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Which Attribution settings govern conversions in the Conversion Performance Report in the Advertising workspace of Google Analytics?

Property Level Attribution Settings

Google Ads Attribution Settings
Data-Driven Attribution
Last Non-Direct Click Attribution

Explanation:

In Google Analytics 4 (GA4), the attribution model used for most reports, including the Conversion Performance Report within the Advertising workspace, is determined by the Property Level Attribution Settings. This means that the attribution model you select in the Admin section for your GA4 property (e.g., Data-driven, Paid and organic last click) will govern how conversion credit is assigned across different touchpoints in those reports. Any changes made to this setting will typically apply to both historical and future data in the relevant GA4 reports, providing a consistent view of your conversion performance.

Reference Link: [GA4] Select attribution settings – Analytics Help: https://support.google.com/analytics/answer/10597962

This official Google Analytics Help page explicitly states, “The Attribution settings page lets you choose how Google Analytics assigns credit to different ads, clicks, and other factors before users trigger key events and Google Ads web conversions.” It also details how changing the “Reporting attribution model” in these settings impacts your GA4 reports.

An advertiser relies heavily on incrementality to measure offline and online media and is considering adopting a Marketing Mix Model for the first time. The director of analytics is considering both third-party and in-house solutions. They have a budget to run a third-party Marketing Mix Model (MMM) and a robust data science team who could build an in-house model. They spend the majority of their media budget on digital and prioritize measurement solutions that are digital-savvy. In what two ways would Meridian, Google’s open-source MMM solution, be a good fit for this advertiser? Select two answers.

By vmartinez

An advertiser relies heavily on incrementality to measure offline and online media and is considering adopting a Marketing Mix Model for the first time. The director of analytics is considering both third-party and in-house solutions. They have a budget to run a third-party Marketing Mix Model (MMM) and a robust data science team who could build an in-house model. They spend the majority of their media budget on digital and prioritize measurement solutions that are digital-savvy.
In what two ways would Meridian, Google’s open-source MMM solution, be a good fit for this advertiser? Select two answers.

The advertiser has allocated funds to run an MMM through a third-party vendor.

Meridian helps advertisers evaluate all media, but especially digital, with more accuracy and actionability.
The advertiser has in-house data science expertise to build and maintain Meridian.
Meridian is a replacement for the advertiser’s own multitouch attribution and incrementality testing.

Explanation:

The given answer is correct. Meridian would be a good fit for this advertiser in these two ways:

Meridian helps advertisers evaluate all media, but especially digital, with more accuracy and actionability. Meridian is Google’s open-source MMM solution, designed to provide better insights into both online and offline media, with a particular strength in digital channels by leveraging Google’s proprietary data (like YouTube reach and search query volume). This aligns with the advertiser’s focus on digital and prioritization of digital-savvy measurement.
The advertiser has in-house data science expertise to build and maintain Meridian. Meridian is an open-source solution. This means it requires a capable in-house data science team to set up, customize, and maintain the model. Since the advertiser has a robust data science team, this open-source nature is a benefit, allowing for transparency and tailoring the model to their specific needs, avoiding “black box” third-party solutions.

Reference:

About Meridian | Google for Developers: https://developers.google.com/meridian/docs/basics/about-the-project (This page explains Meridian’s focus on digital media and its open-source nature requiring in-house expertise).

You work with a national beverage distributor who’s launching a new product in a few months. They’d like to promote the product to their existing users and already have their email addresses from a partner site, so they blast information that way. What’s wrong with how they’re promoting the product?

By vmartinez

You work with a national beverage distributor who’s launching a new product in a few months. They’d like to promote the product to their existing users and already have their email addresses from a partner site, so they blast information that way. What’s wrong with how they’re promoting the product?

Your customer should have verified the email addresses.

Your customer should have emailed all previous users first.
Your customer should have asked for consent.
Your customer has used email addresses from a previous company.

Which scenario describes why an advertiser should implement consent mode?

By vmartinez

Which scenario describes why an advertiser should implement consent mode?

The advertiser needs to prevent their consent banner from showing too often to previous website visitors.

The advertiser needs a solution for deploying their consent banner to users from their Google tag.
The advertiser needs their Google tags to respect user consent for ad measurement and personalization.
The advertiser needs to attach consent to their data to continue using enhanced conversions after regulatory changes.

When a consumer completes a conversion on your website, you may receive first-party consumer data such as an email address, name, home address, and/or phone number. This data can be collected and sent to Google in a hashed form through which Google Analytics feature?

By vmartinez

When a consumer completes a conversion on your website, you may receive first-party consumer data such as an email address, name, home address, and/or phone number. This data can be collected and sent to Google in a hashed form through which Google Analytics feature?

Admin API

Customer Match
Data Import
User-provided data

You have a goal of maximizing reach and increasing awareness. To do so, you’re running a Video reach campaign (VRC) to keep your brand top of mind. Before implementing a Brand Lift study, which two considerations should you keep in mind? Select two answers.

By vmartinez

You have a goal of maximizing reach and increasing awareness. To do so, you’re running a Video reach campaign (VRC) to keep your brand top of mind. Before implementing a Brand Lift study, which two considerations should you keep in mind? Select two answers.

Lift results aren’t guaranteed because they’re based on surveying people and recording the differences in response rates.

Lift results are guaranteed because the test will keep running until there are statistically significant results.
Lift isn’t a good always-on metric because lift — over time for the same media — will decrease, which means the media is working.
Lift is a good always-on metric, because it’s a key health indicator for the campaign’s creative assets and it should increase steadily over time.

Explanation:

The given answer is correct. When planning a Brand Lift study for a Video Reach Campaign, two key considerations are:

Lift results aren’t guaranteed: Brand Lift studies rely on surveying a small portion of exposed and control groups. Responses can vary, and achieving statistically significant lift isn’t automatic, as it depends on campaign effectiveness and sample size.

Lift isn’t a good always-on metric: Lift tends to decrease over time for the same continuous media exposure. This isn’t a sign of failure; rather, it indicates the brand message has already saturated the audience, meaning the media has successfully achieved its “top-of-mind” goal. Thus, it’s better for campaign-specific measurement than continuous monitoring.

Reference: While a single definitive page stating these two points verbatim as considerations for Brand Lift might be elusive, these concepts are widely discussed in Google’s Brand Lift best practices and advanced measurement guides. For example, the idea that sustained exposure leads to diminishing new lift is a core tenet of frequency planning.

You can infer these points from: About Brand Lift studies – Google Ads Help: https://support.google.com/google-ads/answer/10285723

(This page details what Brand Lift measures and how it works, indirectly supporting these considerations about survey-based measurement and the nature of “lift” over time).