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+10% Revenue Per Visitor in 90 days. Or we refund the engagement.
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Your analytics tool ships a dashboard someone else decided you needed. Fixed schema, their metric definitions, and the night you ask a question that does not fit the tiles you export to a spreadsheet and rebuild it by hand. Here are the six views that actually run your store, each as a prompt you point at your own export. Build them in order and you have replaced the part of the GMV-priced dashboard you open every morning.
The six split into three habits. MER and CAC are your daily efficiency read. Contribution margin and new-versus-returning are your weekly health read. Cohort LTV and inventory cash are your monthly planning read. Stand them up in that sequence and you end with the morning glance, the weekly review, and the planning view that a percentage-of-revenue tool charges you to assemble.
Two rules make every number below trustworthy, so set them once.
Revenue truth is Shopify or Stripe, never the ad platform. Sum what Meta, Google, and Klaviyo each claim and you triple-count the same order, because all three take credit for it. That is why MER, spend against your actual store revenue, is the headline and per-platform ROAS is a directional cross-check. Build all six on Shopify revenue and feed platform numbers in only as the spend side.
Write your definitions down once. A one-page house-definitions doc, pinned to the project, fixes gross margin, your contribution-margin stack, return rate, processing rate, and how you count a new customer. Every prompt below inherits it, so you settle those arguments once instead of re-litigating them inside six dashboards.
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Steal this: open a doc today and write five lines: gross margin %, your contribution-margin stack, return rate, processing rate, and your definition of a new customer. That single page is what makes every dashboard below say the same thing every run. Most brands never write it, which is why their own metrics drift on them.
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Read these once so the outputs mean what you think they mean. When a number looks wrong, the cause is almost always a definition you and the model disagree on, not the math.
| Metric | Definition | Why it is the one that matters |
|---|---|---|
| MER (Marketing Efficiency Ratio) | Total revenue / total marketing spend, attribution-independent. MER of 4 means $4 of revenue per $1 spent. Same math as blended ROAS. | It cannot be gamed by attribution. Every platform-reported ROAS can. |
| Break-even MER | 1 / contribution-margin %. At 30% CM, break-even MER is 3.3. At 40%, 2.5. Below this line a marketing dollar loses money. | It draws the exact line where scaling spend starts costing you profit. |
| Blended CAC | All acquisition cost / all new customers (paid, organic, referral). | The true cost of a customer once organic stops flattering your paid number. |
| New (paid) CAC | Paid acquisition spend / net-new first-time customers. Track this beside blended CAC, weekly. | The spread between the two is your early warning that paid efficiency is rotting. |
| Contribution margin | Gross margin minus fulfillment, returns, payment processing, and acquisition spend. | The real DTC profit signal. Gross margin hides the costs that actually sink channels. |
| Cohort LTV | Cumulative gross profit per customer across the months until the cohort flattens. Payback is the month it first clears CAC. | It tells you whether you are buying customers who pay you back, and how fast. |
Use these as sanity-check ceilings, not targets. As rough industry bands: $1-5M brands run blended MER around 1.5-2.5, $5-10M around 2.5-3.5, $10-25M around 3.0-4.5, $25-100M around 3.5-6.0+. Blended CAC usually lands $50-100, and you want LTV:CAC at or above 3:1 with payback under 12 months. They exist to catch a number that is obviously broken, not to chase. Hold every one of them against your own history before you trust it.
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Steal this: compute your break-even MER right now, 1 divided by your contribution margin. If you are scaling spend at a blended MER below that number, you are buying revenue at a loss and the platform ROAS dashboard is hiding it. That one line reorders your whole media plan.
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For every dollar into paid, how many came back across the whole business, and are you above or below the line where marketing makes money. This is your morning glance.
Feed it total revenue (Shopify, net of refunds) and total marketing spend (every paid channel summed), by day.
You are my DTC analyst. Using the attached Shopify revenue export and the ad-spend
exports (Meta, Google, TikTok, and any other paid channel), calculate blended MER
for each day, week, and month in the file.
Definitions to use exactly:
- Revenue = Shopify gross sales minus refunds and discounts (use net revenue; tell me
which column you used).
- Total spend = sum of all paid-channel spend for the same period.
- Blended MER = revenue / total spend.
Also compute my break-even MER as 1 / contribution-margin%. My contribution margin is
[XX]%. If I don't give you one, ask before assuming.
Output a table: period | revenue | total spend | blended MER | break-even MER |
above/below break-even. Flag any day where MER fell below break-even.
State the max date present in the data so I know the window isn't stale.
Re-sum total spend a second way (sum each channel column independently and add) and
confirm it matches your first total. Report both numbers. If revenue or spend has
gaps or blank dates, list them. Do not silently skip them.
One trap to know about: ad platforms revise the last 24 to 72 hours of spend and conversions as late attribution lands, so a MER you pull at 6 AM for yesterday will move by tomorrow. Re-pull a trailing 7-day window each run so the recent days settle, and never treat the most recent two days as final.