Google Consent Mode’s Impact on Marketing Platforms: What Advertisers Need to Know

Marketing is changing with Google Consent Mode—impacting tracking, attribution, and ad performance. Find out how businesses can adapt while staying compliant with privacy laws like GDPR.

Monika Boldak

Associate Director, Marketing

Connecting Data Analysis and Marketing Strategies

Google Consent Mode enables businesses to stay compliant with privacy regulations like GDPR and CCPA while continuing to collect valuable data. As third-party cookie deprecation accelerates and privacy concerns rise, traditional tracking methods face growing limitations. Consent Mode offers a solution by allowing for aggregated and modeled data collection when users decline cookies, helping businesses retain insights while prioritizing user privacy.

Key Changes and Impacts on Metrics

Conversions Reporting:
- Before Consent Mode: Conversions were tracked using third-party cookies, allowing direct insights into user actions and precise conversion rates. This highly accurate method tied conversions to specific users across sessions and devices, allowing marketers to optimize campaigns effectively. However, this reliance on cookies often violated privacy regulations and led to data being collected without explicit user consent.
  - Why It's Changing: With cookie deprecation and privacy regulations like GDPR, direct tracking without user consent is no longer viable. Google Chrome is planning to phase out third-party cookies, following in the steps of Safari and Firefox. Collecting data without consent is risky and can result in legal penalties and customer distrust.
- With Consent Mode: When users deny cookies, conversions are modeled based on data from consenting users. Google uses machine learning to estimate conversions for non-consenting users. This provides partial data recovery, but conversion accuracy may decrease due to the reliance on estimates rather than actual user data. Businesses can still get an idea of conversion trends, but precise targeting and optimization may be more difficult.
Users and Sessions:
- Before Consent Mode: Websites could track users across multiple sessions using cookies, giving detailed insights into return visitors and user engagement. However, this practice often tracked users without their consent, violating privacy laws and raising ethical concerns.
  - Why It's Changing: With growing privacy awareness and browser-level cookie blocking, tracking users without their consent is becoming increasingly difficult. This results in incomplete session attribution and risks non-compliance with laws like GDPR.
- With Consent Mode: Non-consenting users are measured anonymously, with no third-party cookies being used to link sessions. Each visit may be counted as a new session/user, leading to inflated user counts and underreported returning visitors. This creates fragmented user and session data, affecting metrics like returning user rates, session duration, and loyalty tracking. However, the Consent Mode ensures compliance while still providing some data for analysis, albeit less granular and precise.
Behavioral Data (Events, Page Views):
- Before Consent Mode: Websites could track user actions like page views, clicks, and other interactions with precision using cookies. Behavioral data was comprehensive, helping businesses understand user journeys and optimize user experiences. However, tracking often occurred without explicit consent, breaching privacy laws.
  - Why It's Changing: Cookie-based tracking without consent is no longer acceptable due to privacy regulations. Users must now give explicit permission for their behavior to be tracked, and without consent, websites must stop tracking or risk legal repercussions.
- With Consent Mode: Behavioral data from non-consenting users is aggregated and partially modeled. While page views and events are still logged, the depth of data is limited, and user behavior modeling fills in the gaps. This means businesses receive estimated insights rather than direct data. Event-based models still provide some value, but optimizations based on these estimates may be less accurate compared to consented data.
Attribution Models:
- Before Consent Mode: Attribution models, which track users’ interactions across multiple touchpoints, relied heavily on cookies to link behaviors across sessions and devices. This allowed marketers to precisely attribute conversions to specific channels or campaigns. However, this cross-site tracking often occurred without user awareness, violating privacy expectations and regulations.
  - Why It's Changing: Privacy laws require explicit consent for cross-site and cross-device tracking, making traditional attribution models less effective as cookies are blocked or rejected. Without cookies, businesses lose visibility into the customer journey, making it harder to attribute sales accurately.
- With Consent Mode: Attribution models become more reliant on modeled data for users who don’t consent to tracking. Google’s machine learning algorithms estimate the contribution of non-consenting users to overall performance, providing a generalized view of attribution. While these models can still give directional insights, they lack the precision of cookie-based tracking, leading to potential inaccuracies in campaign performance assessments.
Audience Segmentation and Remarketing:
- Before Consent Mode: Marketers could create highly targeted segments and remarketing lists based on detailed user data collected via cookies. Remarketing allowed businesses to retarget users with personalized ads, increasing engagement and conversion rates. However, this approach often violated privacy laws, as users were tracked across sites without consent.
  - Why It's Changing: As cookies are phased out and privacy regulations require explicit consent, personalized audience segmentation and remarketing without user approval is no longer allowed. This significantly limits businesses’ ability to retarget users who don’t opt in to tracking, reducing the effectiveness of personalized marketing strategies.
- With Consent Mode: Audience segmentation becomes less detailed for non-consenting users, as only anonymized data can be used. Google’s machine learning can still estimate audience behaviors and create broader, less personalized remarketing lists. However, the precision and effectiveness of remarketing efforts will diminish, leading to less targeted campaigns and potentially higher costs per conversion.

Data Accuracy and Modeling with Consent Mode

Data Accuracy: With Consent Mode, businesses retain some data collection capabilities, but the accuracy of this data is impacted. When users do not consent to cookies, the data is aggregated and less granular. Google uses modeled data to fill the gaps, meaning that the insights gained are based on estimates rather than actual user behavior. While this helps businesses maintain visibility, modeled data lacks the precision needed for highly optimized decision-making.
Modeling Impact: Machine learning plays a crucial role in Consent Mode, as Google uses it to estimate conversions, behaviors, and attribution for non-consenting users. While this provides some insights, the models require a sufficient volume of consenting users to generate accurate estimates. For businesses with low traffic, the models may not work effectively, leading to larger gaps in data and less reliable insights.
Compliance and Trust: Implementing Consent Mode is essential for maintaining user trust and complying with data privacy regulations. While it may reduce data accuracy and limit certain marketing capabilities, it ensures businesses can collect some data ethically and transparently. This shift also aligns with the broader industry move toward privacy-first data collection, which is increasingly favored by both users and regulators.

Impact of Consent Mode on Advertising Platforms

Consent Mode significantly alters the way businesses interact with advertising platforms by limiting the data available for ad personalization, retargeting, and measurement when users deny consent. Here's how it impacts major advertising platforms:

Google Ads:
- With Consent Mode: When users do not provide consent, cookieless pings still collect limited data, such as anonymized event signals, but detailed user information is not stored. Ad clicks, site interactions, and conversions are aggregated, and modeled conversions estimate actions for non-consenting users. This reduces the accuracy of conversion tracking and optimization. Additionally, remarketing lists will be less comprehensive, as users who decline cookies cannot be added. While this approach supports compliance, it limits the ability to personalize ads and refine audience targeting, potentially impacting campaign performance..
Facebook/Instagram Ads:
- With Consent Mode: Facebook and Instagram Ads rely heavily on third-party cookie-based tracking for personalized ad targeting and remarketing. Without third-party cookie consent, their ability to track users across websites and apps is significantly impaired, making it harder to serve targeted ads. Conversion tracking becomes less reliable, as no modeled data is available. However, businesses can still run broader campaigns, but the lack of personal data impacts ad relevance and performance.
TikTok Ads:
- With Consent Mode: TikTok relies on user data for ad personalization and conversion tracking, but with the deprecation of third-party cookies, its ability to do so is significantly limited. Unlike platforms integrated with Consent Mode, TikTok does not have a direct mechanism to compensate for missing cookie data. This reduces the accuracy of conversion tracking and the precision of ad targeting, making it harder to attribute user actions to specific ads. As a result, advertisers must rely on broader audience segments and less personalized content, diminishing the effectiveness of highly targeted campaigns.
Pinterest Ads:
- With Consent Mode: Pinterest Ads, which track user behavior both on and off the platform, will have less ability to serve personalized ads without the user’s consent. Conversion tracking will rely on observed data from consented users, reducing accuracy, and remarketing lists will not include non-consenting users. This results in less precise targeting and lower ad performance as the platform has limited data on non-consenting users.
Other Key Platforms:
- With Consent Mode: LinkedIn's ability to track user interactions and retarget ads is limited, reducing the effectiveness of B2B and B2C campaigns. Modeled data helps fill in the gaps, but the reduced precision in user behavior tracking impacts campaign performance.
- Twitter/X Ads: Similar to other platforms, Twitter's personalized ad targeting and conversion tracking will be affected. Non-consenting users will not be tracked across sites, leading to less effective remarketing and broader, less personalized ad campaigns.

Conclusion

Implementing Consent Mode for Google services ensures compliance with data privacy laws while still allowing for some degree of data collection through modeled estimates in Ga4 and Google Ads. However, businesses should expect reduced targeting precision, weaker remarketing capabilities, and less accurate conversion tracking across platforms like Facebook, TikTok, Pinterest, and LinkedIn and instead should prioritize remarketing through first-party data. As the digital landscape shifts toward a privacy-first model, marketers must adapt their strategies to operate effectively with less granular data.

At Napkyn, we specialize in helping businesses configure Consent Mode, ensuring seamless integration with GA4, Google Ads, and other marketing platforms. Our team can guide you through privacy-compliant data collection while optimizing your conversion tracking and ad performance.

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