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CLOSED-LOOP BIE-Commerce Analytics

Closed-Loop E-Commerce Analytics & Profit Intelligence: From Metrics to Execution

Traditional e-commerce analytics dashboards are descriptive: they show you graphs of revenue, traffic, and ROAS across disconnected tabs, but never explain why numbers changed or what actions to take. Orbit for E-Commerce unifies analytics with store control, providing causal root-cause diagnostics and closed-loop execution.

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Quick Answer: What is Closed-Loop E-Commerce Analytics?

Closed-loop analytics connects reporting telemetry directly to operational execution. Instead of discovering a margin drop in Looker and having to manually switch tabs to adjust ad spend or catalog prices in Shopify, closed-loop systems isolate the exact root cause (e.g., sizing returns, ad fatigue) and allow operators to execute fixes from the same conversational interface.

Core Technical Capabilities

True Landed Contribution Margin Waterfall

Calculates real net profit by deducting landed product COGS, pick/pack logistics, payment gateway surcharges, return shipping, and attributed ad spend.

Pareto 80/20 Catalog Profitability Audits

Identifies the core 20% of SKUs generating 80% of actual net cash, while isolating the margin bleeders that cost more to market and return than they generate.

Reverse Logistics & Return-Rate Diagnostics

Correlates customer return reasons with specific product variants and marketing channels, uncovering hidden sizing defects and packaging damage.

Closed-Loop Prescriptive Execution

Move seamlessly from discovery to action: when the system detects ad fatigue on a SKU, instruct it to pause the campaign or stage a bundle discount immediately.

Production Implementation Scaffold
analytics/contribution-margin.ts
Net Contribution Margin Waterfall Calculator
export interface OrderFinancials {
  orderGmv: number
  cogs: number
  merchantFees: number
  fulfillmentCost: number
  attributedAdSpend: number
  returnAllowance: number
}

export function computeNetContribution(order: OrderFinancials) {
  const grossProfit = order.orderGmv - order.cogs
  const totalVariableCosts = 
    order.merchantFees + 
    order.fulfillmentCost + 
    order.attributedAdSpend + 
    order.returnAllowance

  const netContribution = grossProfit - totalVariableCosts
  const contributionMarginPercent = (netContribution / order.orderGmv) * 100

  return {
    netContributionDollars: parseFloat(netContribution.toFixed(2)),
    contributionMarginPercent: parseFloat(contributionMarginPercent.toFixed(1)),
    profitHealth: contributionMarginPercent >= 22 ? 'HEALTHY' : 'MARGIN_LEAKAGE',
  }
}
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Frequently Asked Questions

How does Orbit calculate contribution margin without manual spreadsheet work?
Orbit ingests data streams from Shopify, Stripe, Meta/Google ad networks, and your landed COGS tables, automatically calculating net contribution margin per order and SKU in real time.
Does Orbit replace Triple Whale, Lifetimely, or Google Analytics?
Yes. Orbit consolidates attribution modeling, unit economics, and cohort reporting into a single workspace, eliminating multiple analytics subscriptions and the tab-switching click tax.
Can I query my business data in plain English?
Yes. You can ask complex analytical questions like 'Why did net profit shrink 6% despite revenue increasing 15%?' and receive a step-by-step causal breakdown in seconds.
Are queries executed safely against live data?
Yes. Orbit uses a governed Semantic Metric Layer that compiles queries into parameter-safe SQL executed against encrypted read-replicas, preventing query errors or data corruption.
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