Custom scraper

Notino Scraper

We do not have a dedicated Notino data API. What we do have is an AI scraper that reads a notino.com page you point it at, turns it into the columns you asked for and hands them back by REST, CSV or Excel — on a schedule, priced per page.

  • notino.com
  • notino.de
  • notino.co.uk
Three stages of a Notino run: paste a notino.com URL billed on the basic tier at EUR 0.50 per 1,000 pages; declare columns such as brand and product_title; and the 12 columns it returns.

How to scrape Notino

Notino publishes no read API for its catalogue. There is no key to apply for and no endpoint to call, which is why the page is the interface. Notino is the largest European online beauty retailer and is usually the lowest published price for a given fragrance in its markets. The way to get the data is to read the page the way a customer sees it: point the AI scraper at a notino.com URL, declare the columns you want in plain English, and schedule it. Beauty prices are set per size and per shade, and a gift-with-purchase or a sampling offer can be worth more than a discount without touching the price at all.

What the AI scraper does with a notino.com link

The same three steps as any other page you point it at. Nothing about Notino is pre-built, which is exactly why it works on pages nobody wrote a connector for.

  1. Paste the link

    Give it a notino.com product or listing URL. Market, currency and assortment all come from the page itself, so there is no region setting to get wrong — the URL decides.

  2. Declare the columns

    Name each field, give it a type and write a line telling the AI what to look for. “brand” and “product_title” are the two most people start with. The schema is yours and you can change it between runs.

  3. Schedule it and collect

    Run it hourly, daily or on demand. Every run returns the same columns in the same order with a timestamp on each row, so the history builds itself.

Set it up once. The data keeps coming.

Save your search once and it runs by itself. Every run lands in your own Scrapewise database, and you pick how to read it.

  1. Set it up once

    Add your ASINs, keywords, places or apps to a scraper in the web app. New accounts get 5 free requests.

  2. Runs on your schedule

    Pick daily, weekly on the days you choose, every few days, or the first or last day of the month. Scheduled runs start at night, European time. Need it more often? Start runs from your own code.

  3. Saved in your database

    Each run adds dated rows, so this week sits next to last week. Rows are kept for 90 days.

  4. Use it your way

    Open the table in the web app and download the latest run as an Excel file. Ask your own AI assistant about it. Or pull the rows into your code with an API key.

Ask your AI assistant about your own data

Connect Claude Desktop or Claude Code with a read-only key. The assistant reads the rows you've already collected, at no extra cost on Scrapewise. With a full-access key it can start a run for you too.

  • Which of my ASINs lost the Buy Box this week?
  • Which competitor cut prices the most since Monday?
  • Show the keywords where I dropped out of the top 10.

What you send and what you get

You send a link and a column list. Everything else — market, currency, which products are on the page — comes from the page, so there is nothing to configure twice.

You give
  • Link to a Notino pagerequired

    Open the product or category page in your browser and copy the address. Any Notino country domain works the same way.

    https://www.notino.com/
  • Your column listrequired

    Field name, type and one line of plain English per column. Written once, reused on every run.

    brand, product_title, variant, size
  • How often it runsoptional

    Hourly, daily, weekly or on demand through the API. Daily is what most price monitoring uses.

    Daily at 06:00 UTC
You get

One row per product on the page, 12 columns each

  • brand
  • product_title
  • variant
  • size
  • price
  • unit_price
  • was_price
  • currency
  • availability
  • promo_text
  • product_url
  • checked_at

REST API, CSV or Excel. The column set stays the same between runs, so downstream jobs do not re-map fields.

The columns a Notino run comes back with

We are not going to print a table of invented beauty and personal care prices and call it real output. Notino did not return a readable product page to an ordinary request, so we have no run of our own to quote from. So what is published here is the column list you declare before the run, which is the same list every run comes back with.

brandBrand as the site labels it
product_titleProduct title as the site writes it
variantShade or formulation the page is showing
sizeSize as printed, which per-unit price derives from
pricePrice for that size today
unit_pricePrice per 100 ml or 100 g, where the page prints it
was_priceStrike-through price, only where the page shows one
currencyCurrency the page quoted
availabilityStock state as the page states it
promo_textGift-with-purchase or offer wording, as printed
product_urlLink back to the page the row came from
checked_atWhen this run collected the page (UTC)

Every column here is one you name yourself in the schema. If a field is not on the page on the day of the run, it comes back empty rather than guessed.

What a Notino page costs

Pay-as-you-go from your wallet. No plan, no monthly fee, no seat count.

per 1,000 pagespay-as-you-go, no plan

Measured on 3 October 2026, not assumed. A plain HTTP request for a notino.com page comes back with the page, so most runs never need a browser and never need a residential exit.

Worked example

500 Notino pages checked once a day for a month is 15,000 pages.

about EUR 7.50 for the month

You are charged for what a run actually used, not what it was expected to need, and your balance never expires.

See the full price list →

What this page is not promising

We would rather say this here than in a support ticket.

  • No dedicated Notino endpoint

    There is no Notino API in our catalogue and no pre-built Notino schema. The AI scraper reads the page you point it at — that is the whole mechanism, and it is why it works on pages nobody built a connector for.

  • Nothing behind a login

    It reads what a visitor can see. Account pricing, contract pricing and anything behind a sign-in are out of scope.

  • No field the page does not show

    If the page does not print it, the scraper cannot return it. Identifiers like EAN or GTIN only come back where the retailer publishes them.

  • A price is a point in time

    Every row carries the timestamp of the run that collected it. A price without one is not evidence, which is why the column is in the default schema.

  • Notino has one specific trap

    Each country storefront is a separate domain with its own price, and tester and full-size variants sit on the same page.

  • Not a bulk dump of the catalogue

    You give it the URLs you care about. It does not crawl notino.com end to end, and a schedule that tried to would cost more than the answer is worth.

Typical fields the AI scraper extracts from a Notino page

Treat this as a starting point rather than a fixed schema. What comes back is whatever the page actually shows on the day of the run.

Size and shade set the price

Beauty is the category where one product page is many prices, and where a size scrape without a size column is unusable.

  • Price for the size the page is showing
  • Size exactly as printed
  • Price per 100 ml or 100 g where printed
  • Shade or formulation the page is showing
  • Which sizes and shades are listed at all

Offers that are not discounts

A gift with purchase, a sampling offer or a bundle moves perceived value without moving the price, and it is text on the page.

  • Gift-with-purchase or offer wording as printed
  • Strike-through or was-price where shown
  • Bundle or set composition, where the page lists it
  • Loyalty or member price where shown
  • Promotion end date, where printed

Product identity

Beauty catalogues are brand-dense, so brand and variant are the join keys rather than a part number.

  • Brand as labelled
  • Site's own product code
  • EAN or GTIN, where published
  • Category breadcrumb
  • Ingredient list, where rendered
  • Rating and review count, where shown

The column list is one you write: name each field, give it a type and a line telling the AI what to look for. The schema belongs to your run, not to us. How Custom Schema works →

What it cannot give you If a field is not visible on the page, the scraper cannot invent it. Identifiers such as EAN or GTIN only come back when Notino publishes them.

What people use Notino data for

01

Price per 100 ml comparison

The only honest comparison in beauty, because the same product in two sizes is two different value propositions. Size as a column makes it computable.

02

Gift-with-purchase tracking

Beauty competes on offers more than on discounts, and the offer is text on the page. Capturing that wording daily reconstructs a competitor's promotional calendar.

03

Brand price-floor checks

If you own a beauty brand, this is how you see what your products are actually listed at across the retailers that carry them, per size, with the date attached.

04

Shade and range availability

Which shades a retailer actually stocks, and which have quietly gone out of stock, is a range signal that price data alone misses.

05

Assortment research before a launch

What a category carries, at what price points and sizes, from which brands, rather than what a category report says it carries.

06

Feeding your own pricing rules

The export is a normal REST API or CSV, so size, price and per-unit price land in whatever pricing model you already run.

What makes Notino harder than an ordinary storefront

Here is what the scraper is actually up against on notino.com, measured rather than assumed.

Access

  • Plain HTTP requests are answered, but the answer is the shell of the page rather than the priced version of it
  • No named protection vendor on the response, which is why this one lands on a cheaper tier than most of the cohort
  • robots.txt carries a blanket disallow, so the scheduling decision is yours to make and document

Sizes and shades multiply the page

  • Each size usually carries its own price, so a single price column is ambiguous without a size column
  • Shades are frequently separate variants with their own stock state and sometimes their own price
  • Offers are free text rather than a percentage, so they have to be captured as written rather than parsed into a number
  • Brand and category pages are lazily loaded, so a sweep is a list of URLs rather than one request

What the page publishes

  • No product-level structured data is published, so every field is read off the rendered page
  • Each country storefront is a separate domain with its own price, and tester and full-size variants sit on the same page.
  • Price is one of the last things the page settles on, so a read taken too early records the placeholder rather than the number

Keeping a history

  • A single read is a snapshot; the value is in the series, which means the run has to be scheduled and the rows kept
  • Every row carries the timestamp of the run that produced it, so two days can be compared without guesswork
  • Columns stay stable between runs, so a dashboard written once does not break when the site redesigns
FAQ

Notino scraping — questions

What people ask before pointing the scraper at notino.com.

Notino publishes no read API for its catalogue. There is no key to apply for and no endpoint to call, which is why the page is the interface.

Ready to pull Notino data into your stack?

Start free — or talk to our team about your exact fields, refresh cadence and volume.