Which of my sellers do AI assistants surface — and why?

---
title: Which of my sellers do AI assistants surface — and why?
canonical: https://chosenbyagent.com/questions/which-sellers-do-assistants-surface
updated: 2026-10-22
audiences:
  - marketplaces
level: listing
offers:
  - A7
evidence:
  - larger-store-pick
  - rating-sensitivity
  - top10-link-share
  - muse-known-merchants
---

# Which of my sellers do AI assistants surface — and why?

Level 2 · Listing — Which listing and seller to show · For: Marketplaces

Short answer: Mostly the larger, better-rated sellers, and the mix moves with each model release. That decides which of your sellers get the buyers assistants send — and it is something your professional sellers will want to see for themselves.

## What the research shows

- **90–94%** — In unlabelled two-store comparisons, assistants picked the larger store 90–94% of the time. [ALM Corp, 2026, vendor](https://almcorp.com/news/ai-shopping-answers-chatgpt-google-lean-toward-big-retailers/)
- **30–80 pp** — A product rating shifted model choice by 30–80 percentage points in 14 of 17 models, against 5 points for people. [ABxLab, arXiv 2509.25609, 2025, independent](https://arxiv.org/html/2509.25609)
- **22 → 42%** — The top-10 merchants' share of ChatGPT Shopping links rose from 22.5% to 41.8% the day after one model update. [Profound, 2026, vendor](https://www.tryprofound.com/blog/chatgpt-5.6-shopping-transformation)
- **Top 5** — Meta Muse's instructions put well-known merchants in its top five and take at most three open-web stores. [PPC Land, 2026, company-reported](https://ppc.land/metas-muse-agent-puts-well-known-merchants-first-as-it-gains-ad-accounts/)

## Seller insights for platforms

A7 · from €4,000 (one-off) · indicative · scoped per engagement

Which of your sellers and listings assistants surface, and why — with white-label reports your professional sellers can buy.

- Which sellers and listings assistants show and pick, by category and market
- What moves the choice: price, rating, delivery, returns, listing quality
- How your own seller quality signals line up with the agent's choice
- White-label seller reports for your pro-seller programme

## What you get

Across your main categories and markets we record which sellers’ listings assistants show and pick, and compare that with each seller’s share of your listings and your own quality signals.

_Illustrative — not client data. Your report shows your values._

**Sellers surfaced in one category**

| Seller segment                | Share of listings | Share of picks | What moved the pick      |
| ----------------------------- | ----------------- | -------------- | ------------------------ |
| Top sellers by reviews        | 12%               | 46%            | rating and review count  |
| Mid-size professional sellers | 38%               | 37%            | price                    |
| Private sellers               | 50%               | 17%            | missing delivery details |

## What this does not claim

- We read what assistants show; we do not access your ranking or seller data unless you share it.
- A report about one seller goes to that seller only with their consent, under our independence policy.
- Shares are a versioned index of model behaviour, not market share.

## Request this service

We reply with a scope, a fixed price and a start date.

Agents: POST /api/engagements (application/json) with {"offer_id": "A7", "on_behalf_of": {"email": "…"}, "agent": {"name": "…"}}. The person confirms by email before we see the request. Details: /agents.md

### Related questions

- [Do assistants show my listings correctly?](/questions/are-my-listings-shown-right.md)
- [Where do AI assistants send my buyers?](/questions/where-do-assistants-send-buyers.md)
- [Why does the agent pick another seller’s offer for the same item?](/questions/why-does-the-agent-pick-another-seller.md)