Cleanse
Remove errors, broken encodings, and formatting inconsistencies from retailer, marketplace, and distributor files.
DataHub
From fragmented feeds to a number you can act on
Ingest marketplaces, ERPs, and distributor files. Match SKUs. Score health. Publish role-based reports. The intelligence layer is this warehouse — not a chart taped onto last week’s export.
Steps
How work actually moves
Four jobs the platform already does. Conversational agents and a full SKU graph are not claimed as shipped product here.
- 01
Ingest
Marketplaces, modern trade, general trade, distributors, and ERP — files and feeds into one DataHub.
- 02
Match
Barcode, pack, and retailer codes mapped to your internal SKU identity. Duplicates and gaps are scored, not ignored.
- 03
Govern
A live Data Health Score so commercial teams know which numbers are trusted enough to act on.
- 04
Publish
Role-based reports and Inventory360 — custom and executive views on the same warehouse, not a second spreadsheet.
11
Data foundation
Valuable decisions start with a governed DataHub
Cleanse → standardise → enrich → catalog. Original SKUsight steps on channel files — not a generic data brochure.
Standardise
Create one schema across barcodes, packs, retailer codes, and ERP items — so packs can be compared.
Enrich
Attribute and categorise with matching assistance. Score completeness, duplicates, and gaps.
Catalog
Publish a governed commercial model and the documentation teams actually use — then role-based reports read it.
DataHub in detail · SKU Intelligence
SKU Intelligence
Every pack gets one name
Retailer codes, marketplace ASINs, distributor aliases, and ERP items land on the same SKU identity before reports are published. Matching is a DataHub job — not a monthly Excel merge.
Ingest
Files and APIs from retailers, marketplaces, distributors, and ERP keep their source keys.
Match
Rules plus review put those keys on one master SKU so sell-in, sell-out, and stock can be compared.
Publish
Role-based reports only run on matched, health-scored rows — not on a hopeful VLOOKUP.
How SKUsight works
See. Understand. Act — on one SKU identity.
This is not another analytics dashboard. DataHub lands the feeds, matching gives every pack a name, health says what you can trust, and role-based reports put the next action in front of the right team.
SEE
Every SKU, every channel
UNDERSTAND
Why the number moved
ACT
Before revenue is lost
pipeline · illustrative product view
Updated moments ago· exampleDataHub flow
Data Health Score92 · example
Product chrome — not a published customer result.
The animated pipeline in the hero is the same story: ingest every channel, map SKUs, warehouse the facts, then publish a report the role can act on. DataHub in detail · Platform capabilities.
Data Health
Know which numbers you can act on
Every ingest is scored. Matching, duplicates, gaps, and outliers are visible to the people who own the number — not hidden in an analyst’s notebook. The scores below are product UI examples, not published customer results.
Workspace · illustrative
Data Health Score
92
SKU match rate96.4%
Completeness91%
Freshness (sources landed)88%
Product chrome from the workspace — illustrative health metrics, not a customer result.
Decision levels
From what happened to what to do next
SKUsight already frames commercial work as descriptive, diagnostic, predictive, and prescriptive — on the same DataHub, not a separate ‘AI product’. Forecasting and exception reports are in the platform today; conversational agents are not claimed as shipped.
01
Descriptive
What happened
Sell-out, sell-in, inventory, and contribution — by SKU, channel, and account — on one model.
02
Diagnostic
Why it happened
Price–volume–mix, availability, leakage, and promo so the movement has a cause.
03
Predictive
What is next
Demand baselines, stock-out risk, and cover days so the next miss is visible early.
04
Prescriptive
What to do
Role-based exceptions and reports that tell supply, sales, and finance where to act.