1. Overview
Weekly Google Ads audits are essential for catching performance issues early, maintaining optimization discipline, and ensuring consistent execution across multiple accounts. However, manual audits require PMs to open Google Ads, navigate multiple views, pull week-over-week data, and write summary insights—often across a long list of client accounts.
To solve this, I built a one-click weekly audit automation that pulls performance data from Google Ads, evaluates 20+ account health KPIs, flags risks and opportunities using rule-based thresholds, and sends PMs a formatted weekly audit report automatically. This gave PMs consistent insights at scale without spending time inside interfaces.
2. Background & Context
The agency managed multiple Google Ads accounts across different business models and budgets, including:
◉ Lead generation (consultation forms, calls, WhatsApp)
◉ E-commerce (purchase-focused performance)
◉ Local services (geo + schedule constraints)
◉ Multi-campaign structures (Brand / Non-brand / Retargeting / Performance Max)
Before automation, weekly audits involved:
◉ Logging into each account manually
◉ Checking spend pacing, CTR, CPC, conversion rate, CPA/ROAS
◉ Looking for anomalies (spend spikes, volume drops, tracking issues)
◉ Writing a summary for internal follow-up and client reporting
As account volume increased, audit quality and consistency became hard to maintain.
3. Problem Statement
Key operational issues included:
1. Weekly audits were slow and repetitive across many accounts
2. Audit quality varied across PMs and teams
3. Issues like tracking breaks or CPA spikes were detected late
4. Insights were not standardized (too subjective and inconsistent)
5. PM time was spent collecting data instead of taking action
The system needed a reliable method to run the same audit logic across all accounts automatically and deliver PM-ready insights.
4. Tools & Automation Stack
Tech stack & tools used:
◉ Google Ads API (data extraction)
◉ OpenAI API (insight generation from KPI snapshots)
◉ Make.com / Zapier (orchestrating workflows)
◉ Google Sheets (audit log storage and debugging trail)
◉ Slack / Email (delivery channel for weekly reports)
◉ ClickUp (optional: auto-create tasks for critical findings)
5. Automation Flow
The system followed this structure:
1. Weekly scheduler triggers the audit run
2. Automation pulls last 7 days + previous 7 days performance metrics per account
3. System calculates 20+ KPIs and deltas (WoW change)
4. Rule engine flags warnings and critical issues based on thresholds
5. AI generates a PM-friendly audit summary + next actions
6. A formatted report is produced for each account (or grouped by PM)
7. Reports are delivered automatically (Slack/email)
8. If critical → ClickUp task created with the audit summary attached
This created a consistent audit system that ran without manual review.
6. Implementation Details
6.1 KPI Audit Coverage (20+ Checks)
The audit evaluated:
◉ Spend (WoW change)
◉ Clicks (WoW change)
◉ Impressions (WoW change)
◉ CTR and CTR delta
◉ CPC and CPC delta
◉ Conversion volume and delta
◉ Conversion rate and delta
◉ CPA movement (or cost/conv)
◉ ROAS movement (if ecommerce)
◉ Impression share (where applicable)
◉ Lost IS (budget) and delta
◉ Lost IS (rank) and delta
◉ High-spend / low-conversion segments
◉ Search volume drops or spikes
◉ Zero conversion campaigns with non-trivial spend
◉ Conversion tracking health signals (conversion drop-to-zero flags)
◉ Budget utilization patterns (under/over pacing signals)
◉ Top campaign risk flags (largest spend + declining efficiency)
This ensured the audit didn’t rely on one or two headline metrics.
6.2 Rule-Based Flagging Logic (Threshold Examples)
The audit applied consistent rules such as:
◉ CTR drop beyond threshold → Performance drift flag
◉ CPA increase beyond threshold → Efficiency risk flag
◉ Spend up with conversions flat/down → Waste risk flag
◉ Conversions drop near-zero → Tracking or funnel alert
◉ Lost IS (budget) high → Scaling opportunity / budget constraint flag
◉ CPC spike with no efficiency improvement → Auction pressure flag
Each flag produced a severity level (Info / Warning / Critical) and a reason label.
6.2 Rule-Based Flagging Logic (Threshold Examples)
The following prompt powered the summary layer:
You are a senior Google Ads analyst writing a weekly audit for a project manager.
Input includes:
- Current week KPIs
- Previous week KPIs
- Week-over-week deltas
- Flags (Info/Warning/Critical) with reasons
Output requirements:
1) A short performance overview (2–4 lines)
2) A bullet list of critical issues (only if present)
3) A bullet list of opportunities (only if present)
4) A "Next Actions" checklist (max 5 items)
Tone: clear, direct, PM-friendly. Avoid generic advice.
The AI output was designed to be readable in under one minute per account.
6.4 Report Format (Delivered to PMs)
Each account report was structured as:
◉ Account snapshot (spend, conversions, CPA/ROAS, CTR)
◉ Week-over-week movement summary
◉ Alerts (Critical/Warning)
◉ Opportunities (scaling, coverage, efficiency)
◉ Next actions (short checklist)
This ensured the same audit structure across all accounts.
7. Score Mapping / Classification Logic
Accounts were classified into a health status:
| Status | Meaning | Behavior |
|---|---|---|
| Healthy | No material risks detected | Normal monitoring |
| Watchlist | Early warning signals present | Review during weekly optimization |
| Critical | Immediate risk or tracking anomaly | PM alerted + task created |
This allowed PMs to prioritize which accounts needed attention first.
8. ClickUp Automations
Rules used inside ClickUp:
If Status = Critical → Create task in “Urgent” list
If Flag Type = Tracking → Assign to tracking owner + add checklist
If CPA Spike = Critical → Assign to performance lead
If Watchlist persists 2 weeks → escalate priority and add to weekly review agenda
This created execution accountability rather than “report-only” insights.
9. Code-to-Business Breakdown
| Logic / System Component | Business Impact |
|---|---|
| API pull + weekly deltas | Removes manual data gathering |
| KPI threshold flags | Standardizes audit quality across PMs |
| Classification (Healthy/Watchlist/Critical) | Instant prioritization across large account lists |
| AI audit summary generation | Removes repetitive analysis writing |
| Formatted report delivery | PMs don’t need to open Google Ads |
| ClickUp task creation for criticals | Ensures issues convert into action |
10. Results & Performance Impact
1. Audit Time Reduced
◉ Manual audit time per account removed
◉ PM review shifted from “collecting data” to “deciding actions”
◉ Weekly audit consistency increased across the portfolio
2. Faster Issue Detection
◉ Tracking anomalies surfaced earlier via conversion-drop flags
◉ CPA and CTR drift spotted consistently via delta thresholds
◉ Waste patterns identified faster (spend up, conversions flat/down)
3. Consistency Across Large Account Lists
◉ Every account audited using the same KPI checklist
◉ Same report structure across PMs and teams
◉ Easier weekly reporting and QA across the department
4. Scalable Oversight
◉ Audit process expanded to more accounts without adding PM workload
◉ Repeatable logic made onboarding new PMs easier
11. Challenges & How They Were Solved
Challenge: KPI thresholds varied by account type and goal
Solution: Added goal-based thresholds (lead gen vs ecommerce) and budget-based scaling rules
Challenge: Too many false positives from single-metric spikes
Solution: Introduced multi-signal validation (e.g., CPA spike + conversion drop + spend up)
Challenge: Summaries became generic if data context was thin
Solution: Forced prompts to reference exact deltas and flags; limited recommendations to a maximum of 5 actions
12. Lessons for Project Managers
◉ Standardized audits outperform manual “variable” reviews
◉ PMs should receive conclusions and next actions, not dashboards
◉ Classification systems make large account portfolios manageable
◉ Automation is most valuable when it connects insights to execution tasks
◉ Consistency compounds over time when the audit runs every week without fail
13. Conclusion
By automating a weekly Google Ads audit that checks 20+ KPIs, applies consistent health rules, and delivers PM-ready reports, I eliminated the need for manual interface-based auditing. PMs gained faster clarity, consistent oversight across a growing account list, and a reliable mechanism to turn issues into actionable work—without adding operational load.
Looking to Run Consistent Weekly Google Ads Audits Across All Accounts Without Manual Work?
