Purpose-built data models for consumer brands

Unify every sales channel. Understand what drives profit.

Connect retail, eCommerce, Amazon, marketing and cost data into governed models that reveal where revenue is growing, what it costs to generate, and where to invest next.

Explore Daasity Models →See the Two Core Models
Keep your existing data investments. Add the models you need.
One connected view

Bring together DTC, marketplaces, retail, and wholesale reporting.

Revenue to margin

Link sales and units to relevant costs, fees, marketing, and trade spend.

Flexible deployment

Use Daasity as a platform or extend your existing analytics environment.

Featured commercial intelligence models

Know what you sold. Know what you earned.

Top-line growth and profitable growth are not the same thing. Daasity connects both perspectives through models designed for the complexity of consumer brands.

01 / Revenue visibility

Omni-Channel Sales Model

A consistent view of sales across DTC, marketplaces, wholesale and retail.

What you can understand

  • Net sales and units by brand, product, channel and retailer
  • Growth trends and channel mix over time
  • Retail sell-through versus wholesale sell-in where data is available
  • Performance across Shopify, Amazon and retail partners
  • Executive KPIs with consistent, governed metric definitions
Business question: “Which channels and products are driving incremental growth?”
02 / Profit visibility

Contribution Margin Model

Connect revenue to the cost of serving each product and channel.

What you can understand

  • CM1: Net sales less COGS and applicable channel fees
  • CM2: CM1 less marketing and trade investments
  • Contribution margin dollars and percentages
  • Profitability by product, SKU, channel and retailer as supported by inputs
  • How channel costs and promotion affect realized margin
Business question: “Which growth opportunities create the greatest contribution?”

Metric definitions, data grain, available cost categories and allocation rules are configured and validated for each customer. Sales sources must be reconciled to prevent double counting.

From revenue to return

Follow the economics—not just the sales chart.

Bring channel performance and cost data together to move from net revenue to contribution margin.

Net SalesRevenue across owned channels using agreed recognition and mapping rules
CM1Net Sales − COGS − applicable channel fees
CM2CM1 − marketing and trade investments
Better DecisionsPrioritize channels, products and growth opportunities by margin
Example analysis

Revenue can grow while margin falls

See whether higher marketplace sales are offset by channel fees, fulfillment expenses, or promotional investments. Identify which cost drivers merit attention.

Example analysis

Allocate investment where it counts

Compare channel contribution, not just gross revenue or ROAS, when prioritizing sales expansion, promotions, and marketing spend.

Beyond the core models

Extend the intelligence as your business grows.

Start with Omni-Channel Sales and Contribution Margin, then add the supporting models that answer your next business questions.

MODEL 03

Retail Promotion Optimization

Analyze promotional lift, trade investment, and performance by account and product to inform future promotional plans.

MODEL 04

Digital Marketing Mix

Connect marketing investment, attribution and commerce results to understand acquisition efficiency and channel performance.

MODEL 05

Inventory Optimization

Bring sales velocity, inventory position and available forecasts together to support smarter stock and replenishment decisions.

Preserve and extend

Already have an analytics platform? Keep it.

Daasity's data models can complement your existing digital sales and marketing analytics. Add retail intelligence, harmonize key definitions, then extend the same foundation into omnichannel revenue and contribution margin.

Existing digital models+Daasity retail ingestion→Governed mappings→Omni-Channel + Margin

For consumer brands

Connect teams around a clearer, shared picture of revenue and profit across sales channels. Use dashboards, governed data, and AI-enabled analysis as appropriate.

For agencies & analytics platforms

Add retail data models and deeper commercial intelligence to existing digital and marketing capabilities without having to rebuild the entire analytics stack.

AI-ready intelligence

Ask better questions of governed business data.

With the Daasity MCP AI Server, supported AI applications can interact with governed models so teams can explore commercial performance using natural-language questions.

Ask your data

“Which channels gained revenue but lost contribution margin last month?”

Connect relevant sales and cost measures to investigate channel economics.

Ask your data

“Where should we prioritize investment to reach our growth goal?”

Examine channel trends, margin trade-offs and opportunities for follow-up analysis.

AI responses depend on connected data, governed metric definitions, model coverage and application configuration. Recommendations should be validated before operational decisions.

Common questions

Frequently asked questions

Do we have to replace our current BI or marketing analytics platform?

No. Daasity's modular approach can support an existing environment. Integration scope, data-model mapping and delivery method are determined during solution design.

Can we adopt just one model?

Daasity offers modular data models. The right model and deployment approach depend on available source data, required outputs and integration scope.

How do you avoid double-counting retail and wholesale sales?

The implementation defines consistent ownership, sales type and channel rules. For example, retailer sell-through and a brand's wholesale sell-in may represent different stages of the same product movement; they should not be simply added together as company revenue.

What data is required for Contribution Margin?

At minimum, agreed sales and cost-of-goods inputs are needed. Channel fees, fulfillment, marketing and trade inputs—and their allocation methodologies—determine how complete the profitability analysis can be.

Can our team use AI tools to query the models?

Daasity's MCP AI Server supports access through compatible AI applications, subject to your organization's architecture, permissions and configuration.

Turn data into decisions

See your entire business. Invest in what drives profitable growth.

Explore how Daasity's Omni-Channel Sales and Contribution Margin models can fit your existing data environment and business goals.

Request a Model Demo →Contact Sales