License purpose-built models that turn commerce, retail, marketing, inventory, and cost data into consistent business metrics—without building every transformation and business rule from scratch.
Deploy within your data environment on supported architectures, connect your reporting tools, and extend governed intelligence to AI through Daasity’s MCP AI Server.
| Channel | Net sales | CM1 % | CM2 % | CM2 vs PY |
|---|---|---|---|---|
| DTC · Shopify | $4.82M | 58% | 34% | ▲ 2.1 pts |
| Amazon | $3.10M | 41% | 22% | ▼ 3.4 pts |
| Wholesale (sell-in) | $2.65M | 39% | 27% | ▲ 0.8 pts |
| TikTok Shop | $0.74M | 44% | 13% | ▼ 5.0 pts |
fct_omnichannel_sales+cost_rules→fct_contribution_marginTransformation logic, modeled tables, business rules, and documented metric definitions for each model.
Between the pipelines and warehouse you already run and the BI tools and AI applications your teams already use.
Commerce logic—channel mapping, sell-through vs. sell-in, cost allocation—is hard to build and harder to maintain. Daasity maintains it.
Here’s what the Omnichannel Sales and Contribution Margin models deliver to the business: the questions they answer, the outputs your team gets, and the decisions they support.
Each model stands on its own and shares common definitions with the others, so you can start with your most pressing question and add models as you grow.
Where are sales growing across products, accounts, and channels?
Key inputs: DTC orders, marketplace sales, wholesale shipments, retail POS where available
Which products and channels contribute the most after relevant costs?
Key inputs: sales data, COGS, channel fees, fulfillment, marketing and trade spend
Which promotions deliver profitable results?
Key inputs: retail POS, promotion calendar, trade spend and deductions
How does marketing investment relate to commercial performance?
Scope: marketing performance reporting and attribution. Statistical marketing mix modeling (MMM) needs are confirmed during scoping.
Key inputs: ad platform spend, attribution or web analytics, order data
Where do stock availability and demand create risks or opportunities?
Key inputs: inventory positions (DC, 3PL, retail), sales velocity, forecasts where available
Tell us the business question you need answered and the data you have today. We’ll recommend the model—or combination—that fits.
Discuss Model Licensing →Here’s what’s in a Daasity model license, what you can configure, and who is responsible for what.
| Your question | The answer |
|---|---|
| DeliverableWhat is delivered? | Transformation logic, modeled tables, business rules, metric definitions, and documentation for each licensed model. Transformation codeModeled tablesBusiness rulesMetric definitionsDocumentation |
| DeploymentWhere does it run? | In your cloud data warehouse on supported platforms and transformation frameworks, or hosted on the Daasity platform. The supported architecture for your environment is confirmed during solution design. |
| ConfigurationWhat remains configurable? | The business logic that differs from company to company. Product mappingsChannel definitionsAccount hierarchiesCost treatmentsAllocation rules |
| ImplementationWhat does implementation include? | Source mapping, deployment, reconciliation against your financial reporting, and validation sign-off. Daasity and customer responsibilities are defined in the statement of work. |
| After launchWhat happens after launch? | Daasity maintains and updates the licensed model logic and provides support under your agreement. Customer-specific extensions are documented and managed as custom changes, so they’re preserved through model updates. |
| Usage rightsWhat are the usage rights? | Licensed for your internal business use. Deploying models for clients, or reselling them, is covered by a separate partner agreement. |
Most companies already have pipelines, a warehouse, and BI. What they lack is reliable foundational models. Daasity licenses that middle layer.
You already land source data in a warehouse. Daasity models deploy on top of it.
Add Daasity ingestion for sources you don’t have yet—like retail POS—then deploy the models.
Run the models on the Daasity platform if you’d rather not manage warehouse infrastructure.
Licensed together, the two models share product, channel, and account definitions, so every revenue number has a matching profit number.
See whether higher marketplace sales are offset by channel fees, fulfillment, or promotional investment—and which cost drivers deserve attention.
Rank channels and products by what they contribute after relevant costs when prioritizing expansion, promotions, and marketing spend.
Answers draw on governed definitions, so each figure can be traced back to the model. Responses depend on connected data and application configuration; validate before operational decisions.
When a brand sells to a retailer (sell-in) and that retailer sells to consumers (sell-through), both records describe the same units at different stages. Adding them together double-counts revenue.
The Omnichannel Sales model assigns each record a sales type, ownership, and channel, so wholesale sell-in counts toward company revenue while retail sell-through informs velocity, availability, and promotion analysis. Full rules are in the model documentation.
Brands license models to run their own business. Agencies and analytics platforms license them to deploy across clients.
Give finance, sales, and marketing one set of numbers without dedicating your data team to building and maintaining every model.
Extend your digital and marketing capabilities with retail and profitability models—without building them for each client.
The transformation logic, modeled tables, business rules, metric definitions, and documentation for each model you license. See What you license for the full breakdown.
No. You license the right to use them; Daasity retains the model IP and maintains the core logic. Your data remains yours and stays in your environment.
On supported cloud data warehouses and transformation frameworks in your environment, or on the Daasity platform. Prerequisites depend on your integration path; see Architecture.
No. The models sit between your data foundation and your reporting tools. Daasity ingestion is available for sources you don’t already capture.
Yes. Every model can be licensed on its own. Sales and Contribution Margin are a featured combination, not a requirement.
Daasity maintains and updates the licensed logic and provides support under your agreement. Your team owns configuration choices such as mappings and allocation rules.
Configurable settings—product mappings, channel definitions, cost treatments, allocation rules—are part of the standard model. Extensions beyond those are documented and managed as custom changes.
The model covers marketing performance reporting and attribution across digital channels. If you need statistical marketing mix modeling, raise it during scoping so expectations are clear.
Yes, through Daasity’s MCP AI Server with compatible AI applications, subject to your architecture, permissions, and configuration.
Tell us your business questions and your current data environment. We’ll walk through the right models, the supported deployment path, and licensing terms.
