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Fuse for e-commerce · B2B and B2C

Liberate your data,
keep it ready for business

Governed, standardised and usable by every team and system.

Supplier files, APIs and system extracts arrive in different shapes, languages and levels of detail. Fuse reconciles them on the business key you map, settles the conflicts on your rules, and checks each channel's requirements before the feed leaves.

Where Fuse sits

Between what you receive and what you publish

Supplier files and system extracts on one side. The shop, the marketplaces, the distributors and your sales teams on the other.

Fuse is the quality layer in between. It reconciles the sources on the business key you map, controls the result against your rules, and hands each destination the payload it expects.

Between what you receive and what you publish Sources: Supplier A, Supplier B, ERP extract, PIM extract, WMS feed. They converge on Fuse. Reconcile · Control · Enrich. Fuse keeps them as Golden records: Governed · Traceable · Up to date. Fuse then publishes to E-commerce site, Marketplaces, B2B distributors, Sales teams. Supplier A Excel, sent weekly Supplier B CSV over an API ERP extract Price and stock PIM extract Attributes and copy WMS feed Availability quality layer Fuse Reconcile · Control · Enrich Golden records Governed · Traceable · Up to date E-commerce site Long copy, public price Marketplaces Mandatory attributes B2B distributors Contract price, documents Sales teams Pitch and customer terms Between what you receive and what you publish Sources: Supplier A, Supplier B, ERP extract, PIM extract, WMS feed. They converge on Fuse. Reconcile · Control · Enrich. Fuse keeps them as Golden records: Governed · Traceable · Up to date. Fuse then publishes to E-commerce site, Marketplaces, B2B distributors, Sales teams. Supplier A Excel, sent weekly Supplier B CSV over an API ERP extract Price and stock PIM extract Attributes and copy WMS feed Availability quality layer Fuse Reconcile · Control · Enrich Golden records Governed · Traceable · Up to date E-commerce site Long copy, public price Marketplaces Mandatory attributes B2B distributors Contract price, documents Sales teams Pitch and customer terms

E-commerce daily problem

The consequences of an incorrect product catalog

Selling at a loss? Illegal. Selling at the wrong price? Frustrating. Shipping the wrong product? Infuriating. Not selling at all because of bad data? No way.

An easy-to-use, effective tool that learns from your decisions.

Errors surface when a product goes live, when a customer orders, when a marketplace rejects a feed or when a salesperson finds that two systems say different things. By then the cost is already commercial.

Product health

Ergonomic office chair

CHAIR-458 GTIN 05400123456789

2/8 fields ready

  • reference CHAIR-458 Ready Matched across all four sources.
  • gtin 05400123456789 Ready Checksum valid.
  • description 48 characters Review Too short for the marketplace minimum of 300.
  • material not set Review Attribute missing. Required by two channels.
  • price 129 EUR / 134 EUR Blocking Two sources disagree. ERP and Supplier B are 5 EUR apart.
  • availability Last seen 14 days ago Blocking Stale. The freshness rule allows 24 hours.
  • image_url v2 asset Review Points at the superseded product version.
  • lead_time not set Review Absent. Blocks the B2B distributor feed.

The shift

Many sources. One trusted record. Ready to publish.

Fuse matches rows on the business key you choose, highlights where sources disagree, and applies the priority rules your business has defined.

The result is not just standardised data. It is data you can trust: for every record, you can see where it came from, what changed, and whether it is validated.

Before Four systems, four dialects

  • Supplier A

    Excel, weekly

    gtin
    05400123456789 agrees
    reference
    SKU-458 restated
    price
    €129 agrees
    colour
    rouge restated
  • Supplier B

    CSV over API

    gtin
    05400123456789 agrees
    reference
    458-R restated
    price
    134 EUR disagrees
    colour
    Red agrees
  • ERP extract

    Nightly job

    gtin
    05400123456789 agrees
    reference
    PROD-458 restated
    price
    129.00 agrees
    colour
    R restated
  • PIM extract

    Manual entry

    gtin
    05400123456789 agrees
    reference
    SKU458 restated
    price
    not set absent
    colour
    rouge restated

After One record, every field accountable

CHAIR-458

Ergonomic office chair

  • CHAIR-458 reference sourced from Fuse master validated
  • 05400123456789 gtin sourced from Supplier A validated
  • 129 EUR price sourced from ERP extract validated
  • Red colour sourced from Colour reference validated
  • EN · FR · NL locales sourced from Translation step validated

Ready to publish

How it works

Six steps. One discipline.

The same pipeline runs on every import, on the rules you set.

  1. 1

    Collect

    CSV, JSON and XML files, REST APIs and exchange standards, plus extracts from the ERP, PIM, WMS and suppliers you already run.

  2. 2

    Understand

    Structure, formats, languages, units, categories and currencies, mapped to your model.

  3. 3

    Reconcile

    Duplicates, variants and conflicts, resolved on the business key you configured.

  4. 4

    Enrich

    Mapped internal fields first, then the approved external sources you switch on.

  5. 5

    Control

    Completeness, schema and business rules, at the strictness you choose.

  6. 6

    Publish

    Files, REST or a connector to the shop, the PIM and the channels, as changes are validated or on schedule.

Inside the record

Every field knows where it came from

Origin, transformation and validation status travel with each value, so you finally master all your information sources. When a price is questioned, the answer is on the record — not in someone’s inbox. You get real data lineage at field level: trace, explain and trust every value.

price sourced from ERP extract validated

CHAIR-458 Ergonomic office chair

price
129 EUR ERP extract · priority rule applied · validated
colour
Red Supplier A · glossary term applied · validated
lead_time
Absent from every source · waiting in the Inbox

Outcomes

What changes, and how it is measured

Four figures from Data Punks engagements. Each one shows what it is measured against, because a number without a denominator is decoration.

  • -70%

    Data processing time

    The hours spent collecting, cleaning and reformatting product data before it can be published.

    Observed on Data Punks engagements, comparing the manual effort on an agreed perimeter before Fuse with the same perimeter once the pipeline runs it. Not a contractual commitment.

  • -100%

    Critical data errors reaching a channel

    Errors on the fields you decided are critical: they are blocked at the boundary instead of published.

    Applies to fields covered by blocking validation rules. Those records stop in the Inbox, so none reach a channel; fields you choose not to gate are not counted.

  • -60%

    Data time-to-insight

    How long it takes to answer a question about the catalogue, from "where did this price come from" to "which products are incomplete in Dutch".

    Observed on Data Punks engagements, measured on questions that previously required extracting and joining data from several systems by hand.

  • +30%

    Omnichannel performance

    Complete, compliant records published on more channels, with fewer rejections and fewer withdrawals.

    Observed on Data Punks engagements across the channels in scope. Depends on the catalogue's starting completeness and on each channel's own rules, so it is measured per client rather than promised.

Fit

It sits beside what you already run

Fuse is a non‑intrusive SaaS layer that complements your internal and external sources, your applications and your reference data.

No heavy implementation, no rip‑and‑replace. Your systems keep ownership of their fields; Fuse makes the whole landscape more reliable.

Beside your stack
Fuse is the quality layer between sources and systems. It prepares and reconciles data before it enters your PIM and before it reaches your channels, so every application consumes clean, standardised and trusted values.
EU data residency
All Fuse product data is processed and stored in the European Union, on EU infrastructure, to meet your sovereignty and compliance expectations.
Twenty years of it
Data Punks is a Brussels company with more than twenty years of experience in European data governance and integration architecture. We build pragmatic solutions for real business constraints, not lab prototypes.
Humans in the lead
You define the model, the priorities and the level of strictness. AI agents accelerate detection, matching and enrichment, but every rule and every decision stays under your control.

Bring us the feed that breaks first

One supplier, one range or one marketplace. We map it, run it through Fuse and show you the exceptions on your own data.

Thirty minutes. No slide deck.