Stock is not visible across channels
Storefront, marketplace and warehouse stock levels are updated at different times, so the same item is sold twice or shown as unavailable.
Impact: Cancelled orders, lost sales and customer complaints.
Retail and e-commerce analytics
Improve Inventory Visibility and Product Profitability With Unified Retail Data
Retail data is spread across storefronts, marketplaces, point-of-sale, warehouses and advertising platforms. We unify these sources so merchandising, inventory and marketing teams can see stock, sales and margin for each product and location in one place.
The channel problem
One product, five versions of its stock
A retail or e-commerce business sells through several channels, and each keeps its own version of stock and sales. The storefront, the marketplaces, the stores and the warehouse update at different times and in different formats. The result is overselling on one channel, idle stock on another, and product margins nobody can calculate with confidence.
We unify product, order, stock and settlement data under one identifier. Margin is calculated after returns, marketplace fees, shipping and discounts. Demand estimates feed directly into AI demand forecasting for inventory, and the same sales data supports intelligent order processing across channels. Teams planning a broader machine learning programme start from this governed base.
Channels and systems
Every storefront, marketplace and warehouse in one model
We confirm what each system exposes, how often it can be refreshed and who owns the data, before the design is final.
E-commerce storefront
Orders, customers, product catalogue and discounts
Marketplaces
Marketplace orders, fees and settlements
POS and store systems
In-store sales and returns
Warehouse and inventory system
Stock levels, transfers and receipts
Advertising and analytics platforms
Spend, impressions and campaign results
What it costs
Where unified retail data changes the numbers
Product margin is unknown
Revenue is reported per channel, but returns, fees, shipping and discounts are not allocated to products.
Impact: Decisions about pricing and range are based on revenue rather than profit.
Marketing performance is hard to link to sales
Ad platform data and order data are reported separately, with different attribution windows.
Impact: Budget moves toward the metrics that look good in each platform.
Reports arrive after the decision
Weekly spreadsheets are assembled by hand, and promotions are reviewed after they end.
Impact: Stock and pricing corrections come too late to matter.
Retail data model
One product identifier across every channel
Ingestion
Frequent loads of orders and stock from storefronts and marketplaces, with daily settlement and fee data.
Storage and modelling
A product, location and channel model with a single product identifier that maps every source.
Calculations
Contribution margin by product after returns, fees, shipping and discounts, using agreed rules.
Serving
Inventory, sales and margin dashboards for merchandising, plus campaign performance reporting for marketing.
Commercial measures
Stock, margin and campaign return on one basis
Each measure is baselined before the project starts, so improvement is shown against your own starting point.
| Measure | How it is calculated | Why it matters |
|---|---|---|
| Oversold orders | Orders accepted for stock that was not available | Shows the cost of stale stock data |
| Stock-out days | Days a product was unavailable on a channel where it was listed | Links availability to lost sales |
| Contribution margin by product | Revenue after returns, fees, shipping and discounts, per product | Shows which products deserve investment |
| Campaign return on spend | Margin generated per unit of marketing spend, on a consistent attribution basis | Makes budget decisions comparable across platforms |
| Data freshness | Time between a sale or stock change and its appearance in dashboards | Shows whether stock decisions use current data |
Illustrative scenario
Cross-channel stock visibility: illustrative
This is an illustrative scenario, not a verified client result. Measured outcomes are shared only from real projects, with their baseline and method.
The challenge
A brand sells through its own site, two marketplaces and its stores. Stock is updated in batches, so the same units are sometimes sold on more than one channel.
The approach
- Map every channel to one product identifier
- Load stock and orders at a frequency that matches the risk of overselling
- Publish a stock position dashboard with alerts when a product falls below its threshold
- Review channel allocation weekly with merchandising
What we measure: Oversold orders, stock-out days, margin per product after channel costs. Measured against a baseline from before the project.
Implementation path
From channel audit to monthly merchandising reviews
Each phase ends with a defined output. Timelines are estimated after the assessment, once sources and scope are confirmed.
- 1
Channel and product audit
We map each channel, its data and its refresh options, and check how products are identified across systems.
Output: Channel map and product identifier plan
- 2
Margin and attribution rules
We agree which costs are allocated to products, how returns are treated, and which attribution window marketing uses.
Output: Margin and attribution rule book
- 3
Pipeline and model build
We build the order, stock and settlement loads at the frequency each channel needs, with a single product and location model.
Output: Unified retail data model
- 4
Dashboards and alerts
We publish stock, sales and margin dashboards, with alerts when a product approaches a stock threshold or margin drops.
Output: Merchandising and marketing dashboards
- 5
Review and optimisation
We review performance with merchandising each month and refine the rules as new channels or products are added.
Output: Monthly review and rule updates
Rules and access
Margin rules and supplier costs under control
Controls are agreed for each project, based on the sensitivity of the data and the rules that apply to your organisation.
- Consistent product identifiers across all channels
- Access control for margin and supplier cost data
- Handling of customer identifiers in line with privacy requirements
- Documented rules for cost allocation and attribution windows
- Monitoring of data freshness for stock and orders
Dashboards and rules
What merchandising and marketing use every day
- Unified product and location data model
- Cross-channel inventory visibility dashboard
- Product profitability analysis with documented cost allocation
- Campaign performance report linked to order data
- Stock and sales alerts for merchandising teams
Retail questions
Retail and e-commerce analytics: FAQs
Can you connect our marketplace data with the storefront?+
Usually, through marketplace APIs, reports or settlement files. We confirm the available data and its refresh frequency during the assessment.
How is product profitability calculated?+
We agree the cost rules with finance and merchandising, such as which fees, returns and shipping costs are allocated to each product, and implement them consistently.
Can marketing and sales data be compared fairly?+
Yes. Attribution windows and definitions are agreed and documented, so campaign results are reported on a consistent basis.
How quickly can stock data be refreshed?+
It depends on the source systems. Some can refresh every few minutes through APIs, others daily. The refresh design follows the risk of overselling for each channel.
Can you handle many marketplaces with different fee structures?+
Yes. Each marketplace's fees and settlement timing are modelled separately, then combined into one margin view, so differences between channels remain visible.
Will merchandising teams be able to use the dashboards without help?+
The dashboards are designed for the questions each team asks, with agreed definitions and short training. Ongoing support is included in a support agreement.
Find out where your reporting delays come from
A data platform assessment maps your systems, the reports that matter and the decisions they support, then gives you a practical first step.