Strategy

Map competitors' live ad offers and find your positioning gap

Pull local competitors' live Google and Meta ads, map their offers, urgency claims, trust signals and CTAs, compare them with your own RSA copy and find the claims you can own.

When to use it

When local competitors are winning clicks and you want to see what they actually offer and claim in their ads so you can find a gap to own.

What you get

A competitor table of live Google and Meta ads (offers, urgency, trust signals, CTAs) compared with your own RSA copy, ending in table-stakes claims, claims you can own and offers not to match.

Does it change anything in my account?

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

Works with

Google Ads, Meta Ads, SEO Intelligence

Fill in before sending

[3-5 competitor domains or brand names][city or district]

Use the public ad libraries to research how my local competitors advertise. Competitors: [3-5 competitor domains or brand names]. Service area: [city or district]. For each competitor, run competitor_ads on platform google and on platform meta (Meta needs my connected Meta account), with region set to my market. Optionally, if I have SEO add-on credits, check seo_history and then run seo_paid_keywords for each competitor domain to get the headlines and descriptions they run on Google Search and the landing pages they send clicks to. Give me one table with these columns: - platform - live ads returned (say if the result hit the limit, so the count is a minimum) - start date of the oldest active ad, only if the library returns dates; otherwise write "not shown" - main offer (free quote, discount, fixed price, free inspection) - urgency claims (24/7, same day, "arrives in X minutes") - trust signals stated in the ad copy (years in business, licences, review counts, guarantees). Only record what the ads actually say; do not look up or estimate review counts - call to action (call, form, WhatsApp, booking), from the CTA button or the copy Leave a cell as "not in library data" rather than guessing. Then read my active Google Ads responsive search ads: find them with list_entities (entity ads), read the copy with get_ad_details, and use rsa_asset_performance to see which of my headlines and descriptions actually earn clicks and conversions. Compare my claims with theirs. Finish with three short lists: 1. Claims every competitor makes. These are table stakes, so flag any I am missing. 2. Two or three claims nobody makes that I could credibly own, and the proof I would need to back each one up. 3. Competitor offers I should not match, and why (margin, capacity, or risk of attracting bad leads). This is read-only research. Do not change anything in my account.

Use the public ad libraries to research how my local competitors advertise. Competitors: [3-5 competitor domains or brand names]. Service area: [city or district].

For each competitor, run competitor_ads on platform google and on platform meta (Meta needs my connected Meta account), with region set to my market. Optionally, if I have SEO add-on credits, check seo_history and then run seo_paid_keywords for each competitor domain to get the headlines and descriptions they run on Google Search and the landing pages they send clicks to.

Give me one table with these columns:
- platform
- live ads returned (say if the result hit the limit, so the count is a minimum)
- start date of the oldest active ad, only if the library returns dates; otherwise write "not shown"
- main offer (free quote, discount, fixed price, free inspection)
- urgency claims (24/7, same day, "arrives in X minutes")
- trust signals stated in the ad copy (years in business, licences, review counts, guarantees). Only record what the ads actually say; do not look up or estimate review counts
- call to action (call, form, WhatsApp, booking), from the CTA button or the copy

Leave a cell as "not in library data" rather than guessing.

Then read my active Google Ads responsive search ads: find them with list_entities (entity ads), read the copy with get_ad_details, and use rsa_asset_performance to see which of my headlines and descriptions actually earn clicks and conversions. Compare my claims with theirs. Finish with three short lists:
1. Claims every competitor makes. These are table stakes, so flag any I am missing.
2. Two or three claims nobody makes that I could credibly own, and the proof I would need to back each one up.
3. Competitor offers I should not match, and why (margin, capacity, or risk of attracting bad leads).

This is read-only research. Do not change anything in my account.

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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.