Note d'experts

Google Ads: Optimize Your Tracking and Capitalize on Your 1st-Party Data

Mathieu Lima
Mathieu Lima
Mis à jour : 26 nov. 202510 min read

Introduction and Stakes

Google Consent Mode, sGTM, enhanced conversion tracking, customer match... Google launches and continues to launch many features, and it is sometimes difficult to see clearly. This article aims to explore the latest features related to Google Ads tracking and describe what they imply.

Reminder of Stakes

Data marketing is evolving rapidly: the GDPR framework, browser and OS restrictions (ITP for Safari and ATT for iOS), as well as user usage (use of ad blockers) are disrupting the web marketing landscape and how campaigns are managed. The culmination of these changes is the "end of cookies" (specifically third-party cookies) planned for 2024 on Google Chrome.

However, the success of digital marketing relies largely on tracking, and a loss of measurement leads to two major consequences:

  • Blind steering: advertisers do not know which actions and in particular which campaigns are profitable and how to optimize their investment.
  • Targeting and bidding algorithms are less effective and cannot deliver ads to the right people at the right time.

Major marketing players are adapting their products to respond to these challenges, reduce their dependence on third-party cookies, and limit the impact of GDPR on campaign performance (while trying to stay within the legal framework, the outline of which is also changing).

Advertisers must understand and integrate these new concepts, otherwise they risk missing growth opportunities and leaving the way open for players who know how to adapt.

1. Capitalize on 1st-Party Data

This involves sharing your customers' and prospects' data with Google (email address, first name, last name, etc.) so that the ad platform can match this data with users registered on Google environments (for example Gmail or Chrome) without needing a cookie for this. This offers three major advantages:

  • Improve campaign performance measurement (Google will be able to attribute more conversions) as cookies become less effective
  • Use these audiences for remarketing campaigns
  • Send signals about your customers to Google to help it target target profiles (Conquest campaigns with the "New Customer Acquisition" objective)

It is necessary to have the user's consent to send personal data to Google, even if this data is hashed.

1.1 [Feature] Enhanced Conversion Tracking

Definition

This is the action of enriching the conversion tag with 1st-party data, email address, and other personal data of your customers to Google (hashed data).

Technical Implication

Modification of the dataLayer + Tag mapping + Configuration in the Google Ads interface

Benefits

  • This allows increasing the volume of measured conversions attributed to Google and therefore having more data to optimize campaigns, improve targeting, and justify more budget.
  • This also allows activating other features to capitalize on 1st-party data (see Activate customer lists based on conversions).

It is a feature that brings value quickly (increase in conversions between 5% and 8%) and remains relatively easy to implement. It is also a feature that allows creating customer lists (1st-party) relatively easily.

1.2 [Feature] Customer Match

Definition

This is the act of creating audiences in Google Ads based on your customer data via the interface (CSV import), via API (notably with the use of a reverse ETL), and/or with enhanced conversion tracking (see Activation of customer lists based on conversions).

Technical Implication

  • Manual process if CSV (format the CSV file correctly and import it into Google Ads),
  • and/or activate feature 1.1 [Feature] Enhanced Conversion Tracking and 1.3.2 [Feature] - Activation of customer lists based on conversions
  • and/or via API: Data Warehouse + Reverse ETL (ex: Hightouch) or CDP (ex: Segment / Rudderstack etc) or Capture (EdgeAngel solution)

Benefits

  • This allows creating remarketing and repurchase audiences based on 1st-party data (the most robust way for campaigns of this type as Google abandons cookie-based remarketing due to changes related to privacy, browsers, and regulation).
  • This also allows using "premium" signals to optimize Conquest campaigns, as was the case with similar audiences.

Previously, it was possible to easily create and use remarketing and similar audiences via Google Analytics and/or the Google Ads tag. It is now necessary to create these audience lists based on first-party data.

For advertisers with significant marketing budgets, it is essential to set up a data architecture allowing continuous sharing of Google Ads customer lists from a Data Warehouse + Reverse ETL (or a CDP) offering more segmentation possibilities.

1.4 [Feature] - Customer Acquisition

Definition

This involves indicating to Google which are the audiences of your existing customers. Google already has information thanks to the tracking in place (based on cookies), but offers you the possibility to enrich this information with much more precise data.

Technical Implications

  • You can add "Customer Match" audiences, as well as Web and GA4 audiences directly in the interface (Conversion > Customer Acquisition > Define existing customer list).
  • You can also enrich your conversion tag with the "Provide new customer data" parameter which relies on slightly more advanced tracking where you indicate if the conversion is associated with a new customer or not (this is the most reliable method).

Benefits

  • It is a key feature to segment the approach of your campaigns between Conquest and Repurchase/Remarketing.
  • It allows knowing the proportion of new customers compared to those who repurchase at the level of your campaigns (using the New/Known Customers segment) and arbitrating more effectively between optimizing ROAS/profitability and seeking growth with new customer acquisition (medium/long-term vision).
  • Concretely, this allows you to create a specific bidding strategy according to your objectives and your activity:
    • Solution 1: give a higher value to new customers (because we know they will have repeated purchases for example) for campaigns that combine conquest and loyalty/remarketing.
    • Solution 2: bid only on new customers if you are on 100% conquest campaigns.

Use this feature as soon as you have segmented your strategy between Conquest campaigns (new customers) and remarketing/repurchase campaigns. Start by using the audiences you have, then enrich the signals using the "Provide new customer data" parameter and create a GA4 "new_customer" goal in addition to import into Google Ads.

2. Recover Signals from Users Who Have Not Given Consent

Activating 1st-party data responds to technological challenges (cookies), but requires user consent. The loss of signals related to users who have not given their consent essentially depends on your Consent Management Platform (CMP). To address this issue, Google provides a specific feature called Google Consent Mode (GCM) which aims to address this specific challenge while respecting the regulatory framework (to be validated with your legal department or DPO).

2.1 [Feature] - Google Consent Mode

Definition

Consent Mode is a Google feature allowing the advertiser to continue sending data to Google (to Google Ads, Floodlight, and GA4) in "degraded" mode when there is no positive consent from the user. Data from users who have not given their consent is notably "stripped" of the notion of user and session ID (no cookie placed on the user's browser). This feature allows limiting the collection and processing of personal data.

Technical Implication

You must adapt the configuration of your tags in connection with the consent of your users. For this, you must use a CMP preferably compatible with Consent Mode (like Didomi) or manage the setup via Google Tag Manager. The configuration presents some pitfalls to avoid and also offers sub-features like URL Passthrough or Ads Redacted Data to go further.

Benefits

  • This allows improving conversion attribution, allowing to increase the volume of measured conversions and therefore having more data to optimize campaigns, improve targeting, and justify more budget. We can expect an uplift greater than 30%.
  • GCM also allows activating behavioral modeling on GA4 if you meet certain volume conditions, which allows you to model data from users who have not consented, directly in GA4 reports.

GDPR Considerations

Google Consent Mode is a solution proposed by Google and has not been officially validated by the CNIL. Each player, in collaboration with their legal and analytics partners, must develop their own data collection strategy based on their risk assessment.

If your DPO or legal manager considers the feature compliant with the GDPR framework, we recommend activating this feature which allows "recovering" a large part of the data, necessary for steering the activity.

3. Improve the Robustness of Your Setup with Server-Side

To go beyond ad blockers and other browser and OS policies (ITP, ATT, ...) but also to gain control over this data (for example improve GDPR compliance and not send everything and anything to media platforms) and reduce JavaScript resources on your site (to gain web performance), it is possible to set up server-side tracking. Server-side tracking is also a way to go further in sharing 1st-party data in some cases.

An important point with iOS 17 also where Safari blocks GTM Web in private browsing. With sGTM you can keep your tracking.

Starting from Safari version 17 (iOS 17 and macOS 14 Sonoma), Safari blocks GTM Web in private browsing. Setting up sGTM allows keeping your tracking.

3.1 sGTM: Google Tag Manager Server-Side

Definition

sGTM is Google's server-side TMS (Tag Management System) which improves your collection architecture. sGTM complements GTM Web. It is essentially a proxy hosted by you (we speak of a 1st-party environment) which offers many advantages.

Benefits

  • More resistant: sGTM allows loading JavaScript libraries (GTM Web, Google Analytics etc.) without calling external resources. Resources are called from your own domain and are therefore less easily blocked by ad blockers and browser policies.
  • Web performance: instead of loading all JavaScript libraries of marketing solutions, we focus on a data stream (GA4 data stream or other protocol) and then, GTM Server sends the data to the different solutions. In this way we reduce the volume of JS resources on the client side and gain a few points of loading time.
  • Control, enrichment and security: you can better control the data sent to ad platforms if your privacy rules or GDPR policy require it. You can also enrich the data sent to platforms with first-party data that you do not wish to expose in the dataLayer.
  • The sGTM architecture can be used for other media platforms (TikTok, Meta, Snap, etc.). It is notably an effective way to implement Meta Conversions API (CAPI).

Technical Implications

Configuring sGTM already requires having tracking based on GTM Web + advanced dataLayer and being up to date on consent management and the configuration of your CMP. It is the most "ambitious" subject to activate in the list, but it is done very well. Here is a quick overview of actions:

  • Configure sGTM in a cloud environment on GCP / AWS / Azure directly or using a third-party service like Addingwell.
  • Modify a few lines of front-end code.
  • Make a few modifications at the hosting level (DNS records and CDN).
  • Optimize and maintain the system to ensure scalability.
  • Configure server-side tags from the Web data stream.
  • Apply GDPR rules to your setup.

To learn more, check out our expert note Server-Side Tagging with Google Tag Manager.

It is already a "game changer" at present and it will be increasingly so. We recommend any advertiser for whom measurement and optimization of marketing campaigns are essential to activate this project. Warning: there are some pitfalls to avoid, notably on consent management which can be poorly handled by media agencies who see a way, wrongly, to bypass GDPR and will expose their client to regulatory risks.

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