How Mercidia measures performance

We standardize revenue, spend, fulfillment costs, and attribution inputs so recommendations are evaluated on real contribution, not vanity metrics.

Profit-first measurement

Mercidia treats marketing performance as an operating system problem, not a reporting problem. We reconcile ad spend, conversion sources, and margin assumptions into one decision layer so every recommendation can be judged by expected profit impact.

Revenue inputs

We align revenue windows across storefront, attribution, and paid media sources so performance comparisons are consistent.

Cost drivers

Fulfillment, product cost, platform fees, and marketing spend all flow into the same denominator before automation rules are allowed to act.

Measurement blueprint

Define your measurement window

Pick a consistent period so revenue, spend, and logistics costs line up. Most teams use the last 30 days or the trailing calendar month.

Lock the timeframe before pulling any data
Exclude one-off launches unless you can isolate their costs
Reconcile refunds or chargebacks inside the same window

Collect every cost driver

Marketing ROI is only as good as your denominator. Include ad spend, fulfillment & logistics, product costs, and any other variable fees tied to the revenue stream.

Marketing spend should match the channels included in revenue
Logistics covers shipping, warehousing, and handling fees
Product costs include COGS or wholesale fees
Other variable expenses capture agencies, payment fees, or incentives

Calculate contribution & ROI

With inputs standardized, convert everything to contribution margin, ROI percentage, and efficiency ratios. These support auditable performance comparisons downstream.

Contribution = Revenue − Total variable costs
ROI = Contribution ÷ Total variable costs
Efficiency ratio = Revenue ÷ Total variable costs

See the full data flow

Want to understand permissions, API boundaries, and how synced data enters the product? Start with the collection flow, then compare plans or create a workspace.

How we collect data View pricing

Read the methodology by question

Each page explains one part of the revenue-to-decision loop and the limits that keep the result honest.

How revenue is reconciledWhy Shopify, Meta Ads, and GA4 can disagree.How attribution is comparedFirst-touch, last-touch, and linear views without causal claims.How recommendations are builtObserved signals, uncertainty, options, owners, and outcomes.How Pilot is safeguardedCalibration, approvals, limits, provider-aware review, and rollback.