Why digital marketers should treat trust as a strategic asset

The terrain is complex. Regulations such as GDPR and CCPA are a net positive for consumer rights, but can create issues for marketers. Their broad scope can create ambiguity and inconsistent requirements. Likewise, browser-level tracker blocking enhances privacy but fragments measurement, making campaign performance harder for us to assess.

At the same time, AI adoption is accelerating. These solutions thrive on large datasets, yet paradoxically, marketers are experiencing the rapid AI growth alongside a sharp decline in the volume of data available, caused in part by tighter regulations.

To navigate these challenges, here are five priorities for thriving in a privacy-first world.

Build trust

Respecting user privacy is non-negotiable. The path forward is not about exploiting loopholes but about fostering genuine trust. Research shows a strong link between brand trust and higher opt-in rates. A Cookie Information study of 2,000 Nordic sites found cookie acceptance was driven largely by how much users trusted the brand and the clarity of its banner. While average opt-in rates were 72.5%–82%, there was up to a 35.3% swing for brands using identical cookie banners, suggesting trust plays a significant role.

If you’re not already doing so, measure trust in your brand tracker and correlate it with consent management platform (CMP) opt-in rates. Earned trust directly translates into richer first-party data.

Leverage privacy-enhancing tech

Two factors should be considered within your data strategy: volume and quality. Google, Meta, and various other platforms have invested heavily in privacy-enhancing technologies to address both. Google Tag Gateway has been shown to increase data volume by up to 11% based on Google’s internal data.

Server-side Google Tag Manager (sGTM) boosts quality by safely utilizing sensitive data to be processed without exposing it to the user – enabling, for instance, real-time profitability calculations for value-based bidding. Partnering with John Lewis, we saw a 20% increase in search campaign profitability after incorporating transaction profitability into the Google bidding strategy.

Meta’s Conversions API increased ROAS by 66% in a Jellyfish study with a leading UK retailer by significantly increasing Event Match Quality (a Meta metric that scores how accurately customer information linked to a web or app event, such as a purchase, can be matched to a user’s Meta account).

Review your adoption of all privacy-enhancing technologies from all major platforms. In today’s environment, they’re no longer optional.

Align internal teams

Most privacy-enhancing technologies require legal sign-off because they involve first-party data. Marketers often see legal as a blocker; legal teams often see marketers as unaware of the risks. Both perspectives are valid, and both slow progress.

Breaking this stalemate requires deliberate alignment between marketing, legal, IT, and data teams. Legal should understand marketing priorities and roadmaps; marketing should understand what’s needed for a data protection impact assessment (DPIA) and prepare accordingly. IT and data departments are critical to the conversation as they are often the conduit to the deployment of these technologies.

Consider establishing a cross-functional steering group to meet regularly. When responsibility is shared, execution accelerates, and you avoid falling behind competitors.

Embrace conversion modeling

Regulators are mandating clearer consent options (including ‘reject all’), which inevitably reduces opt-in rates. Conversion modelling tools, such as Google Consent Mode, bridge the gap by respecting user choices while predicting the behavior of non-consenting users. This provides the algorithm with additional data volume to learn and target effectively.

These tools aren’t just nice to have, as they’re often required to unlock capabilities. For example, Consent Mode is mandatory for using first-party audiences in Google within the European Economic Area.

Modeling gaps in both behavioral and conversion data is now a primary data collection strategy, not a fallback.

Test and refine, continuously

As with any implementation, particularly with strong economic headwinds, proving ROI is essential. While incrementality testing and media mix modeling remain the gold standard, fast and cost-efficient methods like Causal Impact testing can also deliver value. Based on historical data, Causal Impact can be run at scale using Google’s open-source Causmos solution.

Review your testing cadence and ensure insights feed directly into planning. In a fast-shifting regulatory and economic environment, continuous learning is the surest way to secure ongoing investment.

The bottom line is that in the privacy-first era, growth belongs to marketers who see trust as a competitive advantage, harness privacy-enhancing technologies, and unite their teams around shared goals. Measurement will evolve, but for those who adapt early, it can become not only more resilient but also a driver of smarter, more effective marketing.