Strategy

Is my Google Ads spend adding leads beyond what Google Maps brings?

Lines up 6 months of Business Profile actions and search terms against Google Ads spend, conversions and search terms. Estimates how much paid spend looks incremental and which paid terms cover searches your free listing misses. Read-only.

When to use it

When you run a local business and wonder whether Google Ads brings customers beyond what your free Google Maps listing already delivers.

What you get

A verdict with an estimated range of incremental ad spend, which paid terms to keep funding and a simple incrementality test to run later.

Does it change anything in my account?

No. The assistant only reads your data and reports back.

Works with

Google Ads, Business Profile

Fill in before sending

[business location][max amount to shift]

I run a local business at [business location]. I want to know whether my Google Ads budget brings customers I would not get from my free Business Profile listing anyway. Use the last 6 months. 1. Business Profile actions by month. Find my location with gbp_list_locations. gbp_insights only returns a total for the last N days, so call it six times with days=30, 60, 90, 120, 150 and 180. Subtract each total from the next one to get calls, direction requests and website clicks for each 30-day block. Label the blocks by date range, not calendar month. 2. Business Profile search terms. Pull the terms people used to find the listing with gbp_search_keywords, covering the last 6 months. This data lags about 2 months, so state which months it actually covers. 3. Google Ads by the same blocks. Pull spend, clicks, conversions and cost per conversion for the last 180 days. Use performance_report at campaign level with a monthly segment if it supports one. Otherwise use google_ads_query with date ranges that match the six 30-day blocks from step 1. Pull search terms for the same 180 days with search_terms_report, and read campaign targeting (locations and radius) with get_campaign_targeting. 4. Put both sources in one table with one row per 30-day block: Profile calls, directions, website clicks, Ads spend, Ads clicks, Ads conversions. Note whether blocks with higher ad spend show higher total actions (Profile plus Ads), or whether Profile actions drop when Ads rise, which would suggest ads are taking credit for customers who would have found me anyway. 5. Compare the Profile search terms with the paid search terms, using only the months both sources cover. List: - paid terms that already bring strong Profile impressions (likely overlap) - paid terms where the Profile does not appear at all (likely incremental) - paid terms that convert but fall outside my targeted locations or radius, if any. Deliver a short verdict: - An estimated range for the share of ad spend that looks incremental. Say plainly that this comes from correlation over 6 blocks, not proof. - Which paid terms to keep funding: the ones the Profile does not cover. - Whether part of the budget, up to [max amount to shift], would be better spent elsewhere. - A simple test I could run later to measure true incrementality, for example pausing the overlapping terms for a few weeks and watching Profile actions. Describe it only, do not set it up. This is analysis only. Do not change any campaign or the Business Profile.

I run a local business at [business location]. I want to know whether my Google Ads budget brings customers I would not get from my free Business Profile listing anyway. Use the last 6 months.

1. Business Profile actions by month. Find my location with gbp_list_locations. gbp_insights only returns a total for the last N days, so call it six times with days=30, 60, 90, 120, 150 and 180. Subtract each total from the next one to get calls, direction requests and website clicks for each 30-day block. Label the blocks by date range, not calendar month.
2. Business Profile search terms. Pull the terms people used to find the listing with gbp_search_keywords, covering the last 6 months. This data lags about 2 months, so state which months it actually covers.
3. Google Ads by the same blocks. Pull spend, clicks, conversions and cost per conversion for the last 180 days. Use performance_report at campaign level with a monthly segment if it supports one. Otherwise use google_ads_query with date ranges that match the six 30-day blocks from step 1. Pull search terms for the same 180 days with search_terms_report, and read campaign targeting (locations and radius) with get_campaign_targeting.
4. Put both sources in one table with one row per 30-day block: Profile calls, directions, website clicks, Ads spend, Ads clicks, Ads conversions. Note whether blocks with higher ad spend show higher total actions (Profile plus Ads), or whether Profile actions drop when Ads rise, which would suggest ads are taking credit for customers who would have found me anyway.
5. Compare the Profile search terms with the paid search terms, using only the months both sources cover. List:
   - paid terms that already bring strong Profile impressions (likely overlap)
   - paid terms where the Profile does not appear at all (likely incremental)
   - paid terms that convert but fall outside my targeted locations or radius, if any.

Deliver a short verdict:
- An estimated range for the share of ad spend that looks incremental. Say plainly that this comes from correlation over 6 blocks, not proof.
- Which paid terms to keep funding: the ones the Profile does not cover.
- Whether part of the budget, up to [max amount to shift], would be better spent elsewhere.
- A simple test I could run later to measure true incrementality, for example pausing the overlapping terms for a few weeks and watching Profile actions. Describe it only, do not set it up.

This is analysis only. Do not change any campaign or the Business Profile.

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StrategyChanges after your approval

Shift budget between Google Ads and Meta based on 30-day CPA

A single campaign table across Google Ads and Meta and a line-by-line budget reallocation plan built on a clear CPA rule.

When to use itWhen one platform is clearly cheaper per conversion than the other and you need to decide where your monthly budget should go.

Compare my Google Ads and Meta campaigns over the last 30 days and tell me where my budget should move. My monthly ad budget is [monthly budget] and my target cost per conversion is [target CPA].

1. For every active campaign on both platforms, pull spend, conversions, cost per conversion, conversion rate and current daily budget. Use the same date range for both platforms.
2. Build one table sorted by cost per conversion. Include each campaign's share of total spend and its share of total conversions.
3. Mark any campaign with fewer than 10 conversions as "low confidence" and do not move its budget yet.
4. For Google Search campaigns, add impression share lost to budget.

Decision rule:
- A campaign with at least 10 conversions and a CPA more than 30% above target loses budget.
- A campaign below target CPA that loses more than 20% impression share to budget, or is a Meta ad set spending its full budget, gains budget.
- Never change any single budget by more than 20% in one step.

Deliver a reallocation table with these columns: campaign, platform, current daily budget, proposed daily budget, reason. Do not change anything yet. I will mark which lines I accept. Then show me a preview of those exact changes and wait for my confirmation before you apply them.

StrategyChanges after your approval

Month-end pacing check across Google Ads and Meta

A projection of total month-end spend against your monthly budget, plus a previewed rebalance that lands total spend within 5% of target.

When to use itWhen the month is half over and you want to be sure your ads will not overspend or underspend your fixed monthly budget.

I have a fixed monthly ad budget of [monthly budget] split across Google Ads and Meta. Check whether I will land on it this month.

1. Run budget pacing for Google Ads. Note which campaigns will overspend and which will underspend by month-end.
2. Pull Meta spend month-to-date for each campaign and ad set, along with their current daily budgets. Project month-end spend at the current daily rate.
3. Show one table with these columns: campaign/ad set, platform, spend so far, projected month-end spend, current daily budget, cost per conversion this month. Add the projected combined total versus my budget.

If the projected total is off by more than 5%, propose new daily budgets for the remaining days that bring it back within 5%. Follow these rules when you rebalance:
- Take money first from campaigns whose cost per conversion is above [target CPA].
- Add money first to campaigns with the lowest cost per conversion that are not already spending their full budget.
- Do not cut any campaign by more than 30%.

List each proposed change with the old value, the new value and the reason. Preview all changes and wait for my approval before applying anything.

StrategyRead-only

Check that conversions are comparable before moving budget between channels

A trust table that compares platform-reported conversions to GA4 and shows each channel's comparable cost per conversion.

When to use itWhen Google Ads, Meta and GA4 report very different conversion numbers and you do not know which one to trust before comparing channels.

Before I move any money between Google Ads and Meta, I need to know whether their conversion numbers can be compared at all. Use the last 30 days.

1. Google Ads: audit conversion tracking health. List the primary conversion actions with their counting type (every or one), click-through and view-through lookback windows, and attribution model.
2. Meta: list the pixels with their last fired time, the custom conversions, and the conversion events my campaigns optimize for. Note that Meta's default attribution includes view-through conversions.
3. GA4: pull key events by session source/medium for the same 30 days. Confirm which key events correspond to the platform conversions.
4. Build a table per channel with these columns: platform-reported conversions, GA4 key events from that channel, ratio, spend, platform CPA, GA4-based CPA.

Flag every issue that inflates or hides results:
- Counting set to "every" on lead actions.
- Duplicate or secondary actions being counted.
- A pixel that has not fired in 24 hours.
- A platform-to-GA4 ratio above 1.5.

Finish with a clear answer: which CPA should I use to compare channels, and what must be fixed first. Do not change any setting. If a fix is needed, describe it and I will ask for a preview separately.

StrategyRead-only

New client onboarding: one-page competitive landscape brief

A one-page brief mapping who advertises in the client's market, where, with what message, and where the client stands today.

When to use itWhen you are about to start with a new client and need to understand who they compete against in paid and organic search before the kickoff call.

We are onboarding [client name] (domain [client domain], Google Ads account [account]). Build a competitive landscape brief before our kickoff call.

1. Get an account snapshot so we know current spend, conversions and active campaign types.
2. Run a live SERP analysis for the client's 5 most important commercial queries: [5 core queries]. Record which domains show in paid positions and which show in the top 5 organic results.
3. Take the 4 domains that appear most often in paid positions. For each one, pull its paid keyword footprint (keyword count and estimated paid traffic) and its live ads from public ad libraries.
4. Run a keyword gap between the client domain and those 4 competitors.

Deliverable, one page:
- competitor table with these columns: domain, paid presence (queries appeared on out of 5), organic presence, estimated paid keyword count, channels with live ads, main message
- where the client is stronger, where it is weaker and where it is absent
- 5 prioritized questions to ask the client at kickoff, such as margins, which competitor they lose deals to, and which offers they can legally match

Read-only. No changes to the account.