Press Ganey Forsta’s new report reveals the trust gap in CX, showing how data use, personalisation, and AI transparency drive or destroy loyalty.
Loyalty is earned through trust. Press Ganey Forsta’s new research report, “The CX Trust Deficit: Loyalty at Risk in the Digital Age,” paints a clear portrait: most customers are willing to share personal data for better experiences but trust is painfully scarce. And without it, brands face real consequences: revenue erosion, friction, and fractured loyalty.
Trust Lifts Willingness But Only Up to a Point
Almost 70% of consumers in both the US (69%) and UK (64%) say they’ll share personal information if it enhances their experience. Even more compelling: 71% of Americans and 66% of Britons are comfortable paying more to buy from brands they trust. That’s a powerful strategic signal: trust doesn’t just drive conversion, it commands a premium. Yet, only a mere 19% in the US and 17% in the UK actually believe brands will use their data responsibly.
Personalisation Is a Double-Edged Sword
Personalised experiences matter. Nearly 30% of consumers (30% US, 28% UK) say they’d switch brands for better personalisation and 1 in 5 have already done so. But there’s a caveat: personalisation alone isn’t enough. It must be trustworthy, meaningful, and handled with integrity.
Speed Isn’t Enough Without Follow-Through
Nearly 60% of consumers expect a brand to respond within 24 hours, and 67% expect follow-up after their interaction. Yet many organisations still lag on those basics making speed feel hollow without the follow-up that builds confidence.
AI Is Welcome, But Human Trust Still Matters
AI’s practical benefits are undeniable: faster service, lower friction, better availability. Almost half of US (48%) and UK (45%) consumers are open to AI-powered CX. But only 1 in 5 are very comfortable interacting with AI alone. That means transparency, clarity, and hybrid human-AI balance remain critical for trust.
“Trust has always been the foundation of exceptional customer experience,” says Luke Williams, Chief Customer Experience and Research Officer at Press Ganey Forsta. “But in this era of rapid AI adoption and elevated scrutiny over data, it’s also the clearest competitive advantage.”
Five Trust-Building Mandates for Marketers
- Treat Transparency as a Differentiator
Don’t bury your data practices in fine print. Show how personal data and AI are used to enhance experiences. Clarity builds credibility.
- Master the Basics Then Innovate
Brands still best at trust are the ones who do ordinary things like responding and following up exceptionally well. Innovation only matters when fundamentals are solid.
- Personalise with Purpose
Don’t personalise for its own sake. Use data to create genuinely useful, relevant interactions. Give customers a reason to share data and demonstrate the payoff.
- Be Seamless Across Channels
From mobile and web to in-store and calls, consistency matters. Disjointed experiences erode trust and frustrate customers.
- Own Your AI, Transparently
Let customers know when AI is part of the experience. Transparency earns trust. When sensitive issues or confusion arise, make sure human help is available.
A Marketer’s Toolbox for Fixing the Trust Deficit
- Audit your data practices: Do they feel consumer-forward, or buried behind jargon?
- Map your response time & follow-up performance: Are you keeping promises or disappointing customers?
- Personalisation audit: Is your messaging helpful, or generic? Are you rewarding data sharing with value or spam?
- Channel consistency check: Does your experience reflect brand integrity across touchpoints?
- AI visibility test: If AI is at play, is it declared clearly? Are fallback human options obvious?
When privacy feels fragile and attention spans are shorter than ever, consumers are giving their loyalty to brands who earn it, not those who assume it. In a world leaning into convenience and AI, the brands that win in 2025 will be those who marry speed with empathy, data with clarity, and technology with humanity.
ALSO READ: 5 CX Challenges AI Fixes When You Start with The Problem