Optimization

Google Ads experiments readout: declare winners and end losers

Compares the base and trial campaigns of every running and recent Google Ads experiment, gives a winner, loser or inconclusive verdict against your KPI and prepares the end actions for your approval.

When to use it

When you have Google Ads experiments running or recently finished and need to know which ones won, which lost and which are just burning traffic.

What you get

A base vs trial table for each experiment with a winner, loser or inconclusive verdict, days still needed for inconclusive tests, and a previewed list of experiments to end awaiting your approval.

Does it change anything in my account?

Only with your approval. The assistant first shows a preview of every change and waits for your go-ahead.

Works with

Google Ads

Fill in before sending

[account name][CPA or ROAS][30]

Review the campaign experiments in Google Ads account [account name]. My primary KPI is [CPA or ROAS]. 1. Find the customer_id for [account name] with list_accounts. Run list_experiments (action list) and keep the experiments that are running or ended in the last [30] days. Note each one's id, type, start and end dates and the campaigns it locks. 2. Map the arms. Each experiment has a base (control) campaign and a trial campaign. If list_experiments does not make clear which is which, run a GAQL query on experiment_arm (experiment_arm.name, experiment_arm.control, experiment_arm.campaigns, experiment_arm.traffic_split) to identify them. 3. Pull metrics per arm with google_ads_query on the campaign resource, filtered to the base and trial campaign ids and to segments.date between the experiment's start date and its end date (or yesterday if still running): metrics.cost_micros, metrics.clicks, metrics.conversions, metrics.conversions_value. Calculate cost per conversion, ROAS (conversion value / cost) and conversion rate (conversions / clicks) yourself. If a query fails or an arm returns no rows, say so for that experiment instead of guessing. Return one table per experiment with both arms, the % difference for each metric, the days run, the traffic split and a verdict based on these rules: - Winner: the trial beats the base on my primary KPI by at least 10%, the test ran 14+ days, and each arm has 30+ conversions. - Loser: the trial is 10%+ worse under the same volume conditions. - Inconclusive: any other result. Using the current daily conversion pace of the slower arm, estimate how many more days are needed to reach 30 conversions per arm. Flag experiments that have run for more than 6 weeks without reaching the volume threshold. They are wasting the traffic split. For winners, write a one-line recommendation I can act on in the interface (apply the change to the base campaign, or promote). Do not promote anything. For losers and stale tests, propose ending them. Do not end anything yet. Run list_experiments with action end and confirm=false for each one as a preview, show me the exact list with experiment ids and the campaigns that will be unlocked, and wait for my approval before calling it with confirm=true.

Review the campaign experiments in Google Ads account [account name]. My primary KPI is [CPA or ROAS].

1. Find the customer_id for [account name] with list_accounts. Run list_experiments (action list) and keep the experiments that are running or ended in the last [30] days. Note each one's id, type, start and end dates and the campaigns it locks.

2. Map the arms. Each experiment has a base (control) campaign and a trial campaign. If list_experiments does not make clear which is which, run a GAQL query on experiment_arm (experiment_arm.name, experiment_arm.control, experiment_arm.campaigns, experiment_arm.traffic_split) to identify them.

3. Pull metrics per arm with google_ads_query on the campaign resource, filtered to the base and trial campaign ids and to segments.date between the experiment's start date and its end date (or yesterday if still running): metrics.cost_micros, metrics.clicks, metrics.conversions, metrics.conversions_value. Calculate cost per conversion, ROAS (conversion value / cost) and conversion rate (conversions / clicks) yourself. If a query fails or an arm returns no rows, say so for that experiment instead of guessing.

Return one table per experiment with both arms, the % difference for each metric, the days run, the traffic split and a verdict based on these rules:
- Winner: the trial beats the base on my primary KPI by at least 10%, the test ran 14+ days, and each arm has 30+ conversions.
- Loser: the trial is 10%+ worse under the same volume conditions.
- Inconclusive: any other result. Using the current daily conversion pace of the slower arm, estimate how many more days are needed to reach 30 conversions per arm.

Flag experiments that have run for more than 6 weeks without reaching the volume threshold. They are wasting the traffic split.

For winners, write a one-line recommendation I can act on in the interface (apply the change to the base campaign, or promote). Do not promote anything.

For losers and stale tests, propose ending them. Do not end anything yet. Run list_experiments with action end and confirm=false for each one as a preview, show me the exact list with experiment ids and the campaigns that will be unlocked, and wait for my approval before calling it with confirm=true.

Open in Claude Open in ChatGPT Discuss in the forum

More prompts

OptimizationChanges after your approval

Find search terms that waste budget and turn them into negatives

Combines smart negative suggestions with the full search terms report to flag zero-conversion and overpriced terms, then previews a grouped batch of negatives that protects your brand and converting keywords.

When to use itWhen your Google Ads search terms report shows money going to irrelevant or expensive searches and you want to cut that waste safely.

Review the search terms in my Google Ads account [account name] for the last 30 days. Use the smart negative keyword suggestions and the full search terms report together. My brand name and its common spellings are: [brand terms].

Flag two groups:
1. Terms that spent more than [spend threshold] with zero conversions.
2. Terms with exactly one conversion where the cost of that term is above 2x my target CPA of [target CPA]. Calculate this yourself from the cost and conversions in the search terms report.

Skip any term the report lists under already_negative, and check my existing negatives (including shared lists) so you never propose a duplicate.

For the matched keyword, query search_term_view with the keyword segment. If that field does not come back for a term, write "not available" instead of guessing.

Give me one table sorted by cost, highest first. Columns: search term, campaign, ad group, matched keyword, clicks, cost, conversions, recommended negative, match type, level (campaign or ad group).

Decision rules:
- Use exact match for one-off variants.
- Use phrase match when the same unwanted word appears in several terms, for example "free", "jobs" or "DIY".
- Pull my converting keywords from the keyword report. Never suggest a negative that would block one of them or any of my brand terms.
- If a term is relevant but simply expensive, list it separately as a bid or ad copy issue, not as a negative.

End with the estimated monthly savings. Use the last 30 days of cost from the terms you would block as the estimate, and say that this is an upper bound. Then show a preview of the negatives you would add, grouped by campaign, as one batch per campaign. Wait for my approval before adding anything.

OptimizationChanges after your approval

Block searches for places outside your service area

A list of search terms mentioning locations you do not serve, the location setting that lets them in, and a previewed fix for both.

When to use itWhen you suspect your ads are showing and costing money for searches from cities or areas you do not serve.

OptimizationChanges after your approval

Month-end budget pacing check across all client accounts

Runs pacing on every connected client account, compares projected month-end spend with each client's agreed monthly cap, and proposes CPA-ranked daily budget changes within guardrails, approved account by account.

When to use itWhen you manage several client accounts and need to know before month-end who is overspending or underspending against the agreed budget.

List my connected Google Ads client accounts (include client accounts under my manager account) and run a budget pacing check on each one for the current month, passing each account's id directly. The monthly caps agreed with each client are: [account name: monthly budget list]. Skip any account that is not on this list and tell me which ones you skipped.

For each account, take month-to-date spend per campaign from a campaign-level performance report for this month, and the daily budget and pace from the pacing check. Calculate projected month-end spend as spend to date plus current daily budget times the days remaining. Add the campaigns up to get the account total and compare it with the client's cap.

Deliver one table sorted by risk. Include these columns:
- account
- campaign
- daily budget
- spend to date
- projected month-end spend
- account variance vs the monthly cap, as an amount and as a %
- flag

Use these flag rules, at account level:
- OVER: projected spend is more than 5% above the cap.
- UNDER: projected spend is more than 10% below the cap.
- ON TRACK: everything else.

For every campaign in a flagged account, add month-to-date conversions and cost per conversion. This shows whether the underspend is worth fixing.

Then, for each flagged account, propose new daily budgets based on the days remaining. The goal is to land total spend within ±3% of the cap by month-end. When adding budget, prioritise the campaigns with the lowest cost per conversion. When cutting, start with the highest. Respect the budget guardrails: no single increase above +50%, no more than +100% within 24 hours, no cut deeper than -80%. If the target cannot be reached within those limits, say so and suggest a second step later in the week or a pause instead.

Show the proposal as a before/after table per account, then a preview of the changes. Wait for my approval account by account before changing any budget. Do not touch bidding strategies or targets.

OptimizationChanges after your approval

Shift budget from rank-limited to budget-limited Search campaigns

A budget-neutral reallocation plan that moves money to Search campaigns losing impression share to budget at an acceptable CPA.

When to use itWhen some Search campaigns run out of budget and miss impressions while others underspend or cost too much per conversion.

In [client account], analyse all Search campaigns for the last 30 days. Target cost per conversion for this client is [target CPA].

1. Run an impression share analysis. Put each campaign in one bucket: mainly losing to budget, mainly losing to rank, or not limited.
2. Add cost, conversions, cost per conversion and current daily budget for each campaign.

Decision rules:
- A campaign RECEIVES budget only if both are true:
  - search impression share lost to budget is above 10%
  - cost per conversion is at or below target
- A campaign DONATES budget if either is true:
  - it spends less than 85% of its daily budget
  - its cost per conversion is more than 30% above target
- Rank-limited campaigns get no extra budget. List them separately. Use keyword Quality Score data to say whether the main fix is bids or Quality Score.

Deliver:
- a table of all campaigns with bucket, metrics and verdict (receive / donate / hold)
- a reallocation plan that keeps total daily budget unchanged, with no single campaign changed by more than 30%

Show the before/after budgets. Wait for my approval before applying any change.