---
id: "action-build-dynamic-tailoring"
type: "action-item"
source_timestamps: ["\\\"§ Adapt what you present to who", "or what", "is looking.\\\""]
tags: ["personalization", "web-development"]
related: ["concept-dynamic-agent-tailoring", "open-question-agent-detection", "framework-ai-commerce-adaptation"]
action: "Develop infrastructure to detect AI agents in real-time and dynamically adjust promotional cues accordingly."
outcome: "Maximizes conversion rates by serving the optimal mix of data and persuasion cues to the specific entity browsing."
speakers: ["Jafar Sabbah", "Oguz A. Acar"]
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-tier2-06-ai-shopping-agents"
sourceUrl: "https://hbr.org/2026/05/research-traditional-marketing-doesnt-work-on-ai-shopping-agents"
sourceTitle: "Research: Traditional Marketing Doesn’t Work on AI Shopping Agents"
---
# Build dynamic tailoring infrastructure

**Action:** Develop infrastructure to detect AI agents in real time and dynamically adjust promotional cues accordingly.

**Do this:** Begin building the technical infrastructure to detect whether a human or a specific AI model is evaluating your page. Use that detection to adjust promotional cues in real time — e.g., **removing scarcity badges for advanced reasoning models** (to avoid [[concept-algorithmic-skepticism|the persuasion penalty]]) or **surfacing bundles for non-reasoning models** (see [[concept-dynamic-agent-tailoring]]).

**Expected outcome:** Maximizes conversion by serving the optimal mix of data and persuasion cues to whichever entity is browsing.

**Open dependency:** Reliable real-time detection is still an unsolved problem — see [[open-question-agent-detection]].

**Framework position:** Step 3 of the [[framework-ai-commerce-adaptation|AI-Centric E-Commerce Adaptation Strategy]].

**Related:** [[concept-dynamic-agent-tailoring]] · [[open-question-agent-detection]] · [[entity-google-ucp]] · [[framework-ai-commerce-adaptation]]