Platform · Glovo

Glovo Data Scraping

One app across markets that behave nothing alike. The category mix in Madrid and in Accra are different products with the same logo.

Glovo data scraping collects restaurant, grocery, pharmacy, retail and courier listings across Glovo's markets in Southern and Eastern Europe, Africa and Central Asia. The design constraint that matters: market maturity varies enormously, so category mix, assortment depth and even which verticals exist differ per country — and a single pooled schema hides all of it.

Glovo's footprint spans markets where quick commerce is mature and markets where it is the first delivery service most people have used. Those are not the same dataset.

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glovo.jsonl LIVE FEED

{"country":"ES","city":"Madrid","vertical":"grocery", "surface":"glovo_store","price_setter":"glovo", "price_local":3.49,"currency":"EUR", "verticals_observed":["restaurant","grocery","pharmacy","courier"]} {"country":"GH","city":"Accra","vertical":"restaurant", "surface":"partner","price_setter":"merchant", "price_local":48.00,"currency":"GHS", "fx_observed_at":"2026-08-25T11:04:02Z", "verticals_observed":["restaurant","courier"], "note":"grocery and pharmacy NOT live here — same logo, different product"} {"vertical":"courier", "has_catalogue":false, "caution":"anything-delivery has no products — not counted in coverage figures"}

3 of 4,880,220 listing rows · 9 countriesverticals_observed per market · FX per observation · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Glovo or its owners. Glovo 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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Glovo at a glance

How we handle Glovo specifically

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

Platform: Glovo — multi-category delivery, Europe, Africa, Central Asia
The design constraint: Market maturity varies enormously across the footprint
Consequence: Category mix and vertical availability differ per country
Country: A dimension on every record, with verticals observed recorded per market
Currency: Many, including volatile ones. FX stamped per observation
Courier category: 'Anything' delivery has no catalogue. Not a product feed
Price setter: Merchant for partner listings; Glovo for its own stores
Refresh: Daily standard; sub-daily in high-volatility markets

Platform specifics

What is specific to a footprint this varied

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

Verticals observed per market, not assumed globally

Glovo's category structure is not uniform. Pharmacy is live in some markets and not others; own-store quick commerce exists in some cities and not others; the courier category is prominent in some markets and marginal elsewhere.

A feed that assumes a global category structure produces two failure modes, both quiet:

An absent vertical looks like an absence of merchants, which reads as a market opportunity that does not exist.
A vertical present only in some cities gets averaged into a national figure that describes neither the cities with it nor those without.

We record verticals_observed per country and per city in every batch, so a gap is visible as a structural gap rather than a data gap. This is the same discipline the Uber Eats page applies, and it matters more here because the variance is wider.

Price setter, and Glovo's own stores

Glovo carries partner merchant listings and, in some markets, its own quick-commerce stores. Those are different commercial arrangements with different price setters.

Partner listings — the merchant sets the price, frequently above their own in-store price.
Glovo's own stores — Glovo sets it, holding its own inventory.

We record price_setter and surface on every record and never blend them. A price movement in a blended series could be a merchant's decision or Glovo's, with nothing in the data to say which.

The courier category is not a product feed

Glovo's "anything" courier service has no catalogue — the customer describes what they want fetched. There is nothing to collect except the service's availability and pricing structure, and we say so rather than including it in a product count.

Currencies, volatility and local-language listings

FX per observation

The footprint includes several volatile currencies. As on our Rappi Turbo work, we stamp fx_rate and fx_observed_at at the observation moment rather than applying a daily close, because intraday movement can exceed the price change you are measuring.

Local currency is always the primary field. Converted values are derived and labelled as derived.

Languages

The footprint spans Spanish, Italian, Portuguese, Polish, Romanian, Ukrainian, Georgian, Kazakh and several others. Product and item names are retained exactly as published, in their original script.

We do not machine-translate into the name field. Matching runs on identifiers, normalised attributes and image hashes rather than title similarity, which fails badly across a language set this wide.

Scope

What we collect on Glovo, 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

Listings with country, city and vertical on every record
verticals_observed recorded per country and city, per batch
price_setter and surface distinguishing partner listings from Glovo's own stores
Local currency primary, with FX rate and timestamp per observation
Modifier groups for restaurant items, with minimum realisable price
Pack parsed for grocery, with unit price on a stated basis
Delivery and service fees as separate fields
Local-language names retained exactly as published
Courier category recorded as a service, not counted as products

❌ What we do not, and why

A global category structure assumed across all markets
A blended price across partner listings and Glovo's own stores
A converted price presented as the primary value
Machine translation written into name fields
Sales, order volumes or merchant revenue

Core Glovo fields

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

Field	What it is on this platform
country / city / vertical	Geography and category, on every record
verticals_observed	What was actually live in this market, per batch
merchant_id / merchant_name	Partner merchant, a commercial entity
surface / price_setter	partner or glovo_store, and who sets the price
price_local / currency	Primary value, always
fx_rate / fx_observed_at	Stamped at the observation moment
modifier_groups / min_realisable_price	Restaurant items, with the basis stated
pack_size / pack_unit / price_per_unit	Grocery items, parsed
delivery_fee / service_fee	Separate from item price
item_name_local / script_dominant	Original text and its script
observed_at	Timestamp

Use cases

What teams do with Glovo data

Multi-market positioning across very different maturities

Country and vertical on every record with verticals_observed per market, so a mature European market and an emerging African one are analysed separately rather than averaged into a figure describing neither.

Own-store versus partner pricing

price_setter recorded, so where Glovo runs its own stores its pricing against partner merchants is visible as a deliberate comparison.

Vertical rollout tracking

verticals_observed over time, showing where pharmacy, grocery or own-store quick commerce have gone live in a market before any announcement.

Emerging-market entry evidence

Assortment depth and price levels in markets where quick commerce is new, which is the evidence a brand needs before committing to a channel that may still be forming.

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

Send us a Glovo 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.

Glovo is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Glovo 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 food & restaurant data covers, and a Glovo-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

Glovo data scraping: frequently asked questions

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

Because Glovo's category structure is not uniform. Pharmacy is live in some markets and not others; own-store quick commerce exists in some cities only.

Without that field an absent vertical looks like an absence of merchants, which reads as a market opportunity that does not exist. We record it per country and city in every batch.

For its own stores, yes. For partner merchant listings, the merchant does — and those frequently sit above the merchant's own in-store price because they are covering commission.

We record price_setter and never blend the two, because a movement in a blended series could be either party's decision.

Not as products, because there is no catalogue — the customer describes what they want fetched. We record the service's availability and pricing structure where published.

Including it in a product count would inflate coverage figures with something that has no products in it.

Names are retained exactly as published, in their original script, with the dominant script recorded. Matching runs on identifiers, normalised attributes and image hashes.

Title-similarity matching fails badly across a language set this wide, and machine translation into the name field makes an original indistinguishable from a translation within weeks.

Because the footprint includes several volatile currencies, and intraday movement can exceed the price change you are trying to measure. A price that looks like it moved may only reflect the rate you applied.

Local currency is always primary; converted values are derived and labelled as derived.

We quote individually. Country count is the dominant driver here rather than SKU count, because each market's category structure, language and currency handling needs its own treatment.

One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Glovo 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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