Which Google Analytics feature relies on machine learning for measuring conversions that can’t be spotted through direct observation?
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Google Analytics Certification (GA4) Exam Answers
To get your GA4 certificate you need to pass 50 question assessment. There are 150 possible questions and during the test you get 50 random questions from these 150. And in a random order. Our file contains all possible exam questions with verified answers.
Exam: https://skillshop.docebosaas.com/learn/courses/14810/google-analytics-certification/lessons/31258/google-analytics-certification
The Google Analytics Certification assessment consists of 50 questions and you have 75 minutes to complete.
Questions:
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By vmartinez
Which Google Analytics feature relies on machine learning for measuring conversions that can’t be spotted through direct observation?
Related question:
By vmartinez
If you wanted to create a new data set with a wide view of your business across brands, products, or regions by combining data from multiple-source properties, which Analytics 360 feature would you use?
Explanation:
A roll-up property contains data from two or more source properties. It can include source data from ordinary properties and subproperties, but not other roll-up properties.
Roll-up properties provide a broad view of your business across products, brands, or regions by combining data from multiple source properties into a single roll-up property. For example, if you have separate properties for multiple brands that your company owns, you can roll those up to a single property that provides an aggregate look at how those brands perform.
Read more here: https://support.google.com/analytics/answer/11526039
By vmartinez
You manage an eCommerce site and are creating new audiences to segment users in ways that are important to your business, like users who’ve made a purchase. Which of these is an example of a predictive audience?
Explanation:
The correct option is You create an audience of users who are likely to purchase in the next seven days. This is an example of a predictive audience because it involves forecasting future user behavior based on historical data and predictive modeling. In practical terms, predictive audiences leverage machine learning algorithms and predictive analytics techniques to identify patterns in user behavior and anticipate future actions, such as making a purchase within a specified timeframe. As someone who has worked extensively with eCommerce analytics, I’ve witnessed the effectiveness of predictive audiences in optimizing marketing strategies and driving revenue growth. By targeting users who are likely to make a purchase in the near future, businesses can focus their resources on high-potential prospects, personalize marketing messages to encourage conversion, and ultimately increase sales. This proactive approach enables eCommerce sites to stay ahead of customer needs and preferences, leading to more efficient and effective marketing campaigns.
Audiences let you segment your users in the ways that are important to your business. You can segment by dimensions, metrics, and events to include practically any subset of users.
A predictive audience is an audience with at least one condition based on a predictive metric. For example, you could build an audience for ‘likely 7-day purchasers’ that includes users who are likely to make a purchase in the next 7 days.
Read more here: https://support.google.com/analytics/answer/9805833
By vmartinez
Which of these structures represents a Google Analytics account’s hierarchy?
Explanation:
Google Analytics is organized in a hierarchy: Organization (optional) – Analytics account – Analytics property – Data Streams
Analytics account: The account is the gateway to Analytics, and provides the container for your Analytics properties. You can have one or more Analytics accounts (up to a maximum of 100). Each account can contain up to 100 properties.
Analytics property: Properties are the containers for your reports based on the data you collect from your apps and sites. You can create up to 100 properties in an account. Properties can be any combination of Google Analytics 4 properties and Universal Analytics properties.
Data streams (Google Analytics 4 properties): Each Google Analytics 4 property can have up to 50 data streams (any combination of app and web data streams, including a limit of 30 app data streams). A data stream is a flow of data from a customer touchpoint (e.g., app, website) to Analytics.
Read more here: https://support.google.com/analytics/answer/9303323
By vmartinez
To understand how many users are coming from various devices, like desktops or mobile phones, you run a report that shows this data, per device, over the past 30 days.
In this report, what is device type?
By vmartinez
You have a mobile app and want to collect and send data from the app to your Google Analytics 4 property. Which of these should you use?