# ROAS Calculator — Competitor and Method Research

Reviewed 2026-09-29. Purpose: understand how return-on-ad-spend is presented
elsewhere, and decide which conventions are worth following and which are
misleading.

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## 1. Google Ads — Ads ROI and value columns

**What it is.** The platform reports "conversion value", "cost / conv. value"
(return on ad spend) and "conv. value / cost" (the inverse) on campaign and
advertised-time reports.

**What we take.** Using the platform's own terminology so a reader can reconcile
these numbers against their Ads account without translation.

**What we reject.** Presenting revenue ROAS as a profitability measure. Google
attributes a conversion value, not a profit, and a tool that blurs the two is the
single most common source of bad budget decisions. Every profit figure here is
labelled as after-cost, and break-even is shown beside ROAS so the gap is
explicit.

## 2. Shopify and WooCommerce profit reports

**What it is.** Storefront analytics reporting net profit, margin and profit per
order alongside revenue.

**What we take.** Showing **profit per order** and **net margin**, not only a
ratio. A ratio can look healthy while the absolute profit is small or negative,
and a small or large order distorts it either way.

**What we reject.** Reporting gross profit from a revenue figure with an assumed
cost. Landed COGS, payment fees, fulfilment and returns all matter, and
under-counting them inflates every profit number. The tool asks for them
explicitly and says so when contribution is zero.

## 3. Optmyzr — break-even and projected spend reporting

**What it is.** A rules-based platform reporting per-account break-even ROAS and
projected month-end spend, with budget monitoring and alerts.

**What we take.** The break-even-plus-15% "target" convention. A target that is
merely break-even leaves nothing for overhead, error and variance.

**What we reject.** Presenting a single account-wide break-even. Break-even moves
with margin, so a blended account figure hides the campaigns dragging it down.
Margin is an input here, not a conclusion.

## 4. WordStream — performance grading against benchmarks

**What it is.** Grades an account against industry averages and suggests pausing
underperforming keywords and adding negatives.

**What we take.** Showing a comparison, because a bare number is uninterpretable.

**What we reject.** Grading letters as the headline. A "B" grade is a benchmark
artefact, and it tells a user nothing about whether *their* account is profitable.
The verdict here is derived from their own margin and break-even.

## 5. Opteo and Adalysis — automated recommendations

**What it is.** Recommendation engines that flag underperforming segments and
propose budget and keyword changes — Opteo and Adalysis, both of which run
40-plus automated checks against a connected account.

**What we take.** The pattern of converting an analysis into a short, ordered
list of actions rather than a wall of metrics.

**What we reject.** Acting on the account. Recommendations here stay
recommendations; the tool changes nothing in the ad platform.

## 6. The common standalone "ROAS calculator"

A large category of lead-gen calculators: revenue and spend in, a ratio out, an
email address required to see the answer.

**What we reject.** The business model. These tools treat profitability as the
hook and gate the formula behind an email address, then compare the visitor
against a benchmark. It produces numbers that are technically correct and
practically misleading, because the cost of goods is never asked for.

---

## Method notes — what this tool computes

Every formula below is shown in the interface. Nothing is inferred from an
industry average.

| Figure | Formula | Why it can mislead if shown alone |
| --- | --- | --- |
| ROAS | `revenue ÷ ad spend` | Ignores margin entirely. A 6× return on a 12% margin is a loss. |
| Contribution | `revenue − COGS − variable cost` | The only figure that can pay for ads at all. |
| Break-even ROAS | `1 ÷ contribution margin` | Infinite when margin is zero. Shown as such, with an explanation. |
| Target ROAS | `break-even × 1.15` | Arbitrary but stated. 15% headroom, not a secret. |
| MER | `total revenue ÷ total marketing spend` | Includes channels the reader may not control. |
| CPA | `ad spend ÷ conversions` | Rewards cheap conversions that lose money. |
| Profit per order | `(contribution − ad spend) ÷ orders` | The most robust single number for mixed order values. |
| Net profit | `contribution − ad spend − fixed cost` | The fully loaded answer. Can legitimately be negative. |

**Deliberate design choices**

- **Zero is treated as a real zero, not as missing data.** A period with revenue
  and no spend is reported as an organic period, not as a broken input.
- **No spend means no ROAS.** Displaying an infinity would invite someone to
  quote it. The ratio is undefined and is shown as a dash.
- **Break-even of infinity is a finding, not an error.** If costs consume all
  revenue, no bid strategy can be profitable, and the tool says that before
  offering any optimisation advice.
- **Scenario maths is constant-efficiency.** The +1,000 revenue scenario assumes
  the same margin at the new volume. It is labelled as an assumption, because
  assuming otherwise would be inventing a result.

## Open questions

- The 15% headroom on target ROAS is a convention with no external authority
  behind it. It is exposed in the output text so a reader can substitute their
  own.
- The tool does not model attribution windows. A figure taken from a short
  conversion window and a figure taken from a 30-day window are not comparable,
  and no tool can reconcile that for you.