Capability · Product builders

Building a product on our data, not just using it

If your users will see the data, you are a different kind of buyer from the teams this site mostly speaks to. This page is for you, and it starts with the question that decides everything else.

If your end users will see the data, you are asking a different question from an internal-use buyer. The one that comes first is redistribution: whether you may display our records to your own customers. That is contractual, not technical, it varies by source, and we tell you which sources are redistributable before you quote, not after you build.

If your users will see the data, you are a different kind of buyer from the teams this site mostly speaks to. This page is for you, and it starts with the question that decides everything else.

Ask what is redistributable See sample data

Free pilot on your own sources, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

✓ Redistribution stated per source, before quoting✓ Schema deprecation policy in writing✓ Pricing that does not scale with your users

redistribution_classification.json LIVE FEED

// what you get before a quote, not after you build {"source": "example-retailer.example", "internal_use": true, "redistribution": "permitted_derived_only", "detail": "metrics and aggregates yes; raw records to end users no", "attribution_required": false} {"source": "example-marketplace.example", "internal_use": true, "redistribution": "permitted_full", "attribution_required": true, "attribution_text": "required near the displayed record"} {"source": "example-portal.example", "internal_use": true, "redistribution": "not_permitted", "reason": "source terms prohibit onward display", "alternative": "derived index, no underlying records"} // three answers, not two. "derived only" is the common one // and the one that most changes what you can build

issued before quoting · one entry per requested sourcethe document a product roadmap should be built on

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

Summary What it is What's included Schema Markets Who it's for Examples How we engage SLA FAQ

Written and reviewed by the Actowiz Solutions Data Engineering team Published 5 August 2026 Last updated 5 August 2026 Reading time 10 min

Key facts at a glance

The first question: Can your end users see it? That is redistribution
Three answers: Full, derived-only, or not permitted. Per source
When you find out: Before quoting. Not after your roadmap depends on it
Schema: Contract with a deprecation policy, because your product breaks if a field vanishes
Pricing: Does not scale with your user count. Your growth is not our meter
Attribution: Required on some sources. Stated, with the wording
Uptime: Targets agreed and stated, since your users see our outages as yours
Exit: Full historical export, no exit fee, schema documented

1question that decides what you can buildredistribution, answered per source

3redistribution outcomes per sourcefull, derived-only, not permitted

0pricing tied to your user countgrowth is not a billing event

24hfree pilot against your schemawire a prototype, not read a spec

Key takeaways

The first question: Can your end users see it? That is redistribution
Three answers: Full, derived-only, or not permitted. Per source
When you find out: Before quoting. Not after your roadmap depends on it
Schema: Contract with a deprecation policy, because your product breaks if a field vanishes
Pricing: Does not scale with your user count. Your growth is not our meter
Attribution: Required on some sources. Stated, with the wording

Last verified 5 August 2026 by the Actowiz Solutions Data Engineering team.

Definition

Why redistribution is a different question, and why it comes first

An internal-use buyer asks whether the data is accurate and fresh. You have to ask that too, plus one they never do: may our customers see it?

Three outcomes, not two

Permitted in full — you may display our records to your users, sometimes with attribution.
Permitted derived only — you may show metrics, indices and aggregates computed from the data, but not the underlying records. This is the most common answer and the one that most changes what you can build.
Not permitted — internal use only. You can still build on it, but nothing derived from that source reaches a screen your customer sees.

Why "derived only" matters more than it sounds

A price comparison app showing a competitor's price per product is displaying records. A price index showing "this category moved 4% this month" is displaying a derived metric. The first may not be permitted where the second is.

Those are different products. Finding that out in month five is expensive; finding it out before you quote costs nothing.

What we will not do

We will not tell you that a source is redistributable when it is not, and we will not leave it unstated so that the question lands on you later. Where the answer is not permitted, we say so and offer the derived-metric route if one exists.

We are also not your counsel. The classification tells you what we are willing to supply and on what basis; your own legal review of your product is yours.

What changes

Six things that differ when you are building a product

Every one of these is invisible to an internal-use buyer and load-bearing for you.

Redistribution rights

The question that decides what you can build.

Stated per source before any quote
Three outcomes: full, derived-only, not permitted
Attribution wording where required
Re-issued when a source's terms change

Schema as a contract

Your product breaks when a field moves.

Field names and types agreed in writing
Deprecation policy with a notice period
Additive changes by default; breaking changes versioned
Change log per release, not a surprise in a batch

Uptime and freshness targets

Your users experience our outages as yours.

Targets agreed rather than implied
Freshness stamped per record so you can degrade gracefully
Incident notification to you, not silence
Source repairs handled by us

Pricing that does not punish growth

Your user count is not our meter.

Fixed monthly retainer on data scope
Not per end user, not per API call your users make
Volume growth on your side does not change the invoice
So your unit economics stay predictable

White-label and attribution

What your users see, and what they must.

No Actowiz branding required in your product
Attribution only where a source requires it, with wording given
Your schema, your field names
We do not contact your customers

Exit that does not hold you hostage

Because you will be asked in diligence.

Full historical export on request
No exit fee, no export charge
Schema documented so a successor can be onboarded
Notice period stated in the agreement

Service scope

What the ecommerce data scraping service includes

A managed engagement, not a tool licence. We own the pipeline and everything that breaks in it.

✓ Included in every engagement

Redistribution classified per source, in writing, before quoting
Re-issued when a source's terms change
Schema contract with deprecation policy and notice period
Stated uptime and freshness targets, with incident notification
Pricing on data scope, never on your user or call count
White-label delivery with attribution only where a source requires it
Full historical export on exit, no fee
Source discovery, scoping and a written collection plan
Free pilot on your own sources before any commitment
Full pipeline build, hosting and proxy infrastructure
Schema design, validation and sampled human QA on every run
Ongoing maintenance when source layouts change — our cost, not yours
Delivery to your warehouse, bucket, SFTP or API endpoint
Documented methodology and compliance notes for your legal review

× Not included — stated upfront

Legal advice, or certification of your product's compliance
A redistribution assurance we are not willing to put in writing
Pricing that increases as your user base grows
Any requirement to display Actowiz branding
Contact with your customers, under any circumstance
Anything behind a login, paywall or credentialed session
Personal data beyond a documented lawful basis
Licensed third-party datasets we do not hold rights to
Guarantees about fields a source simply does not publish

Schema

The redistribution classification

A document, issued before quoting. It is the thing your roadmap should be built on.

Fields in the redistribution classification
Field	Type	What it captures	Refresh
`source`	string	The source you asked for, named	Per source
`internal_use`	boolean	Whether we can supply it for your own internal analysis	Per source
`redistribution`	string	permitted_full, permitted_derived_only or not_permitted	Per source
`detail`	string	What specifically may and may not reach an end user	Per source
`attribution_required`	boolean	Whether display requires attribution	Where permitted
`attribution_text`	string	The wording and placement required	Where required
`reason`	string	Why redistribution is restricted	Where restricted
`alternative`	string	The derived-metric route where records are not permitted	Where applicable
`review_trigger`	string	What would cause us to re-issue this classification	Per source
`issued_at`	timestamp	When assessed. Source terms change	Per document
`issued_before_quote`	constant	Always true	Per document

Source terms change. We re-issue the classification when they do, and tell you rather than continuing to supply on a basis that has moved.

Coverage

Products people have built on this

The shapes recur. If yours is here, the redistribution question has a known answer.

Price comparison appsAI shopping and discovery platformsRestaurant and menu intelligence toolsPOS integrations showing marketplace dataConsumer budgeting and finance appsGrocery and quick-commerce comparisonSocial listening and consumer intelligenceReal estate search and valuation toolsTravel fare prediction and alertingRetail media and ad intelligence dashboardsBrand protection and seller monitoring SaaSCategory and assortment planning toolsInvestor and market research platformsTaste and recommendation enginesOTT and entertainment discoveryLogistics and delivery comparison

If your product is not on this list it does not mean it is a problem. It means the redistribution question has not been assessed for your sources yet, which is a conversation rather than an obstacle. Request a source we don't list →

Markets served

Countries and markets where this service is in highest demand

We deliver into 40+ countries. These are the markets where this particular service is requested most, and the reason demand concentrates there.

Highest-demand markets for this service, and why demand concentrates there
Market	Why demand concentrates here

North America

United StatesCanadaMexico

United Kingdom & Ireland

United KingdomIreland

Western Europe

GermanyFranceNetherlandsBelgiumSpainItalySwitzerlandAustria

Nordics

SwedenNorwayDenmarkFinland

Middle East

United Arab EmiratesSaudi ArabiaQatarKuwaitIsrael

Asia Pacific

SingaporeAustraliaNew ZealandJapanSouth KoreaMalaysiaIndonesiaThailandVietnamPhilippines

South Asia

IndiaBangladeshSri LankaPakistan

LATAM

BrazilArgentinaChileColombia

Africa

Wants to know whether the data dependency is a risk or an asset.

What we deliver

Exit terms, full export, documented schema and a stated notice period.

Metric that moves

Dependency risk

Use cases

Four things builders use this for

Two commercial, two defensive.

Deciding what to build before building it

Redistribution classified per source before a quote, so a feature that depends on displaying records is not designed against a source where only derived metrics are permitted.

Outcome: A roadmap that survives contact with the licence.

Unit economics that hold as you grow

A fixed retainer on data scope rather than per end user or per call, so a tenfold increase in your users does not multiply your data cost.

Outcome: Margins that improve with scale instead of flattening.

Surviving a data incident without a product incident

Freshness stamped per record and a schema deprecation policy, so your product degrades gracefully rather than displaying stale data confidently or breaking on a field change.

Outcome: Failures that your users do not see.

Answering diligence about the dependency

A written classification, stated uptime targets, documented schema and exit terms with full export and no fee.

Outcome: A data dependency that reads as managed rather than fragile.

Engagement examples

Two engagements, anonymised

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 →

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

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.

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.

Build vs buy

Build the collection yourself, or partner?

For a product company the calculation is different from an internal-use buyer's, and usually goes the other way.

In-house build vs self-serve tool vs Actowiz managed service
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

Pricing that does not scale with your users, and why we do it that way

Most data vendors selling to product companies price per end user, per seat or per API call your users trigger. That means your success is a billing event.

We price on data scope — sources, records, refresh, geographies — and nothing else. If your user base grows tenfold and your data scope does not change, your invoice does not change.

Why we prefer it

Your unit economics stay modelable. A cost that moves with users is one you cannot forecast.
We have no interest in your call volume, so we never have a reason to encourage inefficient integration.
Renewal conversations are about the data, not about how well you did last year.

The honest counterpoint

If your product is small and your data scope is broad, per-user pricing would be cheaper for you than ours. We will say so rather than quoting. A ready-made dataset or a narrower scope may serve you better at that stage, and taking a retainer you will resent in month four is not a good trade for either of us.

Schema stability is the thing that breaks products, and it is rarely discussed

Accuracy gets all the attention in vendor evaluation. For a product company the more dangerous failure is a field that changes shape.

A field renamed breaks a parser silently in production.
A type changed from string to number breaks a client that was tolerant of one and not the other.
A field removed takes a feature with it, usually discovered by a user.

What we commit to

Additive by default. New fields appear; existing ones do not move.
Breaking changes are versioned, with both versions available during a stated overlap.
A deprecation notice period agreed in the contract, not decided when it happens.
A change log per release, so a change is something you read rather than something you discover.

This is the commitment most worth interrogating when you compare suppliers. Ask each one what happens when a source adds a field, and what happens when they decide to rename one. The answers vary enormously and almost nobody volunteers them.

How it works

How a data partnership starts

The redistribution answer comes before the quote, which is the point.

Tell us what your product does with the data

Not just which sources. Whether end users see raw records, derived metrics or neither changes the licence, and it is the first thing we need to know.

We tell you what is redistributable, per source

Before a quote. Some sources we can supply for internal use and not for redistribution, and you should know which before you build a roadmap on them.

Free pilot within 24 hours

Real records against your own schema, so you can wire a prototype rather than read a specification.

Agree the schema contract

Field names, types and a deprecation policy in writing. If your product breaks when a field changes, that policy is the thing that protects you.

Production in 5 to 10 business days

With uptime and freshness targets stated, and source repairs handled by us rather than reported to you.

Formats & destinations

JSON, JSONL, Parquet or CSV to your own storage, or a REST endpoint. Your field names and types, agreed in the schema contract.

Compliance & data ethics

We collect only publicly accessible information and never collect personal data. Redistribution is classified per source in writing before quoting and re-issued when source terms change. We do not certify your product's compliance, which depends on your use and jurisdiction.

Service commitments

What we commit to, in writing

These are contractual, not marketing copy. They appear in the engagement document.

Service level commitments written into every managed engagement
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.

Why teams pick Actowiz for this work

Engineers, not a dashboard. You get people who fix breakages, not a self-serve tool you maintain yourself.
We tell you what we can't do. Scope limits and coverage gaps are stated before you sign, not discovered in month three.
QA is part of the service. Schema validation and sampled human review run before delivery, every run.
Compliance is documented. Sources, method and lawful basis written down so your legal team can review them.
Fixed monthly cost. No per-request metering, no surprise overage on a month when a competitor adds SKUs.
Six years, 40+ countries. Long-running production pipelines across retail, travel, mobility and finance.

Definitions

Terms used on this page

Plain definitions of the terms used on this page, so procurement and legal reviewers are working from the same vocabulary as your data team.

FAQ

Product builders: frequently asked questions

Starting with the one that decides everything else.

It depends on the source, and we tell you which before quoting rather than after you build. There are three answers: permitted in full, permitted for derived metrics only, or not permitted.

Derived-only is the most common, and it is the one that most changes what you can build — a comparison app showing per-product competitor prices is displaying records; an index showing a category moved 4% is not.

We re-issue the classification and tell you. We do not continue supplying on a basis that has moved and leave you to discover it.

Where a source becomes restricted we will say so and offer the derived-metric route if one exists. That may change your product, which is exactly why you should hear it from us immediately rather than from the source's legal team later.

No. Pricing is a fixed retainer on data scope — sources, records, refresh, geographies. If your user base grows tenfold and your scope does not change, your invoice does not change.

The honest counterpoint: if your product is small and your scope is broad, per-user pricing elsewhere would be cheaper. We will tell you that rather than quoting.

Additive by default — new fields appear, existing ones do not move. Breaking changes are versioned with both available during a stated overlap, and there is a deprecation notice period agreed in the contract rather than decided when it happens.

This is the commitment most worth interrogating across suppliers. Ask each what happens when they rename a field.

Not to us. Some sources require attribution as a condition of display, and where that applies we give you the wording and the placement requirement in the classification.

Otherwise it is your product, your branding, your field names. We do not require a badge and we do not contact your customers.

Targets are agreed and written rather than implied, because your users experience our outages as yours. Freshness is stamped per record so your product can degrade gracefully instead of displaying stale data confidently.

Source repairs are handled by us and you are notified of incidents rather than left to infer them from a gap in the data.

Full historical export on request, no exit fee, no export charge, and the schema documented so a successor can be onboarded. The notice period is in the agreement.

We put this in writing because your investors will ask, and a vendor who makes leaving expensive is a dependency risk rather than a partner.

Often, with a narrow scope. A tight source list at a low refresh is inexpensive and enough to build and demonstrate a product.

What we would rather not do is take a broad retainer from a pre-revenue company that will strain it. If a ready-made dataset gets you to a demo faster and cheaper, we will point you there.

We quote individually on data scope. Drivers are the same as any engagement — sources, records, refresh, geographies — and explicitly not your user count.

One scoping call, a written redistribution classification before the quote, a free pilot within 24 hours against your own schema, then a fixed monthly quote. Ask what is redistributable.

Ask what is redistributable before you build

Send your source list and what your product does with the data. You get a written classification per source before any quote.

Ask what is redistributable Book a 20-min scoping call

If the answer is not permitted on a source your roadmap depends on, that is worth knowing this week rather than in month five.

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