E-commerce

Monitor MAP violations across sellers

A brand feeds in its protected SKUs and their MAP, and a Nimble Web Search Agent discovers every online seller of each product across the open web, capturing the advertised price with cited evidence. The app then flags below-MAP listings, ranks repeat offenders by seller domain, and files them into a Google Sheets tracker with a Google Doc notice per violation.

Quick Start

Inputs

  1. Protected SKUs The brand's products to monitor, for example "Olaplex No. 3 Hair Perfector 100ml", given as brand, product, and size.
  2. MAP price The Minimum Advertised Price per SKU, for example "$30.00"; anything advertised below it counts as a violation.

Outputs

  • Every online seller of each SKU, with a cited advertised price
  • Below-MAP violations flagged by severity
  • A repeat-offender leaderboard ranked by seller domain
  • A Google Sheets enforcement tracker with one row per violation
  • Google Doc notices for the most severe cases, with cited evidence

The repo ships a full 50-SKU demo cache for professional haircare (Olaplex and Kérastase): 952 seller listings across 269 domains, each with a cited advertised price, so the dashboard runs with no API calls.

View example on GitHub

How it works

A five-stage pipeline.

  1. Discover every seller For each SKU, a Web Search Agent searches the open web for every seller offering the exact product, capturing the advertised price with a cited excerpt and source URL. Category-group sources steer it toward marketplaces, independent stores, and discounters without restricting it to a fixed list.
  2. Detect the violations The app parses each advertised price and flags anything below the SKU's MAP in plain code, so the comparison is auditable rather than a model judgment.
  3. Rank repeat offenders Violations roll up by seller domain into a leaderboard showing which sellers undercut the most SKUs and by how much.
  4. File and notify The full violation list writes to a Google Sheets tracker; the most severe cases each get a Google Doc notice with the seller, listing URL, price versus MAP, and cited evidence.
  5. Investigate the evidence A Streamlit dashboard leads with the totals, the leaderboard, and a per-violation drill-down to the exact price excerpt behind each claim.

Stack

Nimble primitives plus the full runtime stack.
Nimble APIs
What it does
  1. Web Search Agent One dataset_building agent per SKU discovers every seller offering the exact product across the open web and captures each advertised price with a cited source.
3rd Party Tools
Role
  1. Python 3.10+ Resumable concurrent discovery and the deterministic below-MAP math.
  2. Google Sheets and Docs The enforcement tracker and per-violation notices, with a local file fallback when Google is not configured.
  3. Streamlit and Altair The dashboard with severity-coded views, the leaderboard, and the evidence drill-down.
  4. SQLite The offers and violations store.
Reach out if you have any questions.
Talk to an Expert