The E-commerce Scorecard
This scorecard tracks the numbers that decide whether an online store is making money after ad spend, not just whether the ad platforms say they are working. It blends paid media, email, site conversion, inventory, and tracking into one weekly view. The owner or marketing lead runs it, and every row has a named person who answers for it.
Why this scorecard exists
Why platform dashboards are not a scorecard
A generic marketing scorecard gives an online retailer a leads column and a cost per lead. Stores do not sell leads. They sell orders, and each order carries product cost, shipping, discounts, returns, and payment fees before a dollar of profit shows up. A scorecard that stops at revenue or platform ROAS hides the fact that a store can grow top line every month and lose money doing it.
Measuring a store is different because the ad platforms grade their own homework. Google, Meta, and TikTok each claim credit for the same orders, so adding up their reported ROAS produces a number that never matches the bank account. Email and SMS claim orders that would have happened anyway. Inventory adds a problem no other business has: you can run a perfect campaign that sends people to a product you cannot ship. The scorecard has to reconcile all of that against store data the platforms cannot touch.
When the scorecard is live, the weekly conversation changes. MER and contribution margin after ad spend replace platform ROAS as the number the owner cares about. The media buyer, the email lead, the site lead, and whoever runs inventory each report one row and one red flag. Budget moves, product exclusions, and tracking fixes get decided in the meeting with a name and a date, instead of discovered in the P&L two months later.
The scorecard
12 numbers. Every one has an owner.
| Metric | What it means | How to set the target | Owner | Cadence | Red flag |
|---|---|---|---|---|---|
| Blended ROAS It is the one return number the platforms cannot inflate, and it exposes the gap between what Google, Meta, and TikTok claim and what the store actually booked. | Total store revenue divided by total paid media spend across every platform, using store order data rather than platform-reported conversions. | Start with your trailing 8-week median blended ROAS from store data. Set the floor at the level where contribution margin after ad spend stays positive, then tighten by a set step each quarter as creative and site conversion improve. | Media buyer | Weekly | Two consecutive weeks below the floor, or a week where platform-reported ROAS runs more than a third above blended, triggers a spend reallocation review and an attribution check. |
| MER (marketing efficiency ratio) MER is the number the owner can tie to the bank account because it counts every marketing dollar, not just what went into ad auctions. | Total store revenue divided by total marketing spend, including paid media, email and SMS tooling, affiliate fees, and any paid content. | Pull 12 months of revenue and full marketing spend from your books and calculate the monthly MER. Set the target at the median of your profitable months, and revisit it when you change your channel mix or launch a new product line. | Owner | Weekly | MER falling below the target for a full month, or dropping more than 15 percent week over week without a planned spend increase, moves budget decisions to the owner until it recovers. |
| Contribution margin after ad spend This is the row that tells you whether growth is worth having, and it is the only row that catches a store that is scaling revenue while losing money on every order. | Revenue minus product cost, shipping, payment fees, discounts, returns, and paid media spend, calculated as one number for the period. | Build the formula once with your finance lead so cost of goods, shipping, fees, and returns are pulled from real data, not estimates. The target is the dollar contribution you need to cover overhead and fund the next quarter, set from your own P&L, and the ratio version comes from dividing that by revenue. | Finance lead | Weekly | Any week where contribution margin after ad spend goes negative freezes budget increases until the media buyer and finance lead identify which channel or product caused it. |
| New customer order share Paid media that mostly retargets existing customers looks efficient and grows nothing, and this row is how you catch that. | The percentage of orders in the period that came from first-time customers, according to the store's customer record. | Look at your trailing 12 weeks and mark the share of new customer orders in the weeks where you grew profitably. That range is your target band, and the band should move up when you are in an acquisition push and down during a retention or holiday push. | Media buyer | Weekly | New customer share dropping below the band for three straight weeks while paid spend holds flat or rises triggers an audience and exclusion review in every ad account. |
| New customer acquisition cost Blended ROAS hides the price of a new customer, and that price decides whether your acquisition spend pays back within the window you can afford. | Paid media spend attributed to acquisition campaigns divided by the number of first-time customers in the period. | Calculate your average first-order contribution margin and your typical repeat purchase value over 90 days from store data. Your acquisition cost ceiling is the number that pays back inside the window your cash position allows, and you tighten it as repeat rate improves. | Media buyer | Weekly | Acquisition cost above the ceiling for two consecutive weeks pauses scaling on prospecting campaigns and starts a creative and landing page review. |
| Returning customer revenue share A healthy store earns a growing share of revenue without paying an ad platform for it, and this row shows whether retention is doing its job. | The percentage of store revenue in the period that came from customers with at least one prior order. | Chart your returning revenue share monthly for the past year and note the trend. The target is a steady climb from your current level, with the pace set by your email program's capacity, not a number borrowed from another store. | Email and lifecycle lead | Monthly | Returning share falling for two consecutive months while new customer volume holds steady triggers a review of post-purchase flows and repeat purchase offers. |
| Add-to-cart rate It is the earliest signal that the product page, price, or traffic quality is off, and it isolates site problems from ad problems. | Sessions with at least one add-to-cart event divided by total sessions, split by traffic source. | Set a floor from your trailing 8-week median by traffic source, since paid social and branded search will never behave the same. Raise the floor after any product page or pricing change that proves out over four weeks. | Web lead | Weekly | A drop of more than 20 percent from the source's median in a single week triggers a same-day check of site speed, product page changes, and the landing pages attached to live ads. |
| Checkout conversion rate Every point lost between checkout start and order is paid traffic already bought and wasted, and it is the cheapest fix in the whole scorecard. | Orders divided by checkouts started, measured in the store platform rather than in the ad platforms. | Use your trailing 8-week median as the floor. Check it separately for mobile and desktop, because a shipping cost surprise or a broken payment method usually shows up on one device first. | Web lead | Weekly | Any week below the floor triggers a test order on mobile and desktop, plus a review of shipping rates, discount code errors, and payment gateway logs. |
| Email and SMS revenue share Owned channels are the cheapest revenue a store has, and this row keeps the team from over-relying on paid media to hit the number. | Revenue attributed to email and SMS divided by total revenue, using a single attribution window agreed on and written down. | Pick one attribution window and stick with it, then calculate your share for the past six months. The target is a steady increase from your current level, with the size of each step tied to the flows and segments you plan to launch this quarter. | Email and lifecycle lead | Weekly | Share falling below your six-month low, or a sudden jump that does not match the campaign calendar, triggers a deliverability check and a review of the attribution settings. |
| Spend on out-of-stock products This is waste no ad platform will flag for you, and it is common in any store where inventory and marketing live in different systems. | Paid media spend in the period that went to ads or shopping listings for products that were out of stock or below their reorder point. | The target is zero, and the logic is a feed rule or automation that pauses or excludes products the moment stock crosses your reorder threshold. Track the dollar amount weekly so the team can see the fix holding. | Inventory lead | Weekly | Any spend above zero on out-of-stock products triggers a same-week check of the product feed sync and the inventory rule, with the media buyer and inventory lead on the same call. |
| Tracking health Every other row on this scorecard is only as good as the tracking behind it, and platform algorithms optimize toward whatever the pixel tells them. | Orders reported by the ad platforms and analytics tools, added up, compared against orders in the store platform, plus a check that every key event is firing. | Set your acceptable gap from the past four weeks of reconciliation between your analytics order count and your store order count, and treat any widening as a problem. Add a checklist of events that must fire, from view content through purchase, and test them after every site deploy. | Marketing lead | Weekly | An order count gap wider than your baseline, or any missing purchase event, stops budget changes until the tracking is fixed and reverified. |
| Average order value Ad efficiency depends on it, and small changes from bundles, thresholds, and promotions move blended ROAS more than most campaign edits do. | Total revenue divided by total orders in the period, split by new and returning customers. | Use your trailing 12-week median as the baseline and set the target based on the free shipping threshold, bundle, or upsell you plan to test. Compare against the same period last year when seasonality matters. | Marketing lead | Weekly | AOV falling more than 10 percent below the baseline for two consecutive weeks triggers a review of active discounts, promotion stacking, and the product mix in paid campaigns. |
Targets are set from your own history, never from someone else's benchmarks. The builder does the arithmetic once you plug in your numbers.
The weekly review
Twenty minutes, same order, every week.
// 01
Start with MER and contribution margin after ad spend
The owner reads both numbers against target before anyone mentions a campaign. If both are green, the meeting is about what to scale. If either is red, the rest of the meeting is about finding the cause.
// 02
Check tracking, then the drivers
The marketing lead confirms the order count gap is inside baseline so the team knows the numbers are real. Then the group looks at new customer share, checkout conversion, out-of-stock spend, and email share to see which one moved the top line.
// 03
Each owner reports one row and one red flag
The media buyer, email lead, web lead, inventory lead, and finance lead each get two sentences: where their row landed, and whether a red flag fired. No screen sharing, no campaign walkthroughs. Red flags get discussed, green rows get skipped.
// 04
Decide, assign, and write it down
Every red flag leaves the meeting with an action, an owner, and a date. Budget moves, product exclusions, and site fixes get logged next to the scorecard so next week starts by checking whether they worked.
Where scorecards die
Mistakes we see constantly.
Grading on platform ROAS
Each ad platform claims the same orders, so their combined ROAS is always higher than what the store booked. Blended ROAS from store data and MER are the only return numbers that survive contact with the bank account.
Not splitting new from returning
A retargeting-heavy account will look efficient while it stops acquiring anyone. Without new customer share and acquisition cost on the scorecard, the store finds out when growth stalls.
Leaving inventory off the scorecard
Marketing teams rarely see stock levels, so ads keep running on products that cannot ship. One row for out-of-stock spend, owned by the person who controls inventory, ends the problem for good.
Skipping contribution margin because it is hard
Revenue is easy to pull and margin takes a formula, so most scorecards stop at revenue. A store that skips this row can hit every other target and still lose money on growth.
Trusting the pixel without reconciling it
One broken deploy can silently drop purchase events, and every platform will optimize toward the wrong signal for weeks. A weekly order count match against the store platform catches it in days instead of quarters.
Other scorecards
Same discipline, different numbers.
By platform
By business type
Want it set up live in your dashboards?
We install scorecards on real data, wire the owners and alerts, and coach the weekly review. Scorecards and accountability is the service.
Questions we get
Straight answers.
What is the difference between blended ROAS and MER?
Blended ROAS divides store revenue by paid media spend only. MER divides revenue by all marketing spend, including email and SMS tools, affiliate fees, and content. Blended ROAS tells the media buyer how the ad budget is doing, and MER tells the owner how the whole marketing operation is doing.
How do I set a ROAS target without an industry benchmark?
You do not need one. Your target comes from your own margin: the ROAS at which contribution margin after ad spend stays positive is your floor, and your trailing 8-week median tells you where you stand today. Tighten from there as site conversion and creative improve.
Do I need contribution margin on the scorecard if I already track revenue?
Yes. Revenue does not account for product cost, shipping, discounts, returns, or fees, and those decide whether an order was worth buying. Build the formula once with your finance lead and the row updates itself every week.
What if my ad platforms and my store platform disagree on orders?
They always will, because each platform counts orders it touched, and the store counts orders that happened. The scorecard tracks the size of that gap as tracking health and treats a widening gap as a red flag. Store data is the source of truth for every row.
Who should own this scorecard in a small e-commerce team?
The owner or marketing lead runs the weekly review, but each row needs a separate owner who can act on it: a media buyer for paid rows, an email lead for owned channels, a web lead for conversion, and whoever controls inventory for out-of-stock spend. If one person holds every row, the scorecard becomes a report instead of a meeting.
A scorecard is only as good as the system feeding it.
Start with a diagnostic call. We will tell you which of these numbers you can trust today and what it takes to trust the rest.