The Client

A product-research and analytics platform serving importers, private-label sellers, and sourcing teams — the businesses whose entire margin depends on finding the right product, from the right supplier, at the right wholesale terms. Their users lived on Alibaba's B2B marketplace, the world's largest wholesale sourcing platform, but they were doing it the slow way: manually opening listings, copying prices and minimum-order quantities into spreadsheets, and trying to compare suppliers by hand across thousands of products. The client wanted to give them a data-driven product instead — searchable, comparable, trend-aware sourcing intelligence — and for that they needed reliable, structured, programmatic access to Alibaba B2B product data. They came to Actowiz Solutions to be that data layer, delivered as a clean API their platform could build on.

The Challenge

B2B wholesale product data is a distinct problem from consumer e-commerce, and it carries specifics that make or break a sourcing platform:

MOQ and tiered pricing are the heart of B2B. Unlike consumer retail's single price, wholesale pricing is a structure: a minimum order quantity, and price tiers that drop as volume rises (100 units at one price, 1,000 at another, 10,000 at another). For a sourcing platform, this is the data — a product's true competitiveness lives in its MOQ and price-break curve, not a headline number. Capturing this structure completely and accurately is the core requirement.
Supplier information is half the decision. In B2B sourcing, you're choosing a supplier as much as a product — so supplier attributes (type, response indicators, verification/trade-assurance signals, years active, public transaction indicators, ratings) matter enormously and must be captured and linked to products. A product-research platform that shows products without supplier context is showing half the picture.
The field set is broad and technical. A useful record spans product title, price structure (MOQ + tiers), supplier information, ratings, reviews, order/transaction indicators, images, specifications, and shipping details — a wide, varied schema that has to be extracted consistently across an enormous and diverse catalogue.
Product research needs history. The client's product promised trend awareness — is this category's wholesale pricing rising or falling, is this product gaining traction — which requires historical pricing and trend data accrued over time, not just a current snapshot. Point-in-time history had to be built from day one.
Delivery had to be API-shaped and developer-ready. The client wasn't buying a file drop; they were building a platform on top of the data. That meant a real REST API with clean structured responses, documentation, sample payloads, sensible update frequency, defined rate limits, and the reliability a production product depends on — the questions any serious data buyer asks upfront, and rightly.
And it had to be compliant. Public B2B catalogue and supplier-listing data only — no personal data, no gated systems — with the documented posture enterprise buyers require.

The Actowiz Solution

1. The full B2B field schema.

Extraction across the complete set of fields a sourcing platform needs: product title, category, specifications, images, the full MOQ-and-tiered-price structure, supplier information (type, verification/trade-assurance signals, response and transaction indicators, ratings, years active), product ratings and review summaries, order/transaction indicators, and shipping details — resolved into one consistent, structured schema across the diverse catalogue.

2. MOQ and price-tier capture as first-class data.

The wholesale price structure — minimum order quantity and every published price break — captured as structured, queryable data (not flattened to a single price), because this is the field the client's sourcing analytics are actually built on. Price-per-unit computed at each tier for genuine comparability.

3. Supplier linkage.

Supplier attributes captured and linked to their products, so the client's platform could offer supplier-level as well as product-level research — filtering and comparing by supplier verification signals, ratings, and track-record indicators, the way real sourcing decisions are made.

4. Historical pricing and trend data.

Every observation landed in an append-only, point-in-time archive from the first day, building the price-history and trend layer the client's product promised — so users could see wholesale pricing direction over time, not just today's number.

5. A real REST API, developer-first.

Delivery as a documented REST API with clean JSON responses, sample payloads, filtering and pagination, defined and published rate limits, and change-since semantics for efficient syncing — the developer-ready interface a platform builds on, with the documentation and sandbox access serious buyers evaluate before committing.

6. Freshness tiering.

Update frequency matched to field volatility — pricing and availability refreshed faster, static specifications and supplier metadata on a slower cadence — the delta-based economics from our pipeline work, keeping the feed both fresh where it matters and efficient where it doesn't.

7. Reliability and support.

Self-healing extraction infrastructure keeping the feed dependable across a large, dynamic marketplace; health monitoring; and the technical support a production data partnership requires — because a platform running on the API needs it not to break, and needs a responsive partner when questions arise.

8. Compliance.

Public B2B catalogue and supplier-listing data only; no personal data; respectful pacing; per-record lineage; documented provenance for the client's own diligence — the standing posture from our compliance framework.

Sample Structure (Illustrative)

B2B product record (sample, abbreviated):

{
  "product_id": "alb-sample-77412",
  "title": "Sample Stainless Steel Water Bottle 750ml",
  "category": "Drinkware",
  "moq": 500,
  "price_tiers": [
    {"min_qty": 500, "unit_price": 2.80},
    {"min_qty": 2000, "unit_price": 2.35},
    {"min_qty": 10000, "unit_price": 1.95}
  ],
  "supplier": {
    "id": "sup-3391", "type": "verified_type",
    "years_active": 7, "response_indicator": "high",
    "rating": 4.6, "trade_assurance": true
  },
  "specs": {"material": "304 stainless steel", "capacity_ml": 750},
  "images_count": 9,
  "shipping": {"port": "sample_port", "lead_time_days_band": "15-30"},
  "order_indicator_band": "high",
  "captured_at": "2026-08-11T05:00:00Z",
  "lineage_id": "lin-7781-b2b"
}

API response summary (sample):

Attribute	Detail*
Interface	REST, JSON, documented
Filtering	Category, MOQ, price tier, supplier signals
Pagination / sync	Cursor + change-since
Update frequency	Tiered (price fast / static slow)
Rate limits	Published, plan-based
History	Point-in-time from day one
Sandbox	Available for evaluation

Sample data — illustrative of deliverable and API structure.

Engagement Metrics (Representative)

Metric	Value*
Scope	Public Alibaba B2B catalogue + supplier listings
Field set	Title, MOQ, price tiers, supplier, specs, ratings, reviews, images, shipping
Price structure	Full MOQ + tier curve, per-unit at each tier
History	Point-in-time archive from day one
Delivery	Documented REST API, sandbox, defined rate limits
Freshness	Tiered by field volatility
Personal data	None (by scope and policy)
Time to first API access	5 weeks

Representative engagement figures — illustrative of project structure.

The Outcome

The client launched their product-research platform on the API and gave their users what manual sourcing could never provide: searchable, comparable, trend-aware wholesale intelligence across a catalogue too large to work by hand. The MOQ-and-tier capture was the transformation — turning a spreadsheet of copied prices into a queryable price-break structure their users could filter and compare, finding the products and order volumes where the economics actually worked. The supplier linkage let users research the supplier and the product together, the way sourcing decisions are really made. And the historical layer delivered the trend awareness the product was built to promise — wholesale pricing direction over time, not just a snapshot.

Two things mattered as much as the data itself. First, the developer-first delivery — a documented REST API with a sandbox, clean responses, defined rate limits, and change-since syncing — meant the client's engineers could build confidently and fast, rather than wrestling a brittle feed. The questions their team asked upfront (fields, format, frequency, rate limits, history, sandbox, support) were exactly the right ones, and the engagement was structured to answer them concretely, because a data partnership a platform runs on lives or dies on those specifics. Second, the point-in-time history from day one meant the trend features worked at launch rather than a year later — the discipline of archiving from the start being one that can't be retrofitted.

The engagement runs as an ongoing data partnership — the reliability, support, and expanding coverage a production platform depends on — with the client's product growing on a foundation built to be built upon.

Why This Pattern Repeats

Product-research and sourcing platforms everywhere are built on the same foundation: structured, reliable, historical B2B product and supplier data, delivered as an API a platform can build on. The transferable design: the full wholesale field set with MOQ and price tiers as first-class structured data, supplier attributes linked to products, point-in-time history from day one, a documented developer-first REST API with defined rate limits and a sandbox, freshness tiered by volatility, reliability infrastructure and real support, and public-scope compliance. In B2B sourcing, the price break curve and the supplier signals are the product — and delivering them as clean, historical, developer-ready data is what a sourcing platform needs to exist.

Frequently Asked Questions

What B2B product data fields are available?

The full sourcing set: product title, category, specifications, images, the MOQ and tiered-price structure, supplier information (type, verification/trade-assurance signals, ratings, response and transaction indicators, years active), product ratings and reviews, order indicators, and shipping details — in one consistent schema.

Is the data delivered through a REST API?

Yes — a documented REST API with clean JSON responses, filtering and pagination, change-since syncing, defined published rate limits, and sandbox access for evaluation, built for platforms to develop on.

Is historical pricing and trend data available?

Yes — every observation lands in a point-in-time archive from day one, so wholesale price history and trend analysis work from launch rather than accruing only after the fact.

How frequently is the data updated, and what about rate limits and support?

Update frequency is tiered by field volatility (pricing faster, static data slower); rate limits are defined and plan-based; and technical support is included as part of a production data partnership. Contact Actowiz Solutions for documentation, a sandbox, and pricing options (subscription, usage-based, or custom).

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner