Database · Neon PostgreSQL

market_listing

Top-recommended listings crawled from a major e-commerce marketplace using targeted search tags. Each row represents one product surfaced by the platform's recommendation algorithm for a given keyword. Data is collected in batches — earlier batches reflect stronger algorithmic promotion signals.

neondb · public.market_listing — 180 rows · imported 2026-04-15

Field Reference

Field Type Description & Values
id integer PK Auto-incremented primary key. Unique identifier for each listing row.
batch_id text Order of the crawl batch — "1" = first batch crawled (products that appear earliest in platform search results, strongest recommendation signal), "8" = last batch (appears later in results, smaller audience reach). Lower batch_id = higher platform visibility.
Values: "1" – "8"
source_screenshot text Filename of the screenshot used as the source for this row's data extraction.
e.g. "keepsake_1.png"
search_tag text The keyword searched on the platform that produced this listing in results. Represents a target market segment.
Values: "baby girl gift" · "baby keepsake" · "birth announcement" · "keepsake"
etsy_best text Platform quality tier. Currently all crawled listings are star_seller, meaning the shop meets the platform's highest seller standards (high ratings, on-time shipping, responsive).
Values: "star_seller" (all current data)
product_type text Normalized product category extracted from the listing title. Used to group and compare similar products across different shops and search tags.
e.g. "ring dish" · "jewelry dish" · "photo album" · "baby romper"
title text Full listing title as shown on the platform. Often includes personalization keywords, material, and occasion descriptors.
price integer Current (discounted) listing price, stored as an integer in platform units. Divide by 10,000 to get USD. Formula: price / 10000 = USD.
e.g. 111194 → $11.12 USD
original_price integer Pre-discount listing price in the same platform units (÷10,000 for USD). Relationship: price ≈ original_price × (1 − discount/100).
discount integer Percentage discount applied to the listing (0–100). Note: 100% of current data carries a discount — the platform strongly favors discounted listings in recommendations.
Range: 5 – 70. Most common: 41–60%
shop_name text Name of the seller shop on the platform.
e.g. "TreasureBoxStudioLTD" · "LanahomeCraft"
rating real Average star rating of the listing (1.0 – 5.0). All crawled listings score ≥ 4.0, reflecting the platform's quality filter for top recommendations.
Range in data: 4.0 – 5.0. Avg: 4.88
review_count integer Total number of customer reviews on this listing. Strong proxy for market demand and listing maturity. Used to distinguish established (1k+) from emerging (<500) products.
Range: 1 – 69,400. Median: ~530
badge text Platform-assigned visibility badge on the listing. Indicates algorithmic promotion status and demand signals. Null/empty = no special badge.
Values: "Popular now" · "Bestseller" · "Etsy's Pick" · null
free_shipping boolean Whether the listing offers free shipping to buyers. Only 16% of top listings offer free shipping — suggesting it is not a primary ranking factor for this category.
true = 29 listings · false = 150 listings
is_ad boolean Whether the listing is a paid promoted advertisement. Only 2 of 180 listings are ads — confirming that top recommendations are overwhelmingly organic.
true = 2 · false = 178
import_date date Date the row was imported into the database. Used for versioning and tracking when market snapshots were taken.
Current data: 2026-04-15

How to Read the Data

batch_id as a ranking proxy

Products in batch_id = "1" have the strongest organic visibility — they appear first in search results. As batch_id increases, the platform shows these products to fewer users. High price + high rating in later batches (5–8) suggests the algorithm surfaces premium niche products at the end of its recommendation stack.

Price is always discounted

Every listing in this dataset carries a discount (1–70%). The platform's algorithm systematically favors discounted listings. Setting an original_price and applying a 40–60% discount is the dominant competitive strategy across all search tags.

Emerging vs. Established products

A product with rating ≥ 4.8 but review_count < 500 is an emerging opportunity — quality is proven, but the market isn't yet saturated. Products with 1,000+ reviews represent validated demand but have high competition barriers.

Badge = platform momentum signal

"Popular now" indicates short-term demand spikes — the platform actively promotes these listings. "Bestseller" reflects sustained historical sales volume. "Etsy's Pick" is editorial selection (rare, 3 total). A product type with many "Popular now" badges is currently trending and worth entering quickly.


Last updated: 2026-04-15 · Source: market_listing (Neon PostgreSQL)