Key Takeaways:

• Trust starts long before a customer shares data or interacts with AI.
• Strong brands earn loyalty through consistency, relevance, and clear identity.
• Responsible data practices create better customer experiences and business outcomes.
• AI works best when paired with human oversight and clear governance.
• The brands winning with personalization are treating trust as a competitive advantage.

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Consumers are sending brands a complicated message. They want personalization.

• In fact, 64% of consumers say they prefer brands that tailor experiences to their needs. 
• At the same time, 83% say data protection influences their purchasing decisions, and consumer sentiment toward AI has declined sharply in recent years.

Trust has become the deciding factor, and that challenge surfaced across multiple sessions at Activate Summit: 

While the conversations covered different topics, they all pointed to the same conclusion: trust is no longer just a brand attribute. It’s the foundation for how companies collect data, personalize experiences, and deploy AI.

Here’s what leading brands are getting right.

What Makes Customers Loyal to a Brand?

Before brands can earn trust through personalization, data practices, or AI, they need to earn trust at the brand level.

That was a recurring theme in How Iconic Brands Build Virality, Loyalty, and Customer Love, where Jay Livingston (Shake Shack, BarkBox) and Benoit Vatere (Liquid Death) shared how some of today’s most recognizable brands build loyalty. 

Their examples looked very different, but both pointed to the same conclusion: customers stay loyal when they know what a brand stands for.

Loyalty Through Creative Consistency

For Benoit Vatere, Chief Growth Officer at Liquid Death, loyalty starts with consistency.

From its earliest campaigns, Liquid Death committed to a specific creative lane built around comedy, surprise, and the unexpected. Rather than adapting its identity to every trend, the brand has stayed remarkably consistent in how it presents itself.

That consistency acts as a trust signal. Customers know what to expect when they interact with the brand, and that predictability creates familiarity over time.

Brands that constantly change direction may attract attention in the short term. The brands that earn loyalty give customers a clear understanding of who they are and what they stand for.

Loyalty Through Story and Belonging

Shake Shack took a different path.

As Jay Livingston explained, the company began with a story before it became a brand: a burger cart in a deteriorating New York City park that helped raise money to revitalize the neighborhood. Customers weren’t simply buying food. They felt connected to a larger mission and a specific place. 

As Shake Shack expanded, that sense of belonging remained part of the experience. Customers identify with their local Shake Shack in the same way people identify with neighborhoods, teams, or communities.

That emotional connection creates a deeper form of loyalty than transactions alone.

Key takeaways:

• Consistency helps customers understand what to expect from a brand.
• Stories create emotional connections that extend beyond products.
• Loyalty grows when customers feel part of something larger than a transaction.

The brands with the most loyal customers gave people something to believe in first. Whether that was a distinctive creative identity or a community to belong to, that foundation made every downstream interaction stronger.

What Privacy-First Personalization Actually Looks Like

Most marketing teams treat privacy and personalization as a trade-off.

The leaders in The Trust Revolution: Scaling Personalization in a Privacy-First World argued the opposite. The brands getting it right are making privacy and personalization structurally compatible by building trust into their data foundations from the start.

Consent Has to Live at the Source

For Kara Douglas, Director of Customer Lifecycle Marketing & Engagement at LegalZoom, trust isn’t a marketing value. It’s a business requirement.

Customers share highly sensitive information with LegalZoom, from wills to business formation documents. To protect that trust, the company uses its customer data platform as a governance layer, controlling what data can flow into downstream marketing and activation systems.

That approach reflects a broader principle raised by Tim Koeth of Twilio: consent cannot be enforced retroactively across multiple tools. It has to exist at the source of the data pipeline. The question isn’t whether a company has a privacy policy. It’s whether its systems operate according to it.

Data Quality Is a Compounding Performance Issue

Trust can also break down when personalization gets the wrong answer. Shelly Alvarez, VP of Marketing Services at Apply Digital, highlighted a challenge many teams overlook: bad data doesn’t just create bad customer experiences. It creates them faster.

When customer data is inaccurate, incomplete, or fragmented, personalization becomes less relevant. Recommendations miss the mark. Messages arrive at the wrong time. Experiences feel disconnected.

Over time, those moments create doubt. Customers begin to question whether a brand actually understands them. That’s why data quality is more than an operational concern. It’s a trust concern.

Key takeaways:

• Consent should be enforced at the point of data collection, not the campaign level.
• Governance helps ensure customer data is used consistently and responsibly.
• Poor data quality weakens personalization and customer confidence.
• Trust is built into the systems that power customer experiences.

This isn’t just a challenge for regulated industries. Any brand collecting behavioral or transactional data is making decisions that either strengthen or erode customer trust.

How to Use AI in Marketing Without Losing Customer Trust

The brands featured in Scaling Trust in the Age of AI: The Operating Discipline Behind Responsible Growth were not debating whether to use AI. The conversation focused on a more practical question: where does accountability live when AI influences a customer experience?

When AI Undermines the Core Brand Promise

One of the most memorable examples came from Patrick Gunia, Engineering Lead at HelloFresh. The team experimented with AI-generated food imagery to reduce production costs. Customers quickly noticed something felt off. The images looked artificial, which created a problem for a brand built around fresh, real food.

The lesson wasn’t that AI-generated images are inherently bad. It was that brands need to be careful when AI touches the core promise that customers trust them for.

That same team has successfully automated roughly 35% of customer touchpoints using AI. The difference is understanding where automation adds value and where quality standards require closer oversight.

Where the Human Layer Has to Stay

Ryan Wiggins of Mercury shared a similar perspective on customer support.

AI can streamline workflows and remove friction from routine tasks, but some moments require human judgment. A customer support interaction is often more than a service request. It can be a trust moment that shapes how a customer feels about the relationship.

The most effective teams are not asking whether humans or AI should own the experience. They are deciding where each creates the most value.

Governance in GenAI Starts With Brand Voice

Another theme that emerged from the discussion was the relationship between AI and brand voice.

As Adrian Rohr of Fabletics and other panelists discussed, organizations often worry about whether AI can accurately reflect their brand. In many cases, the bigger challenge is that the brand standards themselves have never been clearly defined.

If teams cannot consistently describe their voice, tone, and messaging, it becomes difficult to govern AI-generated content. Strong governance starts with human alignment. AI can help scale a brand voice, but it cannot define one.

Key takeaways:

• AI should support the customer experience, not compromise the brand promise.
• Human judgment remains critical in high-trust customer interactions.
• Accountability should be established before automation is deployed.
• Brand voice must be clearly defined before it can be governed in AI systems.

The question is no longer whether brands will use AI. The question is whether they have established the guardrails needed to use it responsibly.

Frequently Asked Questions (FAQs)

1. Why is trust becoming more important in customer engagement?

Trust is becoming more important because customers expect brands to personalize responsibly. While 60.2% of consumers are open to AI-generated marketing content, 34.3% cite data privacy as a top concern. As AI becomes embedded in customer engagement, trust is what determines whether customers share data, engage, and stay loyal.

2. How can brands personalize experiences without compromising privacy?

The most effective brands build privacy into their data strategy from the start. Clear consent practices, transparent data usage, and strong governance help create personalized experiences while maintaining customer confidence.

3. What role does data quality play in customer trust?

Poor data quality often leads to irrelevant messages, inconsistent experiences, and customer frustration. Strong data foundations help ensure personalization feels accurate, useful, and respectful.

4. How can companies use AI without losing customer trust?

Leading organizations use AI to improve efficiency and decision-making while maintaining human oversight for high-impact customer interactions. Clear governance and accountability help ensure AI supports, rather than undermines, the customer experience.

5. What do the most trusted brands have in common?

They are consistent in how they show up, transparent in how they handle customer data, and intentional about how they deploy new technologies. Trust is built through repeated actions, not one-time campaigns.

Loyalty Is the Return on Trust

The brands featured across these Activate sessions operate in very different industries. Liquid Death built loyalty through creative consistency. Shake Shack built it through story and belonging. LegalZoom built it through disciplined data governance. Mercury, HelloFresh, and Fabletics are working through how to scale AI without compromising customer confidence.

Different challenges. Same principle: Loyalty isn’t a metric you optimize for.

It’s what accumulates when customers trust your story, trust how you handle their data, and trust that the systems acting on your behalf are operating within boundaries you’ve intentionally defined.

That’s the competitive advantage the speakers across these sessions kept returning to. And unlike a campaign, it compounds.