How to use Profitability Dashboard

Metricuno
May 21, 2026
7 min read
Quick answer

A template — and the metric stack behind it — for putting true ROI on one screen: contribution margin, blended marketing efficiency, and ROI by cohort and channel.

Definition
Reporting templates

Profitability Dashboard

A single-screen view of true ecommerce ROI: revenue, contribution margin, blended marketing efficiency, and ROI by cohort and channel.

A profitability dashboard is the operating view a founder or Head of Ecommerce opens first thing Monday morning. Instead of showing top-line revenue and platform-reported ROAS, it stacks the metrics that actually decide whether the business makes money: contribution margin after COGS, fulfilment, and payment fees; blended marketing efficiency across every channel; and ROI by acquisition cohort and channel over a meaningful time window.

The template matters because the metrics on it force a different conversation. Once gross margin, MER, and 60-day cohort ROI sit next to revenue, you stop optimising for traffic and start optimising for the dollars that survive checkout.

Also known as
DTC profit dashboard
Ecommerce P&L dashboard
Contribution margin dashboard

Most Shopify and WooCommerce stores in the €1M-€15M band run reporting that looks healthy and hides the leak. GA4 shows sessions and conversion rate. Meta and Google show ROAS. The bank account shows something else entirely.

The gap is structural. Ad platforms claim revenue they didn't cause, gross margin gets quoted before fulfilment and returns, and repeat-customer profit gets attributed to whichever channel ran a retargeting ad last. A profitability dashboard closes that gap by putting all of it in one place.

The four metric blocks every profitability dashboard needs

Block one: revenue and contribution margin. Net revenue (after discounts, refunds, and returns) sits at the top, then contribution margin in both euros and percent. Contribution margin = revenue − COGS − pick/pack/ship − payment fees − returns reserve. Anything above that line is vanity until you've subtracted those four costs.

Block two: blended marketing efficiency (MER). Total revenue divided by total ad spend across every paid channel — Meta, Google, TikTok, affiliate, influencer. MER is the truth-teller that platform-reported ROAS isn't, because it can't double-count and it can't lie about attribution.

Block three: ROI by acquisition cohort. Customers grouped by the month they first bought, tracked across 30/60/90 days and 12 months. Block four: ROI by channel, where channel-level CAC meets channel-level LTV. Together these two answer the only question that matters for scaling spend: which channels acquire customers that pay you back, and how fast.

The MER vs ROAS trap

If your platform ROAS is climbing but blended MER is flat or falling, the platforms are claiming credit for sales that would have happened anyway. This is the single most common pattern in DTC reporting — and the reason MER belongs on the dashboard, not buried in a quarterly spreadsheet.

Why blended efficiency belongs on the front page

Platform ROAS sums to more than 100% of your revenue. Meta will report on a sale Google also reported on, which TikTok also reported on. Without a blended view, scaling spend on the channel with the best ROAS often means scaling the channel best at claiming credit, not the channel best at causing sales.

MER cuts through that. A store running €200k/month at €50k blended ad spend has MER of 4.0 — full stop. When MER drifts from 4.0 to 3.2 over a quarter, you have a profitability problem even if every individual channel ROAS card looks green. The chart below shows the divergence pattern from a typical apparel store over six months.

Chart

Platform ROAS vs blended MER: the divergence that hides margin loss

0x1x2x3x4x5xJanFebMarAprMayJunEfficiency multipleMonth

Reported platform ROAS (weighted avg)

Blended MER (revenue / total ad spend)

Six months in, platform ROAS says efficiency is improving. The bank says the opposite. This is the single chart that should sit on every profitability dashboard — and it's why MER, not ROAS, is the headline number.

Contribution margin benchmarks by vertical

Contribution margin varies enormously by what you sell. An apparel store at 55% gross margin and a supplements brand at 75% are not the same business, and a dashboard with a hard-coded target line will mislead one of them. Use the table below as a sanity check on where your store should land.

The numbers below are contribution margin after COGS, pick/pack/ship, payment processing, and a 5-8% returns reserve — not gross margin. They reflect Shopify and WooCommerce stores in the €1M-€15M revenue band; sub-€1M stores typically run 5-10 points worse because of smaller order volumes and weaker carrier rates.

Benchmark

Contribution margin ranges by ecommerce vertical (after COGS, fulfilment, payment, returns)

VerticalGross margin (typical)Contribution margin (healthy)Contribution margin (under pressure)
Apparel & accessories55-65%30-38%18-25%
Beauty & skincare70-80%45-55%30-38%
Supplements & wellness70-85%50-60%35-42%
Home & lifestyle50-60%25-32%12-20%
Consumer electronics30-40%12-18%4-9%
Food & beverage (shelf-stable)45-55%20-28%8-15%

If your dashboard shows contribution margin in the "under pressure" column for your vertical, no amount of ad-spend optimisation will fix it — the leak is in product economics, pricing, or fulfilment. That's the diagnostic value of having these numbers on one screen instead of in four different reports.

Wiring it up: data sources and refresh cadence

Practically, a profitability dashboard pulls from four places: your ecommerce platform (Shopify, WooCommerce, Magento) for orders and returns, your ad platforms for spend, your accounting tool or cost-of-goods sheet for COGS and fulfilment, and your CRM or email tool (Klaviyo, typically) for cohort assignment. Most stores already have all four — the work is stitching, not collecting.

Refresh cadence matters more than people think. Revenue and MER should update daily; contribution margin can refresh weekly because COGS and fulfilment lag; cohort ROI updates monthly because 30/60/90-day windows need to close. A dashboard that tries to show everything in real time ends up with one number lying and the rest distrusted by association.

How this fits into ROI decision frameworks

The dashboard surfaces numbers; an ROI decision framework turns them into actions — when to scale a channel, when to pause one, when to revisit pricing. Treat the dashboard as the input layer and the framework as the decision layer. One without the other is either dashboards-for-dashboards' sake or gut-feel disguised as strategy.

Frequently asked

Frequently asked questions

A standard ecommerce dashboard shows traffic, conversion rate, AOV, and revenue — the metrics that describe activity. A profitability dashboard shows contribution margin, blended MER, and cohort ROI — the metrics that describe whether the activity makes money. The first answers "what happened?"; the second answers "should we keep doing it?".

Platform ROAS double-counts. Meta, Google, and TikTok will each claim credit for the same sale if all three touched the customer. Blended MER (total revenue ÷ total ad spend) can't double-count by definition, so it's the only ad-efficiency number that ties cleanly to your P&L.

Start with net revenue (after discounts and refunds), then subtract COGS per unit, pick/pack/ship cost per order, payment processing fees (typically 2.4-2.9%), and a returns reserve (5-8% for apparel, 1-3% for supplements). What's left is contribution margin. Most Shopify stores need a separate sheet or tool because Shopify Analytics doesn't subtract fulfilment or returns.

It depends on contribution margin. As a rule of thumb, your MER needs to be at least 1 ÷ contribution margin %. If your contribution margin is 35%, you need MER of ~2.9x just to break even on ads; healthy growth needs 3.5-4.5x. Stores with stronger margins (beauty, supplements) can profitably run MER as low as 2.0-2.5x.

Track 30, 60, 90 days, and 12 months. The 30-day window tells you whether the cohort is profitable on first purchase (the only window that matters if you can't afford to wait on cash). The 90-day and 12-month windows tell you about repeat behaviour and channel quality — useful for deciding which channels to scale even when their first-order CAC looks expensive.

MER is total revenue divided by total paid ad spend, so organic and direct revenue stay in the numerator but contribute zero to the denominator. That's deliberate: if a channel's incremental contribution is real, MER goes up as you turn off spend; if it's claimed credit, MER stays flat. It's the cleanest test of channel incrementality you can run from a dashboard.

Daily for revenue, ad spend, and MER. Weekly for contribution margin (COGS and fulfilment data lags). Monthly for cohort ROI (you need the 30/60/90-day windows to close). Trying to put everything on a real-time refresh produces numbers that contradict each other and erode trust in the whole view.

The metric stack is the same, but the benchmarks shift. Stores under €1M typically run contribution margins 5-10 points lower because of smaller-order pricing on fulfilment and payment processing. The dashboard is still worth building — in fact, it's often where smaller stores discover their unit economics don't work yet, before scaling spend makes it worse.

The dashboard is the input layer — it surfaces the numbers (MER, contribution margin, cohort ROI). An ROI decision framework is the rules layer that converts those numbers into actions: scale a channel when 60-day cohort ROI > 1.2, pause when contribution margin drops below vertical floor, revisit pricing when MER stays under target for two consecutive months. You need both.

Shopify Analytics covers revenue, AOV, and conversion rate but doesn't natively show contribution margin (no COGS or fulfilment subtraction), blended MER (no ad-spend ingestion), or cohort ROI past 30 days. You'll need either a profitability tool, a stitched BI setup (e.g. Looker Studio + Shopify + ad connectors), or a platform like Metricuno that ingests historical data and assembles the view without dev work.

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