Google provided essential details about its privacy and measurement solutions in its digital marketing playbook.

The digital marketing playbook is timely amidst the ongoing and ever-changing consumer privacy expectations and impending regulations such as the Montana TikTok ban and the AMERICA Act.

In the 31-page guide, Google outlines need-to-know updates for advertisers that will affect how performance is measured and how to connect with consumers in a meaningful way.

The playbook introduces how different key players, such as marketers, agencies, and executives, play a critical role in the future of advertising while keeping privacy at the top of mind.

Building Relationships With First-Party Data

The first section of Google’s playbook is dedicated to crafting a first-party data strategy.

Google outlines the importance of providing a meaningful and appropriate value exchange to strengthen customer relationships.

Part of establishing trust in capturing first-party data is putting the consumer in control of their information. This is where Apple’s App Tracking Transparency (ATT) policy comes in for iOS apps. Advertisers should review the ATT policy and determine the best action for consent in their iOS apps.

Another critical component of a first-party data strategy is integrating data sources and platforms, such as a CRM platform, into Google’s advertising and measurement tools, like Google Ads and Google Analytics.

Tools & Platforms For Accurate Measurement

In the 2nd chapter of the digital marketing playbook, Google outlines vital areas of learning:

• Creating a solid tagging foundation
• More accurate conversion measurement with first-party data and machine learning.
• Connecting and integrating multiple data sources to Ads Data Hub
• Privacy-focused app measurement
• The transition to Google Analytics 4 for measurement
• What the future of measurement looks like.

Sitewide Tagging

Unsurprisingly, marketing campaigns have been increasingly more difficult to track success.

Google’s solution? Adopt a solid sitewide tagging infrastructure.

Google provides numerous options for sitewide tagging, including:

• The Google Tag
• Google Tag Manager
• Google Tag Manager 360

For enhanced privacy and security, server-side tagging is available for both versions of Google Tag Manager.

Conversion Modeling

Another way Google has adapted to privacy changes is by introducing enhanced conversions for the web. This type of conversion tracking allows sitewide tags to collect first-party data (after a user consents), which is then sent to Google.

Google matches the hashed data to signed-in Google accounts to attribute appropriate conversions to Search and YouTube ads.

This is then where conversion modeling comes into play.

Per Google, conversion modeling will remain a key component of their measurement solutions.

Conversion modeling uses machine learning to capture and cross-reference the different signals for better performance.

Google stated in the playbook:

Wherever possible, we directly integrate conversion modeling into Google’s ads products,

so you’ll automatically find this modeled data in your conversions reporting column. This gives you insight into

conversions you otherwise would not have recorded, such as platform restrictions limiting the use of third-party

cookies or other identifiers.

Ads Data Hub for marketers uses BigQuery to aggregate first-party data and joins it with Google event-level ad campaign data. It also guarantees that personal user data is protected through privacy checks and is never available to advertisers.

Privacy-Focused App & GA4 Measurement

Following the rollout of Apple’s ATT policy, marketers should prioritize implementing on-device conversion measurement and Google Analytics for Firebase SDK for their apps.

On-device conversion measurement allows user interactions with app ads to match with app conversions, all without the user identification leaving a user’s device.

The Firebase SDK can be added to Android and iOS apps, allowing cross-platform measurement capabilities.

To meet privacy expectations, Google Analytics 4 has advanced machine learning to help bridge customer data gaps.

This includes conversion and behavioral modeling within the GA4 property. By default, the data-driven conversion model is automatically used. However, advertisers can change the default models.

Privacy Sandbox Updates

First introduced in 2019, the Privacy Sandbox continues to evolve.

Google’s tag solutions are built to integrate with the Privacy Sandbox Attribution Reporting API.

This means that the Reporting API will only report information in a way that doesn’t share consumer identity characteristics. Advertisers can expect more aggregate data around conversion tracking.

Using Platform Insights To Help Drive Growth

The last chapter in Google’s digital marketing playbook focuses on taking action utilizing the first two chapters.

It outlines:

• How to engage first-party audiences at scale
• Using AI to discover new audiences
• Staying up-to-date on privacy changes

With first-party data, marketers can adopt Customer Match to reach users across Google properties like Search, Gmail, YouTube, and Shopping. First-party data works well with Google’s Smart Bidding models to optimize for ROI.

To expand reach outside of first-party data audiences, marketers can use Google audiences that aggregate a variety of signals using AI to reach target audiences. These signals include:

• Demographic information
• Interests based on web and app activity
• Context during real-time auction bidding

The Topics API in the Privacy Sandbox now supports interest-based ads, meaning a user’s browser can shed light on user interests without tracking specific site activity.

Summary

Google’s digital marketing playbook summarizes many announcements made in the last 6-12 months.

Whether marketers have already introduced a privacy strategy or are just getting started, the guide is a great starting point.

Get the complete playbook from Google here.

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