Google Ads AI teammate that catches wasted spend before it hurts
An AI teammate that watches your Google Ads every day, flags spend anomalies, and sends you a summary with what to do next.
Works with
Google Adsand 70+ other apps
Stop finding problems too late
Daily monitoring that catches spend issues before they become expensive mistakes.
Daily spend monitoring
Your teammate checks every campaign daily. If spend spikes or conversions drop, you hear about it within hours.
You stay in control
The teammate finds problems and recommends fixes. You approve before anything changes.
Works across multiple accounts
Same monitoring templates, different thresholds per account. Built for agencies and multi-brand teams.
Clear, actionable reports
Every report shows what moved, why it probably moved, and what to do about it.
Search term cleanup
Finds search terms wasting your budget and recommends negative keywords to add. Weekly, on autopilot.
Connect Google Ads and get your first daily summary tomorrow.
Start freeLive in 10 minutes
Connect your account, set your limits, and get your first summary tomorrow.
Connect Google Ads
One-click OAuth. Read-only to start.
Set your budget limits
Tell it what normal spend looks like for each campaign.
Choose how to get alerts
Slack, email, or both. Daily or instant for big issues.
Review and tune weekly
Check what it caught. Adjust thresholds until the signal is right.
Budget guardrails that actually work
Set spend limits by campaign. Get alerted when something looks off. No more surprise invoices.
Spend rules per campaign
Set what normal looks like for each campaign. Get flagged when it drifts.
- Daily spend pace thresholds
- CPA and conversion rate bounds
- Different rules for brand vs. non-brand
Smart alerts, not noise
Only get notified when something actually needs your attention.
- Suppresses normal fluctuations
- Includes probable cause with every alert
- Routes to the right person automatically
Gets smarter every week
Review what it caught. Adjust thresholds. Fewer false positives over time.
- Track alert accuracy over time
- Tune one threshold at a time
- Promote proven workflows to new accounts
What teams use it for
Real workflows from agencies and in-house teams.
Catch spend anomalies across accounts
Agency team monitoring 12 client accounts from one dashboard.
— Monitor all Google Ads accounts daily. Flag any campaign where spend is 30%+ above the 7-day average while conversions are flat or down. Send a Slack summary by 9am.
Caught a $2,400/day overspend on a client's Performance Max campaign before the weekly call.
Weekly wasted spend cleanup
Growth team running 40+ ad groups across 3 products.
— Every Friday: pull search terms from all active campaigns. Find terms with 50+ clicks and zero conversions. Recommend negative keywords with estimated monthly savings.
Saved $3,200/month in wasted spend by adding negative keywords the team had missed for weeks.
Friday optimization prep
Account lead needs a brief before the Monday optimization meeting.
— Friday 4pm: generate a brief with top 5 movers by spend change, pacing risks for the month, and 3 prioritized recommendations for next week.
Monday meetings go from 45-minute data reviews to 15-minute decision sessions.
Pair spend monitoring with Search Console ranking alerts.
Pair with SEOHow it works in practice
Production-grade controls, review loops, and ROI tracking.
Why campaign management turns reactive
Google Ads fails when teams rely on memory, not process. Spend spikes get noticed late, search terms pile up, and team meetings become backward-looking because nobody synthesized account movement before the call.
Reporting latency slows optimization
By the time the weekly report is built and discussed, market conditions have already moved. A Google Ads AI teammate reduces that delay by generating consistent summaries on schedule.
Where teams lose money first
Audits of underperforming accounts surface the same misses repeatedly. None are strategic mysteries. They persist because the operating cadence is fragile.
- Budget pacing drift discovered after overspend already happened.
- Search term waste from delayed negative keyword review.
- Bid and impression-share volatility with no early warning.
- Manual report prep that steals optimization time every week.
Campaign performance monitoring loop
The baseline Google Ads AI workflow starts with daily monitoring across campaign, ad group, and keyword levels. The teammate compares current performance against short and medium baselines to detect meaningful movement without overreacting to noise.
- Pull daily metrics for spend, clicks, conversions, CPA, and impression share.
- Compare movement against rolling 7-day and 28-day baselines.
- Flag significant changes above agreed thresholds.
- Publish a concise action list with priority and owner.
Spend anomaly detection without panic
A strong Google Ads AI tool separates harmless pacing variation from costly anomalies. Explicit thresholds by campaign type ensure branded, non-branded, and performance max campaigns are evaluated with the right expectations.
- Detect sudden spend jumps with weak conversion support.
- Highlight campaigns with widening CPA variance.
- Track impression share losses tied to budget or rank pressure.
- Escalate only when predefined risk conditions are met.
Automated reporting that reads like analysis
The teammate drafts plain-language summaries: what changed, why it likely changed, and what action should happen next. Recurring sections stay stable so historical comparison is easy and new team members onboard quickly.
The teammate operates as a recommendation engine with strict constraints: it analyzes bid pressure and efficiency, but human owners approve changes. Decision context is always visible.
Google Ads bid management with guardrails
The teammate operates as a recommendation engine with strict constraints: it analyzes bid pressure and efficiency, but human owners approve changes. Decision context is always visible.
- Analyze CPA, ROAS, and conversion-rate shifts by segment.
- Suggest bid adjustments with rationale and confidence.
- Route recommendations to approvers before execution.
- Track post-change outcomes to refine future suggestions.
Budget pacing and reallocation insights
The teammate tracks pacing at campaign level and identifies where spend is over-delivering low-intent clicks or underfunding high-intent demand. That insight helps teams reallocate before the month is lost.
- Forecast month-end pacing based on current spend velocity.
- Identify budget caps suppressing high-intent demand.
- Flag campaigns burning budget with poor downstream quality.
- Recommend reallocation scenarios by objective.
Search term and keyword quality control
The teammate reviews search term patterns, identifies waste clusters, and proposes negative keyword opportunities. This keeps quality control consistent even when teams are busy with other priorities.
Google Ads automation rules are condition triggers, not teammates. They execute predefined actions when a threshold is met but do not synthesize cross-signal context or explain tradeoffs. An AI teammate adds that interpretation layer.
Compared with native automation rules
Google Ads automation rules are condition triggers, not teammates. They execute predefined actions when a threshold is met but do not synthesize cross-signal context or explain tradeoffs. An AI teammate adds that interpretation layer.
Compared with custom scripts
Custom scripts solve specific problems but often become brittle as account structure changes. A Google Ads AI teammate is easier to evolve because behavior is defined in workflow instructions and review loops, not code.
Compared with legacy management software
Legacy Google Ads management software is built around static dashboards. Teams still need analysts to interpret movement and draft recommendations. A teammate closes that gap by converting raw metrics into action-ready summaries on schedule.
Start with one outcome: daily anomaly detection, weekly optimization summary, or search term hygiene. Assign one owner and define success metrics before writing instructions.
Week 1: define scope and success metrics
Start with one outcome: daily anomaly detection, weekly optimization summary, or search term hygiene. Assign one owner and define success metrics before writing instructions.
Week 2: run, review, and tighten
Let the teammate run on schedule and review every output. Capture misses by category: data access, threshold logic, or summary clarity. Change one variable at a time.
- Run the workflow daily with a fixed output template.
- Review the output in under 15 minutes.
- Log misses and update one instruction at a time.
- Repeat for five to seven cycles before expanding scope.
Weeks 3-4: expand to adjacent workflows
After the first workflow is reliable, add one adjacent loop. Reuse thresholds and templates whenever possible. Connect the sibling SEO workflow so paid and organic signals inform each other.
Trust comes from repeatable controls, not confident language. Structured outputs, clear escalation logic, and owner review cadence from day one are non-negotiable.
Quality controls that keep trust high
Trust comes from repeatable controls, not confident language. Structured outputs, clear escalation logic, and owner review cadence from day one are non-negotiable.
- Least-privilege access to Google Ads account scopes.
- Documented escalation matrix with owner accountability.
- Weekly quality review with measurable acceptance criteria.
- Run logs and short postmortems for notable misses.
How to measure ROI from a Google Ads AI tool
Track reduced reporting prep time, faster anomaly detection, and improved response time from issue to approved action. On the business side, monitor CPA stability, reduced waste from search term cleanup, and better pacing alignment.
See what your teammate catches in the first week.
Start freeExplore more
- AI teammates hub
See the top-level category framework and rollout model.
- AI marketing teammates hub
Return to the marketing category page and core channel pages.
- SEO teammate page
Connect paid-search operations with Search Console and keyword workflows.
References
- Building effective agents by Anthropic
Anthropic's guide to building reliable AI agent systems.
- Practices for governing agentic AI by OpenAI
OpenAI's framework for safe AI agent operations.
- The next chapter of AI agents by Google Cloud
Google Cloud's vision for production AI agent infrastructure.
- Google Ads Help Center
Official Google Ads documentation for campaign setup and optimization.
FAQ
Thresholds, governance, and multi-account scaling.
Start watching your Google Ads today
Free to start. Connect your account and get your first daily summary tomorrow.