SAMPLE Luxury Handbag Price Trends – July 2025

This is a sample dataset of 30 rows for a dataset that comprises 4,413 luxury handbag listings drawn from publicly accessible online marketplaces as of mid‑2025.

Each row represents a distinct product listing, spanning top‑tier brands (e.g., Hermès, Chanel, Louis Vuitton) in both “New with tags” and “Pre‑owned” conditions. Listings originate from global sellers, capturing seller location, shipping reach, and last‑updated timestamps to reflect real‑time market dynamics. Prices are recorded in USD, normalized to transaction rates at the time of scraping.

**Data Science Applications:**
Price Prediction & Valuation: Train regression models to estimate optimal listing prices based on brand, condition, geography, and seller reputation.
Market Trend Analysis: Time‑series analysis of price fluctuations and listing volumes across brands and regions to uncover emerging luxury resale trends.
Brand & Condition Segmentation: Cluster listings by brand and condition to profile buyer segments and forecast demand for “new” versus “pre‑owned” items.
Supply Chain & Logistics Modeling: Analyze shipping‑to and excludes‑shipping fields to optimize international distribution strategies and identify underserved markets.
Seller Behavior & Reputation Analytics: Use listing update patterns and seller IDs to detect seasonal activity,-response times, and potential anomalies (e.g., counterfeit indicators).

**Column Descriptors:**
Column Description
title Full listing title (model, material, color details).
brand Luxury brand name (standardized casing).
condition Item state: “New with tags,” “Pre‑owned,” etc.
itemLocation Seller’s city and country.
lastUpdated Timestamp (e.g., “Jun 24, 2025 18:30:14 PDT”) when the listing was last refreshed.
price USD listing price (float).
seller Pseudonymous seller identifier.
shipsTo Destinations the seller ships to (e.g., “Worldwide,” specific countries).
excludesShipping Comma‑separated list of countries excluded from shipping.

**Ethically Mined Data:**
All data were ethically obtained from publicly available sources only.. No personally identifiable information (PII) beyond seller pseudonyms is retained.