Agent Rejection Analytics
Agentic Commerce

Agent Rejection Analytics

AI shopping agents are evaluating your store right now — but traditional analytics can’t see them. Simulate their visits, diagnose why they reject your store, apply fixes, and verify the impact.

Buyer Profiles

6 archetypes

Each profile represents a distinct AI shopping agent archetype with unique priorities and constraints. Weights determine how many simulated visits each profile receives.

Price-Sensitive
Primary Constraint

Lowest cost within requirements

Example Mandate

“Find a stand mixer under $300 with at least 4-star reviews”

Visit Weight
23%
Speed-Obsessed
Primary Constraint

Fastest delivery

Example Mandate

“Espresso machine under $500, delivered within 2 days”

Visit Weight
20%
Brand-Loyal
Primary Constraint

Specific brand or brand tier

Example Mandate

“Only consider KitchenAid or Breville products”

Visit Weight
15%
Sustainability-First
Primary Constraint

Verified environmental claims

Example Mandate

“Prefer products with certified sustainable sourcing; reject if no verifiable claims”

Visit Weight
12%
Spec-Comparator
Primary Constraint

Detailed feature comparison

Example Mandate

“Compare blenders by motor wattage, jar capacity, and warranty length”

Visit Weight
17%
Return-Conscious
Primary Constraint

Low-risk purchase

Example Mandate

“Only buy from merchants with free 30-day returns, clearly stated”

Visit Weight
13%
Run Simulation
We’ll send 25 AI shopping agents — each with different buyer priorities — to evaluate your store.

More visits produce more statistically significant results but take longer to simulate.