Optimization

Right-size your radius targeting using Business Profile and Ads data

Checks whether a campaign's radius center matches the Business Profile address, groups conversions into distance bands (exact where Google provides distance data, clearly labeled as approximate otherwise) and proposes the smallest radius that keeps most conversions.

When to use it

When your local campaign targets a radius around your shop and you suspect you are paying for clicks too far away or the center point is wrong.

What you get

A distance-band table with spend, conversions and cost per conversion, a proposed smaller radius that keeps about 85% of conversions, and a previewed proximity update awaiting your confirmation.

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, Business Profile

Fill in before sending

[campaign name][target CPA]

Check whether the radius targeting on my Google Ads campaign [campaign name] fits where my customers actually are. 1. Read my business address from Google Business Profile, then pull the profile's insights for the last 90 days: calls, direction requests and website clicks. Use these totals as context for how much local demand comes through the listing itself. 2. Read the campaign's current proximity targeting: center latitude and longitude, radius and units. Tell me, as best you can, which area the center falls in and whether that looks consistent with the Business Profile address. There is no geocoding tool, so if a center correction might be needed, ask me for the business coordinates (copied from Google Maps) before proposing a new center. 3. Pull distance data for the last 90 days: - First try a GAQL query on distance_view for this campaign (segments.distance_bucket) with cost, clicks, conversions and cost per conversion. This works when location assets from Business Profile are linked to the account. If it returns data, group the buckets into 0-5 km, 5-10 km, 10-20 km and 20+ km. - If distance_view returns nothing, query user_location_view (or geographic_view) by city or district instead, resolve the location names with geo_target_search, and assign each one to an approximate band based on its distance from the business. Label these bands as approximate and list every location with its assigned band so I can correct any mistakes. 4. Show a table by distance band with spend, spend share, conversions, conversion share and cost per conversion. Decision rule: recommend the smallest radius that keeps about 85% of conversions. Keep an outer band if its cost per conversion is below [target CPA], even if its volume is small. If the center is off and I have given you the correct coordinates, propose moving it there. Show the current and proposed radius side by side, with the share of past spend and conversions that falls inside the proposed radius. Then prepare the change with manage_campaign_proximity (action update, confirm=false), show me the preview and wait for my confirmation before changing the proximity target.

Check whether the radius targeting on my Google Ads campaign [campaign name] fits where my customers actually are.

1. Read my business address from Google Business Profile, then pull the profile's insights for the last 90 days: calls, direction requests and website clicks. Use these totals as context for how much local demand comes through the listing itself.
2. Read the campaign's current proximity targeting: center latitude and longitude, radius and units. Tell me, as best you can, which area the center falls in and whether that looks consistent with the Business Profile address. There is no geocoding tool, so if a center correction might be needed, ask me for the business coordinates (copied from Google Maps) before proposing a new center.
3. Pull distance data for the last 90 days:
   - First try a GAQL query on distance_view for this campaign (segments.distance_bucket) with cost, clicks, conversions and cost per conversion. This works when location assets from Business Profile are linked to the account. If it returns data, group the buckets into 0-5 km, 5-10 km, 10-20 km and 20+ km.
   - If distance_view returns nothing, query user_location_view (or geographic_view) by city or district instead, resolve the location names with geo_target_search, and assign each one to an approximate band based on its distance from the business. Label these bands as approximate and list every location with its assigned band so I can correct any mistakes.
4. Show a table by distance band with spend, spend share, conversions, conversion share and cost per conversion.

Decision rule: recommend the smallest radius that keeps about 85% of conversions. Keep an outer band if its cost per conversion is below [target CPA], even if its volume is small. If the center is off and I have given you the correct coordinates, propose moving it there.

Show the current and proposed radius side by side, with the share of past spend and conversions that falls inside the proposed radius. Then prepare the change with manage_campaign_proximity (action update, confirm=false), show me the preview and wait for my confirmation before changing the proximity target.

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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.