Loyalty as a Growth Engine in the Era of AI: Q&A

With customer acquisition costing at least five times more than retention and third-party cookies phasing out, enterprise brands are rethinking their loyalty strategies. In a recent Loyalty 360 webinar, Ian Young, Head of Loyalty Business Development and Account Management for Comarch Loyalty, detailed how artificial intelligence is transforming customer loyalty from a traditional cost center into an enterprise-wide growth engine. Let’s recap the session and answer key audience questions.

Evolving Loyalty from Cost Center to Revenue Driver

Modern loyalty programs resolve many problems of cookieless marketing and fragmented consumer attention. Capturing and retaining first-party data has become vital to understanding consumer behavior and maximizing Customer Lifetime Value (CLV). As these industry dynamics evolve, several key benchmarks illustrate what separates top-performing retention strategies from legacy models:

• The Financial Performance Gap: Top-quartile loyalty programs significantly outperform lower-quartile ones. Highly rated programs yield up to a 14-point higher Net Promoter Score (NPS), make members 20% more likely to choose the brand over competitors, and make consumers 50% more likely to increase purchase frequency.

• The Shift in Search Behavior: Over 35% of consumers already use AI tools like ChatGPT to research and evaluate loyalty programs—a trend particularly pronounced among Gen Z and Millennials in retail and grocery. Programs must be discoverable within AI search environments.

• The AI Progression Roadmap: Loyalty tech is moving from basic precision (predictive churn, fraud prevention, CLV scoring) into the "agentic shift". AI assistants will handle campaign execution, simulate promotional budgets, and resolve offer conflicts automatically.
  
  
• The 6 Dimensions Framework: Leading programs focus on behavior-driven growth, omnichannel real-time offers, cross-industry partnerships, deep experience integration, and continuous AI optimization.

Audience Q&A: Deep Dive into the Future of AI Loyalty

1. Which brands are leveraging AI effectively, and what platform capabilities should enterprise leaders look for?

Top performers across travel, retail, and financial services leverage AI for next-visit propensity modeling, individualized product recommendations, and automated fraud prevention (such as detecting unauthorized card scanning or internal misuse).

When evaluating loyalty platforms, decision-makers must ensure they are getting native machine learning capabilities rather than legacy rules engines wrapped in AI marketing terminology. Look for platforms with built-in predictive engines that deliver automated churn scoring, send-time optimization, personalized offer generation, and conversational marketing assistants. These capabilities streamline operations for marketing and IT teams while delivering clear ROI metrics to the CFO.

2. From the consumer POV, how much does program differentiation drive brand selection, and do members prioritize total value or novelty?

Program differentiation directly translates to consumer adoption and wallet share. While total tangible value (e.g., discounts, points, cash back) establishes the rational foundation of a program, novelty and convenience drive ongoing engagement.

Consumers, especially younger demographics, increasingly evaluate programs based on instant gratification, seamless app experiences, and emotional touchpoints. Soft benefits (such as exclusive access, free shipping, or experiential rewards) often create stronger brand advocacy than points alone.

3. Is there growing demand to integrate loyalty programs with ChatGPT or Claude via Model Context Protocol (MCP) servers?

Yes, demand is shifting rapidly from initial curiosity to strategic planning. As LLMs become primary engines for search and commerce, consumers will expect to query their point balances, check tier status, and redeem benefits directly within AI conversational interfaces.

Brands that utilize standards like Model Context Protocol (MCP) servers can connect their loyalty platforms safely to external AI tools. This ensures their loyalty rewards and value propositions remain fully discoverable and actionable wherever consumers make purchasing decisions.

4. What is the value difference between a coalition program and a standalone program?

While traditional multi-brand coalition models face operational hurdles in large markets like the United States, targeted cross-industry partnerships offer the benefits of a coalition without eroding individual brand identity.

Standalone programs provide direct customer intimacy, but pairing them with relevant partners (such as hotel brands partnering with rideshare services) drives higher program usage, increases daily app engagement, and expands total value for members. Developing integrated partnerships adds measurable value to any loyalty ecosystem.

Key Takeaways and Next Steps for Loyalty Leaders

• Align Loyalty with C-Suite Priorities: Build a clear business case by tracking non-member versus member spend uplift and conducting A/B campaign testing to prove measurable ROI to your CFO.
  
  
• Prepare for AI-Native Commerce: Ensure your rewards structures and program benefits are indexed so AI agents and search tools can easily discover them.
  
  
• Adopt Agentic AI Capabilities: Transition your team toward AI marketing assistants that reduce manual campaign setups and optimize promotional spend.
  
  
• Replace Static Tier Mechanics: Move away from rigid, legacy structures toward dynamic, real-time personalization across every digital and physical touchpoint.

Transitioning your program into an enterprise growth engine requires aligning tech stack capabilities with dynamic consumer expectations. By integrating AI into your loyalty platform, you can turn everyday engagement into predictable, long-term brand equity.

Download the full report on AI in customer loyalty to discover more data and expert insights that will elevate your strategy.