Observed Signal · Jun 18, 2026 · Research Report · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Positive
AI Rewrites Consumer Loyalty, Amperity Research Finds
Amperity published The 2026 Consumer Priorities Report: The New Rules of Loyalty in the Age of AI, showing generative AI is reshaping brand discovery, purchase decisions and loyalty. The report finds widespread consumer use of tools such as ChatGPT, Claude and Gemini for product research and that many users act on AI recommendations. While personalization remains important, consumers care most about relevance, timing and trust: invasive or irrelevant personalization reduces preference, whereas trusted data usage increases engagement. Amperity’s co‑CEO Derek Slager argues brands need more than raw customer data — they need "trusted customer context" to recognise intent and respond in real time. The findings underscore a shift toward conditional loyalty and increased competitive pressure on brands to deliver timely, privacy‑respecting personalization.
Report quantifies how generative AI is altering discovery and purchase behaviour, signalling material implications for CDPs, loyalty and personalization strategies — important for MarTech/AdTech vendors and brands but not a platform policy or industry‑shifting technical release.
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Key Takeaways & Evidence Grounding
- Amperity released The 2026 Consumer Priorities Report: The New Rules of Loyalty in the Age of AI.
- 80% of generative AI users said they use tools like ChatGPT, Claude, and Gemini to research products, compare services, or plan travel.
- 80% said they sometimes or often act on AI‑generated recommendations by clicking links, making purchases, or booking services.
- 60% of consumers said AI has led them to choose a brand they had not previously considered; only 23% go directly to brands they already know without considering AI recommendations.
- 63% of consumers said they would switch brands for a better offer; 72% said personalized experiences are somewhat or very important and 78% are more likely to engage with personalization when they trust how their data is used.
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
AI Agents Recast How Brand Loyalty Is Earned
This MarTech analysis (published 2026-06-15) argues that the rise of AI assistants and agentic decision-making is changing how brand loyalty is measured and earned. As AI systems increasingly perform discovery and purchasing on behalf of consumers, brands must supply signals that machines can interpret — notably consistency, reliability, relevance and transparent consent — rather than relying solely on traditional loyalty programs. The piece emphasizes the growing strategic importance of first-party data and CRM systems as the infrastructure that makes brands legible to AI, and recommends focusing on clear, machine-readable behavioral history and ongoing value exchanges to maintain visibility in AI-driven recommendation and purchase flows.
Retailers Lose Sales by Failing Personalization Strategies
Amperity published the 2026 State of Personalisation in Retail, a consumer survey-based report showing real-time personalisation materially increases conversion and retention when retailers act on live customer intent. The study (1,000 U.S. consumers) finds consumers respond strongly to instant, relevant offers but frequently encounter irrelevant or mistimed messages. Amperity and complementary Australian research (with Arktic Fox) identify execution gaps—notably underinvestment in identity resolution—plus constrained marketing budgets that limit retailers’ ability to operationalise real-time relevance. The report highlights AI/GenAI as an increasing part of personalisation stacks, with consumers favouring blends of human and AI assistance, and argues that a solid identity foundation is required for real-time personalisation to reliably drive revenue.
AI Personalization Faces Clear Consumer Limits
MarTech summarizes findings from Omnisend’s “AI Shopping Report” showing that U.S. shoppers are willing to share certain behavioral data (browsing, purchase history, location) to get better AI-driven recommendations, but that willingness has clear boundaries. Consumers trust AI-driven discovery when the value is obvious, yet react strongly against practices perceived as unfair or opaque — notably personalized pricing, undisclosed sponsored recommendations, and autonomous purchases. The report quantifies those limits (e.g., 70% would disengage over price discrimination) and finds a rising role for AI in product discovery (some users prefer ChatGPT recommendations to traditional search). The article concludes that transparency, clear explanations and user control will determine adoption more than model sophistication.
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