign tags to URLs, and is essentially a web form that brands can use to simplify the URL creation process. Brands begin by adding the URL that they want an ad or campaign to take users to when they perform an action (such as clicking an ad or link). The next step is to fill out the fields in the form for campaign, source, and medium. The tool is uppercase sensitive, as CAM22 is going to show up separately from cam22 in Google Analytics reports, so keep that in mind when creating tags.
Google URL Builder can only be used to create one URL at a time, so for large campaigns brands may wish to use a spreadsheet and URL template for creating URLs. Each URL should be tested to ensure that it works properly and directs the user to the page that was specified. This can be done by simply pasting each URL into the browser URL bar and testing it out.
Lesson 3: Use Goals to measure business objectives
There are two types of goals used in Google Analytics: business goals and Google Analytics goals. Business goals are, as one would imagine, actions that the brand wants its customers to take on its website, such as signing up for a newsletter, subscription, or purchasing a product or service. Google Analytics goals, on the other hand, goals are used to track conversions, total conversions, and the conversion rate.
Goal funnels can be created that provide a data visualization of the steps needed for the user to complete the goal. This enables brands to more clearly identify where users are leaving the conversion process, and helps to locate pain points in the customer journey.
There are four different types of goals: destination, which refers to the specific page a user reaches on the website, duration, which refers to the length of time for a user session, pages or screens, which refers to the number of pages a user views in one session, and events, which tracks specific actions that occur on a website.
Monetary amounts can be assigned to the conversion goal by flipping the Value toggle to On and typing in the amount that the conversion is worth. Once verified, the Funnel switch can be switched to On to add each step in the funnel. Each step represents an action that is performed by the user in order to accomplish the stated goal.
Lesson 4: How to measure Google Ads campaigns
Google Ads enables brands to generate text ads, which show up next to Google search results by matching keywords that brands bid on via users’ search queries, and display ads, which are ads that are made from text, images, animation, or video, that show up on the Google Display Network.
By linking a brand’s Google Analytics account to its Google Ads account, the brand is able to view Google Ads’ click and cost data alongside the brand’s site engagement data, create remarketing lists to use in Google Ads campaigns, import Analytics goals and transactions into Google Ads as conversions, and view site engagement data in Google Ads.
When Google Analytics and Google Ads accounts are linked, campaign data is shared between both systems, though campaign tracking is still required. Google Ads is able to automatically add a special campaign tag to a brand’s Google Ads URLs using its auto-tagging feature. Auto tagging is required by Google Analytics to get specific Google Ads dimensions into the Google Analytics system.
The Campaigns report indicates how well the various Google Ads campaigns are performing for the brand. It organizes Google Ads campaigns using the names that have been assigned in Google Ads. The Keywords report assists brands with understanding how well its keywords and individual ads are performing. The Bid adjustments report is used to automatically adjust keyword bids based on a user’s device, or time of day, or location.
Lesson 5: Course review and next steps
The course review and next steps lesson is essentially a quick recap of what has been discussed over the previous lessons, and also details some additional information about improving business using Google Analytics data, such as how to locate the top performing pages for new users, pages that are ineffective landing pages, and how users on different devices react to digital marketing campaigns.
Advanced Google Analytics
Advanced Google Analytics, which teaches students how data is collected and processed into reports that are readable. Students will be taught how to use Custom Dimensions, Custom Metrics, and Event Tracking configurations to collect business-specific data. Also covered are more advanced analysis techniques including segmentation, channel reports, audience reports, and custom reports.
The Advanced Google Analytics course teaches students how data is collected and processed into reports that are readable. Students will be taught how to use Custom Dimensions, Custom Metrics, and Event Tracking configurations to collect business-specific data. They will also learn about more advanced analysis techniques including Segmentation, Channel reports, Audience reports, and Custom reports. Other topics include marketing strategies such as Remarketing and Dynamic Remarketing that present ads to customers that have visited a brand’s website.
Unit 1: Data Collection and Processing
Lesson 1: Google Analytics data collection
Every interaction a user has with the brand’s website causes the analytics tracking code to send what is referred to as a hit (a URL string with parameters of detailed user information) to Google Analytics. Details provided by the URL string include the user’s language, the name of the page they are viewing, their screen resolution, and the Analytics ID. The most common types of hits are: pageview hits, event hits, and transaction hits. As one might imagine, pageview hits record when a web page is loaded with the tracking code, events hits occur when a specific action has been taken, such as playing a video, clicking a specific link, etc, and transaction hits happen when ecommerce purchases have occurred.
Lesson 2: Categorizing into users and sessions
Initially, Google Analytics determines new users versus returning users, categorizes hits into sessions, and joins data gathered by the tracking code with other sources of data. Since Google Analytics uses a unique ID for each user, if a user has cookies turned off, each time the user visits the page, a new unique ID will be created and Google Analytics will consider the user to be new, instead of viewing them as a returning user.
Sessions are defined as the period that begins when a user visits a web page, and ends in 30 minutes if no other hits are recorded. The time can be changed in the Google Analytics configuration if need be, for instance for sites that feature videos that may be longer than 30 minutes.
Google Analytics can be joined with other data sources, such as web-enabled kiosks and point-of-sale systems, and data collection hits are manually added to a URL string. Google Analytics can also be linked to other Google tools, such as Google Ads, AdSense, and Google Search Console.
Lesson 3: Applying configuration settings
Google Analytics enables brands to include features such as data filters, goals, data grouping, Custom Dimensions, Custom Metrics, and imported data. These are added with the goal of more accurately defining and analyzing report data. Filters can be created for a view, so that particular data is excluded, or only specific data is included, and they can also be used to modify data while it is being processed.
Filters enable brands to more properly align the report data with their business objectives and goals. Filters that are used should depend on the brand’s specific measurement objectives.
The four types of Goals used in Google Analytics are Destination (or Pageview) Goals, which are based on when a user views a particular page, Event Goals, which occur when a particular action (event) is triggered, Duration Goals, which are based on user sessions over a set period of time, and finally, Pages or Screens per Session Goals, which are based on whether a user has viewed a set amount of pages in a session.
Conversions are counted once per session for each configured goal. When Analytics detects hit data for a goal during data processing, it calculates the goal completions, goal value, and goal conversion rate, and these metrics are included in the reports.
Lesson 4: Storing data and generating reports
When the configuration settings have been updated, Google Analytics turns the data (location, device type, browser type, etc.) into dimensions, calculates metrics associated with them, and stores each dimension in a specific database table. Google Analytics reports are actually a single dimension, with corresponding metrics for each value of that dimension, and the majority of Analytics reports use rows for dimensions, and columns for metrics. Once they are set up, Goals and Enhanced Ecommerce metrics will also show up in the reports.
Often, Analytics simply performs some mathematics to come up with key metrics, such as Time on Page, which is calculated by subtracting the timestamp of a pageview hit from the timestamp of the next pageview hit from the same unique ID. Average session duration, on the other hand, is the average time the user spends from the first hit until the last hit before the user leaves the site. Many of these dimensions may come from the data from a single hit, while others may apply to data across an entire session. As processing is occurring, Analytics will determine which scope (such as hit-level, session-level, or user-level), is applied to each dimension and metric. Once Google Analytics has the dimensions and associated metrics ready, it links the raw, unfiltered data with the brand’s unique property ID. In some situations, there may be so much data to be joined that only a sample of the data will be shown in the returned report, rather than taking the extended time that calculating all of the data would take.
Additionally, users should keep in mind that once the data has been collected and processed, it can’t be changed. If the brand sets a filter to exclude data on a view, for instance, that data will be permanently removed during processing and it cannot be recovered.
Lesson 5: Creating a measurement plan
A measurement strategy is necessary in order for brands to be able to effectively guide the data that needs to be collected, and to determine the proper features that are required. Business goals need to be defined that are attainable and measurable. Each brand will have its own goals and objectives, which might be macro- or micro-conversions such as adding subscribers to a newsletter after purchasing a product (micro), filling out a contact form and following the brand on social media (micro), engaging with a particular amount of content and clicking on an article link (micro) or completing a guided support flow to solve an issue and rating a support article (macro).
Once macro- and micro-conversions have been defined, brands can begin to develop a measurement plan. Measurement plans should include the overall business objective, some different strategies which support those objectives, and tactics that will help the brand achieve its goals. Each strategy will include key performance indicators (KPIs) that are designed to assist the brand with assessing its macro- and micro-conversions.
Unit 2: Setting Up Data Collection and Configuration
Lesson 1: Organize your Analytics account
A Google Analytics account could be used by a brand with one Organization, one account, and one property that is associated with the account. Google recommends that every property have at least three views: Raw Data, Test view, and Master view. Other, larger brands may need multiple Organizations, accounts, or properties, along with additional views for each property.
Each account is assigned a unique ID, which can be seen in the Analytics tracking code. The tracking code is how the correct hit data is sent to the appropriate Analytics account. Multiple properties can be set up under each Analytics account. Even two related sites, such as websites with different URLs or subdomains (www.mysite.com vs local.mysite.com) can be tracked within a single property using what Google refers to as cross-domain tracking, aka site linking. Much like accounts, properties also feature a unique Property ID that’s appended to the Analytics ID — this is how GA recognizes which hits to associate with each property.
Lesson 2: Set up advanced filters on views
Filters assist brands by helping them to refine their data and make it more readable in their reports. Brands can, for instance, use a filter which tracks activity in a specific website directory or tracks subdomains in separate views. Filters can be predefined (and already available in Google Analytics) or custom (which allows brands to include or exclude hits from their data collections) filters.
Brands can create a custom include-only filter on the Device Category view and specify a value of Mobile. The filter will then match the value to any relevant hits that have been collected for that view.
Exclude filters can be used to specifically exclude data such as Paid Search, and Lowercase and Uppercase filters can be used to normalize that data in a report for ease of reading. Filters can be combined, and can force the case to be all uppercase or lowercase. Additionally, Advanced filters enable brands to remove, replace, and combine filter fields in more complex ways using what Google refers to as regular expressions, which are characters that can be used to identify matching text in order to trigger specific actions.
Lesson 3: Create your own Custom Dimensions
Custom Dimensions are much like default dimensions, although users define them and set their value. These types of dimensions enable brands to collect data that has been customized specifically for the brand, and enable brands to report on the particular characteristics of their customers or their behavior.
Lesson 4: Create your own Custom Metrics
When a customer performs an action on a page such as landing on an iPhone-branded product page, the code will trigger a hit, and will increment the metric in Analytics.
Lesson 5: Understand user behavior with Event Tracking
Once a user has performed an action on an element that is set up for event tracking, the event tracking code will pass along four parameters with the hit: Category, Action, Label, and Value.
- Category enables a brand to organize the events that are being tracked into groups.
- Action refers to the action the user took on the website when they caused the event to occur.
- Label is an optional value that is used to provide additional details about the element that is being tracked, such as the name of an audio track. Value is an optional numerical value that describes items such as video loading time or a specific monetary amount.
Total Events are seen as the total number of interactions users have had with the tracked element, while Unique Events are the number of users that have triggered that event. Metrics will be presented for Total Events, Unique Events, and Event and Average Value for each event category that has been set up.
Lesson 6: More useful configurations
This lesson is actually a collection of smaller lessons rather than just one lesson, and is comprised of 8 lessons, each with a video:
- Demographics and Interests reports: Once this has been toggled on, brands can view Demographics and Interests reports about the age, gender, and interests of their users.
Internal Site Search: This can be useful for tracking the search terms that users are looking for when they use the internal website search.
- Calculated Metrics: Calculated Metrics enable brands to perform mathematical computations on existing metrics, and include basic addition, subtraction, multiplication, and division.
- Channel Groupings: This enables brands to customize how Google Analytics groups channels in the brands’ reports.
- Content Grouping: Content Grouping assists brands with grouping pages in their reports to reflect the organization of their websites.
- Enhanced Ecommerce: The Enhanced Ecommerce functionality in Google Analytics enables brands to collect behavioral data for their ecommerce business, and includes how users interact with product pages, on-site marketing, the checkout process, and more.
- User ID: User IDs enable brands to track users across multiple devices (mobile, tablet, desktop PC) for a more accurate user count in their reports.
- Data Import: Data Import enables brands to upload data from a spreadsheet (or CSV file) and combine it with the Google Analytics data.
Unit 3: Advanced Analysis Tools and Techniques
Lesson 1: Segment data for insight
Segmentation in Google Analytics is a method that is used to view a subset of data in a report. Brands are able to create user segments or session segments. User segments are able to span multiple sessions with a maximum date range of 90 days. Session segments, on the other hand, are limited to user behavior within a single session.
Multiple segments can be added to a single report for comparison. For instance, segments of users that made a purchase can be compared with those who didn’t, which helps brands to see which types of users each source delivers. Additionally, there are two types of segments: default segments (segments that are already available in Google Analytics and show up in the System section) and custom segments (segments that brands create and show up under Custom).
Lesson 2: Analyze data by channel
Attribution modeling determines how sales and conversions get attributed to a brands’ marketing campaigns by applying a set of rules. They are designed to help brands to get a better grasp on how different marketing campaigns and different marketing channels work together to produce conversions.
Additionally, Google Analytics has a series of reports that are referred to as Multi-Channel Funnel reports (MCF). The MCF reports can tell a brand what role prior marketing activities had in the conversion process. Channels that played a role in a conversion before the final interaction would be credited with an assisted conversion.
Even more interesting, MCF reports are able to indicate the time it took a user to go from initial interest to purchase. This includes interactions across virtually all digital channels, and includes paid and organic search, referral sites, affiliates, social networks, and email campaigns.
The Overview report includes the Store’s total conversions, click-assisted, impression-assisted, and rich media-assisted conversions. The Assisted Conversions report features the total number and monetary value of assisted sales and conversions broken out by channel. The Top Conversions Paths report details the conversions and conversion value grouped by the channel combinations. Finally, the Time Lag report reveals conversions grouped by the number of days from initial interest to conversion.
Lesson 3: Analyze data by audience
The Active Users report allows brands to gauge the interest level of users on their websites. The report measures the number of unique users who initiated sessions on a website over the last 24 hours, week, two weeks, or thirty days. This can be useful for monitoring traffic drops.
Cohort Type allows brands to select a single dimension of cohort to report on, such as the cohort type Acquisition Date, which groups cohorts based on when users started their initial sessions with the brand’s website.
Benchmarking reports allow brands to compare their data with anonymized aggregated industry data from other brands who have agreed to share their data. Brands are able to select from over 1600 industry verticals to compare themselves against. The Channels report compares a brand’s channel data to benchmarks for every channel in the Default Channel Grouping. The Location report compares a brand’s Country/Territory data to the benchmarks for each of the Countries and Territories that the brand receives traffic from. Finally, the Devices report compares a brand’s Devices data to benchmarks for traffic on desktop, mobile, and tablet devices.
Lesson 4: Analyze data with Custom Reports
The Customization area includes all of the dashboards, shortcuts, alerts, or Custom Reports that have been created. There are three different types of Custom Reports, including Explorer, which is the standard Analytics report that features a line graph and a data table, search and sort options, and secondary dimensions, Flat Table, which is a static, sortable table that displays data in rows, and Map Overlay, which is a map of the world with regions and countries in darker colors for an indication of traffic and engagement volume.
Custom Reports can be used instead of secondary dimensions when brands want to use a Custom Dimension as a primary, not secondary, dimension, as well as when brands want to see more than two dimensions per row. Additionally, Custom Reports enable brands to report on any Custom Metrics they have collected.
Unit 4: Advanced Marketing Tools
Lesson 1: Introduction to remarketing
Remarketing is used to target ad content to users that have already visited a brand’s website. For users that have visited the brand’s website but haven’t made a purchase, remarketing can be used to show them relevant ads on the Google Display Network, mobile apps, or Google Search. This can be used to turn leads into conversions.
Once remarketing has been set up, brands are able to create specific Audiences that enable them to target groups of users based on common attributes. Audiences are created through browser cookies from users that visited a site with Google Analytics implemented and remarketing tracking code enabled.
Lesson 2: Better targeting with Dynamic Remarketing
Dynamic Remarketing enables brands to target remarketing ads more precisely, and enables them to target based on the content or products that users have previously viewed on the brand’s website, purchase histories and demographics, and related and top-performing content and products.
For Dynamic Remarketing to work, brands need to locate their Vertical Attributes, create Custom Dimensions, and update their website tags. Next, they will need to create Audiences and Attributes, and finally, create the Dynamic Remarketing campaign in Google Ads. Once the Google Ads campaign has been created, brands will be able to re-attract audiences based on the content that users previously viewed on their website.
Lesson 3: Course Summary
Google Analytics begins with measurement, and involves asking questions such as « how many users are finishing the customer journey” and “where is the brand losing or retaining customers along the customer journey?” In order to effectively measure, brands must collect the appropriate data that is needed to answer such questions.
Once it has been collected, the data must be packaged into readable reports that provide actionable insights which can be used by leaders to make vital strategic decisions. Of course, then the data must be analyzed, trends have to be identified, data may be segmented, and a competitive analysis may be needed to compare a brand’s performance with related industry benchmarks.
The final phase of the process must be undertaken — testing different solutions to problems that were discovered throughout the process. Analysis enables brands to locate opportunities that will allow them to improve, as well as determine what has been working all along, and what hasn’t worked to turn prospective leads into customers.
The Google Analytics IQ Exam
The Google Analytics Individual Qualification certification exam consists of 70 questions, drawn randomly from a pool of approximately 101 questions (the exact number is unknown). Students are given 75 minutes to complete the exam, and Google requires a score of 80% or greater on the certification exam in order to receive the certification. Once an answer is selected, students cannot go back and change it, so answers should be selected carefully. If a student fails to pass the exam, they can retake it in 24 hours. The Google Analytics IQ certification is valid for one year.