Platform · Keeta

Keeta Data Scraping

Keeta prices by store, and where menus are bilingual, translating them would break a join.

Keeta data scraping collects store listings, menus, prices, fees and availability from Keeta in <COUNTRIES – confirm with R&D>. Two things shape the work: store-level collection, because the same brand prices differently by branch, and bilingual menus where Arabic and English coexist and neither should be overwritten by a translation.

We collect store listings, menus, prices, fees and availability from Keeta in <COUNTRIES – confirm with R&D>.

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keeta_menus.jsonl LIVE FEED

{"store_id":"...","brand_id":"...", "city":"city-a","area":"area-1", "item_name_ar":"...", "item_name_en":"...", "item_price":25.00,"currency":"XXX", "modifier_groups":[{"name":"Size","is_required":true, "options":[{"label":"Regular","price":8.00}]}], "min_realisable_price":33.00, "price_basis":"item + cheapest required modifiers", "delivery_fee":"..."} {"store_id":"...","brand_id":"...", "area":"area-2","item_price":"...", "min_realisable_price":"...", "note":"same brand, different branch price"} {"store_id":"...", "serviceable":false, "store_open":true, "caution":"area not served — store is not closed"}

3 of 1,884,110 store-item rows stores: 4,120store level, both scripts retained · schema v1.0

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Keeta at a glance

How we handle Keeta specifically

This approach is built for this platform, not a reused retail template.

Platform: Keeta — food and quick delivery
Unit of collection: Store, because chains price by branch
Language: Both scripts kept as published, neither translated
Menu structure: Items and modifier options priced separately
Fees: Delivery, service and small-order fees kept apart
Promotions: Platform-funded and merchant-funded separated
Coverage: Area serviceability distinguished from a closed store
Refresh: Agreed schedule

Platform specifics

What is specific to Keeta delivery data

Why Keeta needs its own handling.

Store-level, because brand-level averages a chain that does not price as one

Franchise ownership, rent and local rivals mean a chain frequently runs different prices at different branches in the same city.

A brand-level average is a price no branch charges.
An item missing from one branch is not removed chain-wide.
Franchise and company stores differ on promotions, and the platform does not always show which is which.

Every record carries store_id and area, with brand_id for optional rollups. See also our Carrefour page.

Arabic and English in one menu, and why we do not translate

Bilingual menus mix scripts: sometimes the name and description are split by language, sometimes both appear on one line.

What we do

Keep both scripts as published, in separate fields where the platform separates them.
Record the dominant script.
Match items on structure, price and position, not on name.

What we do not do

We do not machine-translate into the item name. If you want a translation, it goes in a separate field that records the engine and date.

Modifiers are where the real price lives

The headline price is often not what a customer pays. Modifiers carry their own prices and required/optional rules. For example, an item listed at 25 with a required size option starting at +8 costs 33 at entry.

Whether a modifier is required or optional decides whether it can be avoided.
Modifier availability varies by store.

We deliver modifiers as structured records with is_required, option prices and min/max selections. min_realisable_price is the item plus its cheapest required modifiers, with the basis stated.

A headline-only feed gives a figure no customer pays.

Scope

What we collect on Keeta, 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

Store-level pricing with store_id and area
brand_id alongside, as an optional rollup
Item names in both scripts, dominant script noted
Modifier groups with required flags and option prices
min_realisable_price with a stated basis
Delivery, service and small-order fees as separate fields
Platform and merchant promotions kept apart
Serviceability by area, distinct from closed status
Rating and review counts, no reviewer identities

❌ What we do not, and why

Machine translation in the item name field
Sales, order volumes or revenue (not published)
Rider, customer or order data
Brand-level prices that average branches
Anything behind sign-in

Core Keeta fields

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

Field	What it is on this platform
platform / country / city	Service and location
store_id / brand_id	Store level, with optional brand rollup
area / serviceable	Delivery area and whether it is served
item_id / item_name_ar / item_name_en	Item in both scripts
script_dominant	Dominant script flag
item_price / currency	Headline price
modifier_groups	Required flags, min/max, option prices
min_realisable_price / price_basis	Cheapest realisable price and its basis
delivery_fee / service_fee / small_order_fee	Separate fee fields
promo_type / promo_funder	Who funds the promotion
store_open / observed_at	Closed state, separate from unserviceable

Use cases

What teams do with Keeta data

Competitive menu pricing at branch level

See the branch-level price spread across a city through min realisable price, not a single average.

Market entry pricing

Compare item and modifier pricing across brands and areas to inform menu pricing in a new market.

Promotional intensity by funder

Track platform-funded and merchant-funded promotions separately, as distinct signals.

Delivery fee competitiveness

Track fees by area as their own series, because they often move independently of menu prices.

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

Send a Keeta item or category list. We run collection on it and return output with platform fields filled in.

Real extraction
Turnaround target: 24 hours
Coverage and QA note
You keep the data regardless
No card, no trial clock
A named engineer

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

Engagement

Three ways to engage us

The same collection and QA pipeline sits underneath all three. The difference is who runs the schedule and how data is delivered.

Managed service (most common)

A dedicated engineer, site changes fixed by us, scheduled delivery to your warehouse or S3, and a named contact. Best for teams that want data, not infrastructure.

API access

Scheduled delivery endpoints for collected data, rate limits set to your load, sandbox keys, and a versioned schema with deprecation notice. Best for product and engineering teams.

One-time or project extraction

A fixed written scope, a single delivery with a QA report, documented methodology, and the option to convert to managed. Best for deadline-driven research.

Pricing

Quoted per engagement based on scope: a free pilot first, then a fixed monthly figure with no per-request or overage charges.

Request a quote

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

REST endpoints on the same pipeline, with sandbox keys for testing.

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 fixed-scope extraction for a single project or research question.

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

Pricing is quoted individually, based on category scope, number of markets, cadence and ongoing identity maintenance. After a scoping call and free pilot, we quote a fixed monthly figure, with no per-request metering.

Book a 20-min scoping call Request a quote Talk to an engineer

Keeta is usually collected alongside its competitors

Keeta data is most useful next to competitor data on one schema and schedule. See our food and restaurant data service and consider scoping several platforms at once.

That is what food & restaurant data covers, and a Keeta-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

Keeta data scraping: frequently asked questions

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

Branches price differently, so a brand average matches no branch. We record store_id and area, with brand_id as an optional rollup.

Not into the name field. Both scripts are kept, and a translation can be added as a separate field on request.

Headline prices understate what customers pay. Modifier data includes required flags and a minimum realisable price with its basis.

No. Volumes are not published and proxies such as ranking are weak, so we deliver only what is observable.

Talabat and Keeta can be collected on a shared schema where both are in scope.

It is quoted individually based on markets, stores, menu depth and refresh rate: a pilot first, then a fixed monthly quote.

See real Keeta data before you commit to anything

Send an item or category list and receive output with platform fields filled in.

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Free pilot, no card, no obligation. If a field you need is not available, the sample will show it.

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