Platform · Repsol

Repsol Station Data

Two numbers describe a Spanish forecourt: the price on the sign and the discount in the advertising.

Repsol operates one of Iberia's largest networks, and its prices appear in the ministry's public price service alongside every other Spanish station, which gives a clean official baseline. The brand-level work sits on top: advertised per-litre discounts tied to loyalty apps and partner programmes are published with conditions, and those conditions — minimum spend, eligible grades, time windows — are what decide whether the discount is real for a given driver. Records sit at site level with brand and operator as separate keys and an observed_at stamp on every row, nothing behind a login or an exchange licence is collected, and a site that disappears is confirmed across runs before it is called a closure.

A discount without its conditions is marketing. With them, it is data.

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repsol_sample.jsonl LIVE FEED

{"site_id":"official id","price_displayed":1.529,"currency":"EUR"} {"discount_value":0.10,"discount_unit":"EUR per litre","discount_conditions":"as advertised"} {"valid_from":"2026-09-01","valid_to":"2026-09-30","site_format":"branded"}

illustrative sample rows · ESprice and discount apart · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Repsol or its owners. Repsol and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Repsol at a glance

How we handle Repsol specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Baseline: Official ministry price service
Brand layer: Advertised discounts
Conditions: Spend, grade and time windows
Merging: Never into the displayed price
Network: Iberian, with unmanned competitors
Grades: Native labels kept
Services: Shop, wash, EV bays
Refresh: Daily price, weekly conditions

Platform specifics

Displayed price and advertised discount

These are the reasons a Repsol dataset needs its own handling rather than a shared retail schema.

Discount fields

Discount terms change more slowly than prices, so they are tracked on their own cadence with their own validity window.

price_displayed from the official service or the site.
discount_value with discount_unit as advertised.
discount_conditions and valid_from / valid_to.
effective_price_range derived only where all conditions are published.

Unmanned competitors, and what we do not do

Unmanned competitors

Low-cost unmanned operators sit structurally below branded sites in Iberia and are collected as their own peer group. See our Spain and Italy page.

Site level

Every figure stays attached to its site and its observation time rather than being rolled into an area average, as the fuel and energy hub describes.

What we do not do

Merge a discount into the displayed price, claim an effective price when conditions are not published, use an app account, or compare branded and unmanned sites as peers.

Scope

What we collect on Repsol, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

Displayed price kept clean
Discounts with value and unit
Conditions and validity windows
Effective price only when derivable
Official service as baseline
Unmanned sites as their own peer group
Brand and operator as separate keys
Native grade labels kept
Daily price refresh

❌ What we do not, and why

Discounts merged into price
Effective prices without conditions
App accounts
Branded and unmanned compared as peers
Averages as the deliverable

Core Repsol fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
site_id	Official identifier
brand / operator	Two keys
price_displayed / currency_unit	EUR per litre
discount_value / discount_unit	As advertised
discount_conditions	As published
valid_from / valid_to	Offer window
effective_price_range	Derived where possible
site_format	branded, unmanned
grade_key / grade_native	Both kept
lat / lon / address	Geocoded
source / observed_at	Per record

Use cases

What teams do with Repsol data

Promotion tracking

Discount depth and duration.

Competitive position

Branded against unmanned sites.

Catchment analysis

Position within a radius.

Grade spread

Premium against standard.

The 24-hour sample — run on your sources, not ours

Send us a Repsol item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Repsol is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Repsol data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what fuel & energy data covers, and a Repsol-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Repsol data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

It is the baseline. Discount terms sit on top and change the real cost.

Only where every condition is published, and it is labelled derived.

No accounts. Only publicly advertised terms.

Yes, as a separate peer group.

More slowly than prices, so they are tracked weekly.

It depends on sites, offers and refresh.

Talk to us.

See real Repsol data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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