Cro Metrics 2026 Predictions
By Gwen Hammes, Co-CEO at Cro Metrics
1. Consumers Draw Deliberate Lines Between AI Delegation and Personal Experience
Consumers will become increasingly deliberate about what tasks they delegate to AI versus what they choose to experience themselves. Category-specific behavioral patterns will emerge, with individuals determining which discoveries and experiences they want to handle personally versus outsource to AI assistants. People will consciously choose based on factors including the stakes involved, personal enjoyment, and desired control. For example, consumers may delegate restaurant reservations to AI but prefer to personally explore dining options for special occasions.
LLM-driven purchasing will grow for low-stakes and commodity items where convenience outweighs the need for personal selection. However, poor AI recommendations will create return and customer service implications, raising critical questions around accountability: who is responsible when AI makes incorrect purchasing decisions on behalf of consumers? Following consumer behavior remains paramount for understanding these emerging delegation patterns and their implications for brands.
2. AI Agentic Workflows to Begin Integration into Marketing Operations
AI agentic workflows will establish their role in workplace productivity and efficiency, though they will not yet be the comprehensive solution AI companies promise. Marketing teams will increasingly embrace automation, but 2026 will remain a learning year characterized by experimentation and iteration rather than full-scale transformation.
3. Predictive Analytics Enables True Personalization
Predictive analytics will continue improving in accuracy and reliability. Better targeting predictions will enable the one-to-one marketing outcomes that have long eluded most marketers. This advancement will allow for more precise customer engagement and personalization at scale.
4. AI Disrupts Customer Journeys Faster Than Predicted While Creating New Complex Marketing Responsibilities
AI will disrupt traditional online customer journeys more rapidly than anticipated, with research and purchasing processes becoming seamlessly integrated into LLMs and bypassing the need to navigate through traditional website funnels, in some cases eliminating site visits entirely.
The scale of change is already measurable: retail site traffic from chatbot interactions increased 1,950% year-over-year during Cyber Monday 2024, while 44% of consumers now designate AI-powered search as their primary information source, surpassing traditional search (31%), brand websites (9%), and review sites (6%). The proliferation of LLMs has transformed AI into simultaneously an enabling technology, an additional audience segment, and a distribution channel. Marketing teams must now manage it as technology for their operations, target it as an audience that consumes and interprets content, and optimize for it as a discovery channel through which customers find products and services.
Three-prong Challenge
What this means for marketing teams: Marketing organizations face a three-prong challenge that creates mounting pressure on teams already tasked with delivering measurable results while managing constrained resources. First, as technology enablers, teams must implement AI tools for content creation, personalization, and automation. Second, as an audience, teams must optimize content for AI consumption including structured data, clear hierarchies, and machine-readable formats. Third, as a distribution channel, teams must ensure discoverability through AI-powered search and conversational interfaces. This complexity is evidenced by Adobe’s finding that only 14% of practitioners can now deliver exceptional digital customer experiences, down sharply from 25% just one year earlier.
While AI optimization will benefit early adopters, it will affect traditional metrics like Average Order Value and Revenue Per Visitor as customers bypass traditional funnel steps. Organizations that optimize for AI-driven discovery while also focusing on cart and checkout optimization through cross-selling and upselling, combined with robust lifecycle marketing for repeat purchases and loyalty, will achieve the strongest results. The satisfaction gap (only 34% of marketers satisfied with AI value realization) confirms teams are learning in real-time how to navigate this unprecedented complexity.
5. In-Person Moments and Authenticity Become Critical Differentiators
As AI-generated content saturates digital channels, in-person moments and authentic human experiences will become massive differentiators in marketing. A third of consumers are predicted to opt for offline over online brand experiences in 2026, driven by desires for richer sensory interactions that digital channels cannot replicate. Brands that create genuine, physical touchpoints and real human connections will stand out in an increasingly automated market.
The scarcity of authentic, non-AI-mediated experiences will drive their value upward, making them powerful tools for building trust, loyalty, and emotional resonance that AI cannot replicate. This countertrend is already measurable: 50% of consumers are expected to abandon or significantly limit social media due to perceived quality decay, misinformation, and bot proliferation, forcing them to seek authentic interactions elsewhere.
Why this matters: Marketing teams must rebalance investment toward offline and experiential marketing channels even as they simultaneously scale AI-powered digital efforts. This represents a strategic paradox: organizations must invest in opposing directions—automation for efficiency and authenticity for differentiation. Teams should increase budgets for in-person events, pop-up experiences, retail activations, community building, and face-to-face customer interactions. The 92% of marketers maintaining or increasing brand awareness investments with particular focus on authentic storytelling and value-driven content demonstrates this shift is already underway.
Marketing leaders must resist the temptation to automate everything just because they can. Some touchpoints gain value precisely because they remain human-mediated. Organizations should audit their customer journey to identify which moments benefit most from human connection and protect those experiences from automation. The brands that win will combine the scale and efficiency of AI with the trust and emotional resonance of authentic human experiences, creating a hybrid model where technology amplifies humanity rather than replacing it.
6. Generational Divides in AI Trust Require Specific Customer Experience Strategies
AI adoption will vary significantly by audience segment, with age being a particularly strong differentiator that fundamentally shapes how consumers interact with brands. Nearly half of consumers under 45 welcome virtual shopping assistants that proactively add items to their carts based on style preferences and past purchases, while acceptance among older demographics remains much lower.
The behavioral divide is stark: 31% of Gen Z most often use AI platforms or chatbots to find information online, reflecting comfort with AI-mediated discovery that older generations don’t share. Older consumers are notably less likely to provide payment information to LLMs and will demonstrate more cautious adoption patterns around AI-mediated commerce.
Why marketers should care: Marketing teams must abandon one-size-fits-all AI strategies in favor of persona-specific customer experience approaches that reflect dramatically different comfort levels and expectations across generations. Organizations must develop parallel customer journey maps: AI-native paths for younger consumers who expect conversational commerce, chatbot interactions, and automated recommendations, versus traditional paths for older consumers who value human customer service, detailed product information, and direct purchasing. Teams should segment their optimization efforts accordingly, investing in conversational AI and virtual assistants for younger demographics while maintaining human support channels and traditional navigation for older segments. The risk of getting this wrong is significant: forcing older consumers into AI-mediated experiences will drive abandonment, while failing to offer AI conveniences to younger consumers will make brands seem outdated. Brands must tailor their AI-optimization efforts to match the trust levels and behavioral preferences of each demographic segment they serve.
About Author:
Gwen Hammes is Co-CEO of Cro Metrics, where the company works with world-class clients including Bombas, Clorox, Google, and Starz to unlock growth through experimentation. Under Gwen’s leadership, Cro Metrics designs strategic digital solutions that transform brands by delivering measurable impact and driving meaningful change.
About Cro Metrics:
For over a decade, Cro Metrics has helped clients drive success through digital journey optimization and experimentation. The company leverages experimentation principles across website optimization, strategic consulting, paid media, lifecycle, analytics, and to help organizations better understand their customers, mitigate risk, and scale their businesses. For more information about Cro Metrics’ data-driven experimentation and optimization solutions, please visit https://crometrics.com/.
