Blended ROAS calculation
Blended ROAS is total revenue divided by total advertising spend across every channel, with no attribution model applied. Because platforms each claim overlapping conversions, summing platform-reported ROAS overstates performance; the blended ratio sidesteps that by working from one revenue figure and one spend figure. It is honest at the top line but cannot tell you which channel earned the return — that still needs attribution or incrementality.
The formula and why it is honest
Blended ROAS = total revenue / total advertising spend, summed across all paid channels for a period. No model, no per-channel credit, no windows.
Its honesty comes from avoiding double-counting: every ad platform credits itself for conversions other platforms also claim, so adding their reported ROAS inflates the total. One revenue number over one spend number cannot double-count.
What it cannot do
The trade-off is resolution. Blended ROAS tells you whether total advertising is paying back overall, but not which channel drove it or how to reallocate — for that you still need attribution (for directional channel splits) and incrementality (for causal contribution).
A common practice is to track blended ROAS as the trustworthy top-line guardrail and use attribution underneath it for relative comparisons, never trusting summed platform claims as the total.
- Formula: total revenue / total ad spend, model-free
- Avoids the double-counting of summed platform ROAS
- Gives no per-channel split — needs attribution beneath it
How it appears in analytics and logs
When summed platform ROAS looks far better than blended ROAS, the platforms are double-counting shared conversions across their walled gardens.
Diagnostic use case
Sanity-check inflated platform-reported returns by computing one model-free ratio of total revenue to total spend.
What WebmasterID can help detect
WebmasterID's first-party revenue-linked events give an independent total-revenue numerator that does not inherit any one platform's self-reported claims.
Common mistakes
- Summing platform-reported ROAS as if it were the total.
- Using blended ROAS to make per-channel budget calls.
- Mixing revenue and spend from mismatched time periods.
Privacy and accuracy notes
Blended ROAS uses aggregate revenue and spend totals, requiring no individual-level tracking. Educational, not legal advice.
Related pages
- Blended vs platform-reported attribution
Blended attribution takes total business results — say, all orders — and relates them to total spend across every channel, ignoring per-platform claims. Platform-reported attribution is what each ad platform credits itself using its own model and self-reporting. Because platforms can double-count and credit non-incremental conversions, summed platform numbers often exceed reality. This page contrasts the two views and where each is useful.
- Marketing ROI vs ROAS
Return on ad spend (ROAS) and marketing return on investment (ROI) are often conflated but measure different things. ROAS is revenue divided by advertising spend — a top-line efficiency ratio. Marketing ROI is profit (or net gain) divided by the full cost of the marketing — a bottom-line return. A campaign can have a high ROAS yet a poor ROI once margins and total costs are included. This page defines both formulas and when each applies.
- Duplicate conversion counting
Duplicate conversion counting happens when a single real conversion is recorded more than once — for example by both a browser pixel and a server event, by a tag firing twice, or by two platforms each claiming it. It silently inflates reported conversions and value, distorts ROAS, and misleads bidding unless deduplication via shared event IDs and clear ownership is in place.
- Attribution analytics
An independent revenue total free of platform claims.
Sources and verification notes
- Google Ads Help — About conversion value and ROASDefines ROAS as conversion value over cost.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.