Paid Ads

Every platform audited. Not a dollar wasted.

Google, Meta, LinkedIn, TikTok, Microsoft, YouTube — nine specialist entities audit tracking, spend, creative, and compliance in parallel, merged into one plan: Critical to Medium.

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Entity Network — ads-orchestrator

Every platform, one turn

Google, YouTube, Meta, LinkedIn, TikTok, Microsoft — nine specialist entities dispatched in parallel, each auditing its own dimension.

Wasted spend, found

Search terms burning budget with zero conversions, duplicate conversions inflating ROAS, broad matches leaking — named with the dollar amount.

Tracking verified first

Pixel health, CAPI coverage, and event match quality audited before anything else. Without trustworthy tracking, every other number is noise.

Creative fatigue watched

Frequency climbing while CTR falls gets flagged per ad, with a refresh recommendation before performance craters.

Negatives mined by N-gram

Search term reports sliced into N-grams — patterns like "free", "jobs", "diy" surface as shared negative lists, ready to apply.

Experiments with rigor

A/B tests designed with sample sizes and significance thresholds up front. Results aren’t called until they clear the bar.

Also in this module
  • LinkedIn · TikTok · Microsoft covered in cross-platform passes — budget, creative, tracking, compliance
  • Ad policy and privacy compliance checked per platform
  • Budget allocation and learning-phase health across accounts
  • Quality loop — every specialist reports PASS or ⚠︎ BLOCKED in a status table, never silence
  • Executive summaries generated C-suite-ready from the findings
  • Every recommendation ships with expected impact and effort
In The Chat

One message.
Every account audited.

Ask for the audit and watch the specialists land their findings in the thread — including the honest ones: a blocked export gets retried and reported, never skipped in silence.

Chat — ads-orchestrator · hivewatch-pest
Audit our paid accounts — Google and Meta first
ads-orchestratorlivequality loop ×3 per specialist
spawn: audit-google74 checks · $1.2k wasted
spawn: audit-metaPixel EMQ 6.2
spawn: audit-trackingCAPI missing on 2
spawn: search-query-analyst312 negatives mined
spawn: audit-creativefatigue scan…
spawn: audit-budgetLinkedIn export · retry 2/3
Unified plan ready
$1,240/mo wasted
19findings
5critical
Top finding: "pest jobs" burned $214 with 0 conversions — negative list ready
🛡Apply 312 negatives to Google Ads?ApproveDeny
Ask anything…
Google Ads

Where the budget leaks,
to the dollar.

Seventy-four checks across conversion tracking, wasted spend, Quality Score, PMax, and account structure — every finding tied to the search terms and dollars behind it.

Google Ads Audit — hivewatch-pest
$1,240/mo wasted spend
5.8avg Quality Score
74checks run
Conversion tracking — 2 duplicate conversions inflating ROAS
PMax — asset groups missing video, search themes too broad
Ad assets — sitelinks, callouts, and calls present
Top wasted search terms
Search termSpendConvAction
pest control jobs$2140+ negative
free pest inspection$1180+ negative
how to get rid of ants yourself$960+ negative

The wasted spend is already there. Find it this week.

First audit: every platform, one plan.

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Meta Ads

Fatigue caught
before the CTR craters.

Pixel and CAPI health scored, frequency and CTR trends watched per creative, Advantage+ and audience overlap verified — the ad that needs a refresh gets named, not guessed.

Meta Audit — hivewatch-pest
6.2/10Pixel EMQ score
3.4avg frequency
−32%CTR trend · 14d
Creative fatigue
"Summer Pest Special" — videofreq 4.1 · CTR −32% · 21 days live
refresh
"Same-Day Treatment" — staticfreq 2.1 · CTR steady · 9 days live
healthy
CAPI not configured — events rely on browser pixel only
Advantage+ shopping active · audience overlap under 12%
Search Queries

Your search terms,
sliced into signal.

N-gram analysis turns thousands of raw queries into patterns: what converts gets bid up, what burns gets a shared negative list — exported to Google and Microsoft, ready to apply.

Search Queries — N-gram Analysis · hivewatch-pest
N-gramQueriesSpendConv rateAction
"near me"42$8608.2%↑ bid up
"emergency"27$5406.7%↑ bid up
"free"18$3120%+ negative
"jobs" / "hiring"11$2140%+ negative
"diy" / "yourself"9$960%+ negative
312 negatives readygrouped into 4 shared lists · Google + MicrosoftExport to Google Ads →
Experiments

Decisions from significance,
not from noise.

Creative, bidding, audience, and landing page tests designed with sample sizes up front and called only when the numbers clear the threshold. No peeking, no false winners.

Experiments — hivewatch-pest
Headline test — /pest-treatment landing pagesignificant — ship B
Variant A4.1%
Variant B5.6%
confidence 96% · 4,120 sessions · 18 days
Bidding test — tCPA vs maximize conversionscollecting
needs 340 more conversions — no peeking
FAQ

Straight answers

Which platforms does it cover?

Google Ads and YouTube, Meta (Facebook/Instagram), LinkedIn, TikTok, and Microsoft Ads. Google and Meta get dedicated specialist entities; LinkedIn, TikTok, and Microsoft are covered by cross-platform passes for budget, creative, tracking, and compliance.

Does it launch campaigns or just audit?

Both directions: audits and optimization plans arrive prioritized, and the strategist entity builds campaign and media plans. Anything that changes a live account sits behind your approval gate.

How are findings prioritized?

Critical → High → Medium, always with expected impact and effort attached. Cross-platform synthesis catches what single-platform views miss — like budget concentrated on a platform with broken tracking.

What happens if a platform export fails?

The quality loop retries up to three times with corrective feedback. If it still fails, that specialist is marked BLOCKED in the status table with the reason — never silently skipped.

How are experiments validated?

Sample size and significance thresholds are set before the test starts, and results aren’t called until they’re met. The experiment tracker exists precisely to stop decisions based on noise.

Isn’t auditing six platforms expensive to run?

Not the way entities do it. Exports, N-gram slicing, and metric crunching run in plain code — specialists spend tokens on judgment, not on reading raw search term reports. A fraction of what a browser agent burns clicking through the same accounts.

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