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Trust & Company
Scalable web, app and AI-powered collection across 40+ countries.
All 58 services →Repricing driven by competitor moves rather than a weekly review.
Explore → Pricing & Promotions
Brand & Intelligence
Digital Shelf & Search
Assortment For RetailersWhich solution fits?
Talk to ExpertSources we already run pipelines against. Download a real sample from any of them.
Browse coverage →Talabat, Careem Quik and Noon Minutes across 18 GCC cities.
Launch Demo →Tesco, Sainsbury's, Asda, Morrisons and Aldi, daily.
Get Early Access → E-Commerce Dashboard
Flipkart Insights (Live) #1
Grocery Intelligence
Grocery Price (U.S.)
Quick Commerce (India) HOT
Food & Restaurant
Fashion Intelligence
Automotive
Travel & Hospitality
Real Estate
Food Delivery Intelligence NEW
OTT & Streaming NEW
By Use Case
Pricing Intelligence
Digital Shelf Analytics
MAP Monitoring HOT
Cross-Border Price Parity NEW
Share of Search
Review Sentiment
Kitchen Market Gaps NEW
Dynamic Pricing / AI Repricing NEW
Promotions & Deals Alerts NEW
B2B / POI & Lead Data NEW
By Region Flipkart Real-Time Insights
Quick Commerce — Zepto · Blinkit
Pincode Price Tracker
GCC Q-Commerce — Talabat · Noon NEW
UK Grocery — Tesco, Sainsbury's, Asda
AU Grocery — Coles & Woolworths NEW
Marketplace Scrapers
Developer APIs Universal APIs Delivery & SDKsFixed monthly retainer, named engineer, no per-request metering.
Managed Data API → Knowledge Center
Guides & Playbooks
Downloads & Tools
Trust & CompanyThe Gulf problem is that there is no unit to inherit. The European problem is subtler: there is one, it looks right, and using it produces errors that are invisible because the geography seems solid.
The Gulf problem is that there is no unit to inherit. The European problem is subtler: there is one, it looks right, and using it produces errors that are invisible because the geography seems solid.
Free pilot on your own sources, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.
Last verified 5 August 2026 by the Actowiz Solutions Data Engineering team.
European postcodes are precise, stable and universally understood. That is exactly what makes them dangerous as a panel unit: a postcode-based geography looks solid, so nobody checks it.
In the Gulf there is no unit, so everyone knows the geography has to be defined. In Europe there is one, it is credible, and a dataset built on it carries errors that look like market variation.
A serviceability series at postcode level will show flicker — served one week, not the next — that is the vendor's sampling address moving, not the network changing.
Panels are built on addresses with coordinates. postcode_label travels on every record because
it is genuinely useful for joining to other datasets, and postcode_is_panel_unit is
false so nothing downstream mistakes the label for the geography.
Two are shared with other regions. Four are specific to here.
The core correction.
In the same city, from the same retailers.
Not assumptions to carry across borders.
Large in European grocery.
The question procurement will ask.
Shared with every region, and still skipped.
A managed engagement, not a tool licence. We own the pipeline and everything that breaks in it.
Geographic and regulatory fields. Product fields sit on the platform pages.
| Field | Type | What it captures | Refresh |
|---|---|---|---|
country / city |
string | Country drives the rules, not just the currency | Every record |
address_id |
string | The panel point. The actual unit | Every record |
postcode_label |
string | Retained for joining, not used as the unit | Every record |
postcode_is_panel_unit |
constant | Always false. Stated so the label is not mistaken for geography | Every record |
catchment_type |
string | Inner-city dense, student, suburban, peri-urban | Every record |
surface |
string | rapid or scheduled. Two different geographies | Every record |
hub_id / site_id |
string | Where the platform exposes it | Where exposed |
serviceable / slot_available |
boolean | Independent states on scheduled surfaces | Every record |
deposit_amount / deposit_type |
number / string | Where the market operates a scheme | Where applicable |
price_per_unit / displayed_unit_price / unit_price_matches |
number / boolean | Ours, theirs, and whether they agree | Where parseable |
panel_version / panel_entered_at |
string / date | So a series can be filtered to stable points | Every record |
unit_price_matches exists because several European markets mandate a displayed unit price. Where our computed value disagrees with the displayed one, that is usually a listing error the retailer would want to know about, and it is worth surfacing rather than silently preferring one.
Rapid and scheduled both, and they are not the same panel.
The last one has been unusually informative in Europe over the past few years. Rapid networks have contracted sharply, and serviceability across a fixed address panel shows a network withdrawing before any announcement — provided the panel did not move. Request a source we don't list →
We deliver into 40+ countries. These are the markets where this particular service is requested most, and the reason demand concentrates there.
| Market | Why demand concentrates here |
|---|
We run production collection across 40+ countries. Coverage depth varies by market and by source, so we confirm what is actually available for your specific markets during scoping rather than claiming uniform global coverage. Ask about a market we don't list →
Mostly people whose geography looked fine until someone checked it.
A postcode-level price index that flickers is measuring the vendor, not the market.
Address panels with the postcode kept as a label rather than the unit.
Index stability
Rapid and scheduled serve different areas and are frequently blended.
surface on every record, so the two geographies stay separate.
Channel clarity
Deposit schemes and VAT differ enough to break a cross-border comparison.
Deposits as their own field and country rules stated rather than assumed.
Cross-border validity
Private label is a large share of basket and does not cross-match.
Flagged unmatched rather than paired on name similarity.
Index honesty
Will ask whether an address panel is personal data.
A delivery location is not a person, and we collect no personal data anywhere.
Review clearance
Inherits a panel and has to defend it.
panel_version and entry dates, so a series can be filtered to stable points.
Series integrity
Including one thing that has been unusually valuable recently.
A fixed address panel observed over time shows a rapid network withdrawing from areas before any announcement — which has been a recurring event in European rapid grocery.
Outcome: Early sight of a competitor retreating.
Both surfaces on the same addresses with surface recorded, so the range and price difference between a retailer's two channels is a first-class analysis rather than a blend.
Outcome: A comparison few retailers can run on themselves.
Container deposits as their own field, so a German beverage price is comparable to a non-deposit market without a systematic category-wide error.
Outcome: A cross-border index that is not quietly wrong on a whole category.
Our computed unit price against the mandated displayed one, with disagreements flagged — usually a listing error a retailer wants to know about.
Outcome: A finding the retailer cannot easily get themselves.
Clients rarely permit naming. These are real engagement shapes with identifying detail removed, so you can judge whether the work resembles your situation.
Examples are anonymised at client request. Named references are available on request under NDA. See published case studies →
Before you commit to anything, we run this service against your own sources and send you the output. If the coverage isn't there, the sample will show you that too — which is the point. We would rather lose the deal at the pilot than at month three.
Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.
We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.
Best fit: Teams who need the data, not the infrastructure.
The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.
Best fit: Product and engineering teams building on live data.
A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.
Best fit: Research, strategy and diligence work with a deadline.
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.
Almost everyone starts with the first. It is worth understanding what it costs.
| Consideration | In-house scraping team | Generic proxy / DIY tool | Actowiz managed feed |
|---|---|---|---|
| Time to first usable data | 6–12 weeks of engineering before anything is trustworthy | Days, but output needs manual cleanup before use | Free pilot in 24 hours, production in 5–10 business days |
| Who fixes it when a source changes | Your engineers, at the cost of their roadmap | You do — tools report failures, they don't resolve them | We do, same business day, inside the retainer |
| Data quality assurance | Whatever your team has time to build | None beyond HTTP success | Schema validation plus sampled human QA on every run |
| Compliance documentation | Rarely produced, then requested urgently by legal | Not provided; terms risk sits with you | Sources, method and lawful basis documented for review |
| Accountability | Distributed across a team with other priorities | A support ticket queue | A named engineer and an account owner |
| True annual cost | Engineer salaries, proxies, hosting, ongoing maintenance | Low licence fee plus significant hidden analyst time | One fixed monthly retainer, quoted after scoping |
A European retailer frequently operates both a rapid service and a scheduled one. Those serve different areas from different facilities.
The sample on this page shows exactly that: one Berlin address unserved by rapid and served by scheduled. A panel that blends the two records the address as partially serviceable, which describes neither channel.
Range and price are not always identical between a retailer's two channels, and where they differ that is a deliberate commercial decision. Few retailers run this comparison on themselves, because internally the two channels sit in different teams with different systems.
A dataset that keeps surface on every record makes it available. One that blends them destroys it and
nothing in the output says so.
Cross-border European comparison breaks on three things, and none of them is currency.
Container deposit schemes operate in several markets. A German beverage at €4.99 plus €1.50 deposit is not a €6.49 product, deposit amounts differ by container type, and comparing to a non-deposit market without separating produces a systematic error across the whole category. Captured as its own field, never folded in.
VAT rates differ by country and, within a country, by product class — frequently with grocery staples at a reduced rate and prepared items at standard. A cross-border comparison on displayed prices is comparing different tax treatments. We record the displayed basis rather than adjusting, because adjusting requires assuming a classification we did not observe.
Several European markets mandate a displayed unit price. That is helpful and it is worth checking rather than
trusting. We compute unit price ourselves from parsed pack data and capture the displayed value, then flag
unit_price_matches where they disagree.
A disagreement is usually a listing error rather than a parsing failure, and for a retailer that is a finding worth having.
Mostly a conversation about catchment types and which surfaces are in scope.
Whether rapid, scheduled or both matters as much as which cities, because they are different geographies.
Addresses with coordinates, grouped by catchment type, with postcode labels retained for your other joins.
Real extraction, so you see serviceability and assortment variation within a postcode rather than being told about it.
Deposit schemes, VAT treatment and unit-pricing law per market, stated in the deliverable rather than assumed across borders.
Additions logged with entry dates, points never removed silently, so a month-on-month move is the market rather than the panel.
Geographic and regulatory fields travel with the product data in whatever format is agreed. The panel proposal is supplied as a document before quoting.
A postcode is a geographic area and an address panel point is a delivery location, neither of which is personal data. We collect no personal data in any market, and that exclusion predates GDPR rather than responding to it. A methodology document and DPA are supplied before signature.
These are contractual, not marketing copy. They appear in the engagement document.
| Commitment | What we hold ourselves to |
|---|---|
| Pilot turnaround | A real sample from your own sources within 24 hours of scoping, at no cost. |
| Go-live | Production collection running within 5–10 business days of sign-off. |
| Delivery punctuality | 99.5% on-schedule delivery, measured monthly and reported to you. |
| Breakage response | Source layout changes triaged same business day; critical sources inside 4 hours. |
| Data quality | Schema validation on every run plus sampled human QA before any delivery leaves us. |
| Escalation | A named engineer and an account owner, not a shared ticket queue. |
| Change requests | Field additions and source changes handled inside the retainer, not re-quoted. |
| Exit | Your historical data exported in full on request. No lock-in, no export fee. |
Plain definitions of the terms used on this page, so procurement and legal reviewers are working from the same vocabulary as your data team.
Starting with the one that surprises people.
They are, and that is what makes them dangerous here. Hub delivery radii are circles; postcodes are administrative shapes. A radius covers part of several postcodes, so part of a postcode is served and part is not.
A postcode-level serviceability flag is therefore true or false depending on which address happened to be tested, and a series built on it flickers in a way that looks like network change and is actually the vendor's sampling address moving.
Yes, as postcode_label on every record, because it is genuinely useful for joining to demographic and other datasets.
postcode_is_panel_unit is false so nothing downstream mistakes the label for the geography. Both things are true at once and it is worth being explicit about which is which.
Because they are two geographies in one city. Rapid serves tight hub radii; scheduled serves much wider areas from central warehouses. An address unserved by rapid is routinely served by scheduled — a channel difference, not a coverage gap.
Blending them records an address as partially serviceable, which describes neither channel. And the comparison between the two is a finding few retailers can run on themselves, because internally the channels sit in different teams.
Three things, none of them currency. Container deposits, which differ by container type and are refundable. VAT, which differs by country and by product class. And unit-pricing law, which is mandated in several markets.
Deposits are captured as their own field. VAT basis is recorded rather than adjusted, because adjusting requires assuming a classification we did not observe.
No. An address panel point is a delivery location used to observe what a platform offers there. It is not a person, no individual is associated with it, and we collect no personal data in any market.
That exclusion predates GDPR rather than responding to it, which is generally the more useful thing for a DPO to hear.
Matched within a retailer, flagged unmatched across retailers, and never paired on name similarity. Private-label lines have no shared identifier and no equivalent product elsewhere.
This matters more in European grocery than most regions because private label is a large share of basket — an index that quietly pairs it is measuring something other than what it claims.
We quote individually. Drivers are country count, addresses per city, SKU breadth and refresh frequency — country count matters most, because deposit schemes, VAT and unit-pricing rules need per-market handling.
One scoping call, a written panel proposal, a free pilot within 24 hours, then a fixed monthly quote. Request a panel proposal.
Tell us the cities, the catchment types and whether rapid, scheduled or both are in scope. We return a written proposal with what it represents and what it does not.
If your work genuinely needs postcode-level output for a demographic join, we will say so and design for that instead.Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
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