Turn a watch reference number into full specs (caliber, case, dial) as JSON

If you build anything around watch data — a marketplace, a valuation tool, an insurance

quoting flow, a collection tracker — you eventually hit the same wall: you have a

reference number (126500LN-0001, scraped from a listing or copied off an invoice)

and you need the spec sheet behind it — movement/caliber, case material, dimensions,

water resistance, dial color and finish. The listing itself never has all of this. Where

does it actually live, and how do you get it as clean data instead of copy-pasting spec

tables by hand?

The gap in the watch-data ecosystem

Watch marketplace scraping is a solved, proven market — Chrono24 scrapers on Apify

have 16,000+ runs, so people clearly pay for watch listing data. But a listing gives

you price, seller, condition, and a reference number — it does not give you the

manufacturer's full technical spec for that reference. That data lives on dedicated

reference databases, not on the marketplaces themselves.

The reference-grade source for this is WatchBase — a structured database organized

brand → model family → individual reference, with every spec Rolex, Omega, Seiko, and

hundreds of other brands publish for each watch. It has no public API and no search

endpoint, only a browsable page hierarchy, which is exactly why this data usually ends

up copy-pasted into spreadsheets one watch at a time.

What the source data looks like, cleaned up

One record per reference, normalized to the fields you actually compare across watches:

{

  "brand": "Rolex",

  "family": "Daytona",

  "reference": "126500LN-0001",

  "name": "Cosmograph Daytona Stainless Steel - Cerachrom / White / Oyster",

  "caliber": "Rolex caliber 4131",

  "movement": "Rolex caliber 4131 Hours, Minutes, Small Seconds | Chronograph, Column wheel | Chronometer",

  "material": "Ceramic, Stainless Steel",

  "glass": "Sapphire",

  "diameterMm": 40,

  "heightMm": 11.9,

  "waterResistanceM": 100,

  "dialColor": "White",

  "indexes": "Stick / Dot",

  "specs": { "...": "every raw label/value pair WatchBase publishes for this reference" }

}

The specs object matters as much as the normalized top-level fields: field coverage

varies a lot by watch (a current Rolex has far more documented fields than a 1960s

piece), and WatchBase's own labels vary slightly between brands (Material vs

Materials). Keeping the raw label/value pairs alongside the normalized fields means you

never lose data to an over-eager parser.

Getting it without hand-copying spec tables

Rather than walking WatchBase's brand → family → reference hierarchy yourself, you can

run a hosted actor that already does the discovery and normalization:

WatchBase Scraper on Apify.

Give it a brand (or a list of specific reference URLs if you already have them):

{

  "brands": ["rolex"],

  "maxItems": 200,

  "includeMovement": true,

  "includeCaseSpecs": true,

  "includeDialSpecs": true

}

curl -s -X POST "https://api.apify.com/v2/acts/minty_modesty~watchbase-scraper/runs?token=$APIFY_TOKEN" \

  -H 'content-type: application/json' \

  -d '{"brands":["rolex"],"maxItems":200}'

It reads only public reference pages (plain server-rendered HTML, allowed by

robots.txt, no login) and returns one clean record per watch. If you already have

reference numbers from a marketplace dataset, pass referenceUrls instead of a whole

brand and skip straight to the records you need.

When this is (and isn't) the right layer

If you only need one or two watches, just open the WatchBase page. If you're enriching a

marketplace dataset in bulk — hydrating thousands of Chrono24-style listings with the

manufacturer spec behind each reference — that's exactly the gap this fills: listing

scrapers get you price and reference number, this gets you everything after that.