As of 13 August 2026, AI can calculate your paid advertising ROAS.
Most people should hand this to a purpose-built tool.
Can you do it?
5 minutesto a draft.
15 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsA spreadsheet or analytics setup can calculate the same formula, but no price for that alternative is provided in the supplied data.
If this goes wrong: you compare campaigns using inconsistent attribution or costs and put more budget behind the wrong activity.
What to actually do
Use a tool built for this
The route this page recommends
Do it yourself
Second choiceA chat interface, chat-fluent skill, and roughly 15 minutes until you can act on the result.
How to actually do it
- Open each relevant advertising platform and analytics or sales report, then set the same date range, currency and attribution window for every source.
- Export campaign-level ad spend and the revenue attributed to those campaigns, including campaign names or IDs and any refunds, fees or adjustments that affect your chosen cost definition.
- Write down the attribution model, reporting timezone, date range and whether spend includes platform fees, agency fees, VAT or other costs.
- Paste the exports and that context into the prompt, keeping the column headings and marking unavailable values as missing rather than filling them in.
- Ask the model to calculate campaign and overall ROAS, show the substituted figures, and separate the reported calculation from recommendations.
- Recalculate a sample of campaign rows and the overall result in a spreadsheet using the same numerator, denominator, currency and attribution rules.
- Compare the model's flagged missing, duplicated or refunded figures with the source reports, then use the verified result in your budget decision.
Prompt
Calculate the paid advertising ROAS from the data below. Use this formula: ROAS = attributed revenue divided by ad spend, and also show the result as a percentage where useful. First state exactly which revenue and spend fields you used, the date range, currency, attribution model and any exclusions. If the data mixes currencies, date ranges, attribution models or cost definitions, stop and list the inconsistency instead of combining it. Do not invent missing values. Produce a table for each campaign and an overall result, showing the formula with the substituted figures and the arithmetic. Flag campaigns where revenue or spend is missing, duplicated, zero, refunded, or not comparable. Separate reported ROAS from any interpretation about performance. Data: [paste your exported advertising spend and attributed revenue data here]. Context: [platforms, date range, currency, attribution model, and any costs that should or should not be included].
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
Hand it to a person
The distant thirdA person who owns the outcome does this end to end, worth it when the failure is dear.
What it gets wrong
- It cannot decide whether platform-reported revenue is genuinely incremental or merely attributed by the platform's chosen model.
- It cannot resolve conflicting definitions of revenue, spend, fees, VAT, refunds or customer lifetime value without your business context.
- It cannot detect a tracking implementation problem that is absent from the data you provide.
- It cannot decide how much confidence to place in a small or biased dataset when allocating budget.
- It can produce a neat comparison that looks precise even when the campaigns are not comparable.
Even on a YES, the friction has a name: judgement under ambiguity, context depth and stakes of error.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 2 |
| Liability | 2 |
| Effort delta | 2 |
| Total | 10 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT calculate my ROAS?
- Yes. Give it campaign spend, attributed revenue, the date range, currency and attribution model, and ask it to show the arithmetic. Check the result against the original platform reports before changing your budget.
- What data do I need to calculate paid advertising ROAS?
- You need ad spend and attributed revenue for the same campaigns and reporting period. Also provide the currency, attribution window, reporting timezone and whether fees, VAT, refunds or agency costs are included.
- What is a good ROAS for paid ads?
- There is no universal threshold. It depends on your gross margin, fulfilment costs, repeat purchases, fees and business objective, so compare the result with the break-even ROAS for your own offer rather than a generic benchmark.
- Can AI tell me which ad campaign to spend more on?
- It can rank campaigns using the figures you provide, but it cannot establish that the highest reported ROAS caused the sales or will continue at the same level. Check tracking, conversion volume, margins and attribution before reallocating budget.
Nearby answers
- Can AI build a landing page for my paid ad campaign?YES
- Can AI calculate how much I should spend on paid ads?PARTLY
- Can AI choose audience targeting for my paid ads?PARTLY
- Can AI choose keywords for my Google Ads?PARTLY
- Can AI choose the best paid ad platform for my business?PARTLY
- Can AI create a paid ads report for my business?YES
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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