google-ads

Executes the pending changes in `pending_changes.json` in the live Google Ads account.

Runs a custom GAQL query to fetch data not available in the standard export.

Check if `config.json` exists in the project root.

Run this at the start of each session to set up the project.

Validates the pending changes in `pending_changes.json` against the Google Ads API without executing them (dry-run).

Verify that Search, Display, Shopping, Video, and Performance Max campaigns are never mixed in ways that compromise optimization signals.

Ensure branded and non-branded keywords live in separate campaigns with independent budgets and targets.

Audit naming conventions across all campaigns, ad groups, and labels for a standardized taxonomy.

Evaluate whether each ad group contains tightly themed, closely related keywords (ideally 5-20 per group).

Segment and analyze Search Partners performance separately from Google Search.

Check whether Search campaigns have inadvertently opted into the Google Display Network.

Audit all campaign-level settings including location targeting method, start/end dates, and network settings.

Verify that campaigns, ad groups, keywords, and ads are properly labeled for segmentation, reporting, and automated rule targeting.

Review account-level settings including auto-tagging, conversion tracking defaults, auto-applied recommendations opt-ins, and linked accounts.

Ensure campaign priorities (especially for Shopping) are correctly configured and that experiments/drafts are properly structured.

Evaluate whether the account leverages Google's 2025 recommended campaign trio: Performance Max + Demand Gen + AI Max for Search.

Analyze the distribution of broad, phrase, and exact match keywords across the account and compare performance by match type.

Review search term reports to identify high-performing queries that are not yet added as keywords, representing opportunities for better control and optimization.

Identify irrelevant, wasteful, or poor-performing search queries that should be added as negative keywords to prevent future spend waste.

Analyze 1-word, 2-word, and 3-word combinations (n-grams) within search terms to identify systemic patterns of waste or opportunity.

Verify that shared negative keyword lists exist and adequately cover common waste categories to prevent irrelevant traffic.

Identify negative keywords that are blocking or could block desired active keywords, causing ads not to show for intended queries.

Find duplicate keywords across ad groups and campaigns, considering match type and Quality Score to determine which instances to consolidate.

Detect when multiple keywords within the account compete for the same search queries, leading to internal auction competition and suboptimal ad serving.

Identify keywords that exceed cost thresholds without generating conversions, representing candidates for pausing or removal to improve account efficiency.

Flag keywords with bids too low to appear on the first page of search results.

Verify that broad match keywords are paired with Smart Bidding strategies.

Review search queries triggered by broad and phrase match keywords to identify irrelevant matches and negative keyword opportunities.

Evaluate whether keyword search intent matches campaign goals and landing page content.

Verify that RSAs have 10-15 unique headlines for optimal ad strength and combination testing.

Ensure all 4 description slots in RSAs are filled with unique, compelling descriptions.

Audit RSAs for Ad Strength ratings and identify improvements needed to reach Good or Excellent.

Check for over-pinning in RSAs that limits Google's optimization ability.

Find Low performing headlines and descriptions to replace with better alternatives.

Verify all extension types are active and linked at appropriate levels.

Evaluate sitelink extensions for relevance, completeness, and performance.

Ensure continuous ad testing is in place with proper structure and statistical rigor.

Assess whether Dynamic Keyword Insertion is used appropriately and safely.

Verify alignment between ad messaging and landing page content.

Check that high-resolution, properly formatted image assets are uploaded for campaigns that support them.

Verify that video assets are uploaded for Performance Max and Demand Gen campaigns.

Check ad approval status and resolve disapproved or limited eligibility ads.

Scan all ad copy for spelling mistakes, grammar errors, excessive punctuation, and capitalization violations.

Evaluate whether campaigns are using optimal bidding strategies based on goals, conversion volume, and maturity.

Verify that Target CPA and Target ROAS values are achievable based on historical performance.

Flag campaigns currently in Smart Bidding learning phase and assess impact on performance and decision-making.

Find campaigns showing "Limited by budget" status and quantify missed opportunity from budget constraints.

Verify that campaign daily budgets are 5-10x the target or actual CPA to ensure Smart Bidding can optimize effectively.

Track actual spend against monthly budget targets to identify pacing issues before month-end.

Reallocate budget from low-performing campaigns to high-performing campaigns to maximize overall account ROI.

Assess whether campaigns grouped under portfolio bidding strategies are appropriately matched for optimal performance.

Verify that no campaigns are still using deprecated Enhanced CPC (ECPC) bidding and plan migration to modern strategies.

Audit device, location, schedule, and audience bid modifiers to ensure they are optimized and not conflicting with Smart Bidding.

Configure alert thresholds for budget pacing issues and identify campaigns that need monitoring rules.

Evaluate whether shared budgets are being used appropriately and not causing budget allocation issues.

Use bid simulators to model the impact of Target CPA or Target ROAS changes before implementing them.

Verify that conversion values reflect actual business value (revenue, profit margin, LTV) to enable Smart Bidding to optimize for profit, not just conversion volume.

Verify that campaigns use the correct location targeting method ("Presence" vs "Presence or Interest") based on business type.

Analyze conversion performance by geographic location and recommend bid adjustments to optimize spend allocation across high and low performing areas.

Identify and recommend exclusion of geographic areas with high cost but low or zero conversions to eliminate wasted spend.

Analyze performance segmented by device type (desktop, mobile, tablet) and recommend bid adjustments to optimize spend allocation.

Analyze performance by hour of day and day of week to optimize ad scheduling and bid adjustments.

Review performance by demographic segments (age, gender, household income) and recommend targeting adjustments.

Add relevant audience segments in Observation mode to gather performance data without restricting reach.

Evaluate usage of in-market segments and custom intent audiences to improve targeting precision.

Verify that Customer Match lists are uploaded, properly configured, and kept fresh.

Monitor remarketing and customer lists to ensure they maintain the minimum 1,000+ members required for Search targeting.

Verify that local businesses use 'Presence' targeting instead of 'Presence or Interest' to avoid serving ads to users who cannot physically visit.

Monitor Quality Score distribution across keywords and flag keywords with QS of 3 or below.

Track the three Quality Score components separately: Expected CTR, Ad Relevance, and Landing Page Experience.

Identify trending Quality Score degradation by comparing current QS to historical baselines.

Find keywords with 'Below Average' Expected CTR and recommend improvements.

Flag keywords where ad copy does not match keyword intent.

Evaluate landing pages for relevance, speed, and mobile-friendliness.

Verify that all valuable business actions are being tracked as conversions in Google Ads.

Cross-reference Google Ads conversion data with actual business data (CRM, e-commerce platform, order system) to verify tracking accuracy.

Verify that Enhanced Conversions for Web is properly implemented to improve conversion measurement accuracy in a privacy-first world.

Verify that Enhanced Conversions for Leads is properly configured to match offline CRM data back to Google Ads clicks.

Evaluate the readiness and benefit of migrating from client-side to server-side tagging.

Verify that Consent Mode v2 is properly implemented to maintain conversion measurement accuracy while respecting user privacy choices.

Review and optimize conversion action configuration including counting method, attribution model, value settings, and conversion windows.

Verify that Data-Driven Attribution (DDA) is enabled for all eligible conversion actions.

Test landing page load times to ensure pages load in under 3 seconds.

Scan landing pages for 4xx and 5xx HTTP errors that waste ad spend and damage user experience.

Verify that offline conversions (sales calls, in-store purchases, CRM-tracked deals) are being imported back to Google Ads.

Track intermediate actions (micro-conversions) that indicate user intent before the primary conversion.

Audit product feed titles to ensure they follow the Brand + Product Type + Key Attributes format.

Verify that critical product identifiers (GTIN, MPN, Brand) and key attributes are populated in the product feed.

Evaluate and implement custom label strategies to enable margin-based bidding, seasonal prioritization, and performance tiering in Shopping campaigns.

Ensure products are mapped to the most specific Google Product Category (GPC) available, not generic parent categories.

Evaluate whether PMax asset groups are organized by distinct product categories or intent themes.

Verify that Performance Max campaigns have proper audience signals configured, including Customer Match lists, GA4 audiences, and custom segments.

Audit Performance Max Final URL Expansion settings to ensure appropriate control over landing page selection.

Ensure Performance Max campaigns have custom video assets uploaded rather than relying on auto-generated videos.

Monitor for search query overlap between Performance Max and standard Search campaigns.

Evaluate whether New Customer Acquisition (NCA) mode is enabled to bid more aggressively for new customers vs existing customers.

Audit audience segments based on funnel position: homepage visitors, product viewers, cart abandoners, and past purchasers.

Optimize audience membership durations (7-365 days) aligned to the business's buying cycle.

Audit Remarketing Lists for Search Ads (RLSA) campaigns for proper audience targeting and bid adjustments.

Verify dynamic remarketing is properly configured with product feed integration and custom parameters.

Set appropriate frequency caps (typically 3-5 impressions per user per week) to prevent ad fatigue and wasted impressions.

Maintain exclusion lists for users who converted within an appropriate window (7-30 days).

Audit Customer Match list usage, freshness, and application strategy for cross-device targeting.

Audit GA4 behavioral audiences (5+ sessions, pricing page visitors, engaged users) synced to Google Ads.

Confirm GA4 is properly linked with bidirectional data flow, audiences syncing, and key events imported as conversions.

Verify that conversion values reflect actual business value (revenue, profit margin, LTV).

Evaluate whether cross-device conversion paths are captured through Enhanced Conversions.

Verify that offline conversion data is imported within 1-14 days of the lead event.

Detect conversion tag firing drops below expected thresholds indicating tracking breakage.

Use data exclusions to prevent broken tracking periods from influencing Smart Bidding.

Track product returns and refunds to measure true ROAS.

Pre-build comprehensive negative keyword lists with common irrelevant terms to prevent wasted spend.

Block low-quality websites, apps, and YouTube channels at the account level to prevent wasted spend.

Conduct placement reports to identify high-impression, low-conversion placements for optimization or exclusion.

Exclude mobile app placements, particularly games and children's apps, which typically generate accidental clicks.

Identify time periods (hours and days) with high spend but low or zero conversions to optimize ad scheduling.

Monitor for suspicious click patterns and implement IP exclusions to protect against click fraud.

Audit and manage Google's auto-applied recommendations to prevent unwanted changes.

Monitor search queries triggered by close variants and 'same meaning' expansions to identify irrelevant traffic.

Distinguish between impression share lost due to budget constraints versus ad rank issues to prioritize optimization efforts.

Identify keywords exceeding spend thresholds with zero conversions and recommend automated pause rules.

Analyze day-of-week performance to recommend daily budget allocation and monthly pacing strategies.

Identify performance anomalies and recommend automated alert configurations for key metric deviations.

Audit destination URLs for errors, redirects, and issues that waste ad spend and trigger disapprovals.

Bulk analyze RSA headline and description performance across all ads to identify top performers and replacement candidates.

Track week-over-week search query volume shifts to identify emerging opportunities and declining terms.

Analyze Performance Max campaign performance with available channel and placement insights.

Monitor Quality Score distribution and recommend alerts for keywords dropping to QS 3 or below.

Identify campaigns needing scheduling rules for promotions, events, and time-bound activities.

Track account changes including manual updates, automated rules, and auto-applied recommendations for audit purposes.

Segment impression share loss into budget vs rank causes to identify the right optimization strategy.

Track SERP positioning metrics to ensure ads appear in premium positions for maximum performance.

Analyze regional competitive dynamics and identify geographic opportunities based on impression share by location.

Analyze month-over-month performance patterns to identify seasonal trends, plan budgets, and set benchmarks.

Monitor ad approval status and provide systematic resolution workflow for disapprovals.

Audit landing pages for policy compliance including privacy policy, SSL, and content requirements.

Monitor trademark usage in ads, track exemptions, and maintain compliance with trademark policies.

Pre-launch compliance checklist for new ads covering prohibited content, editorial standards, and policy requirements.

Use Seasonality Adjustments for expected conversion rate changes during 1-7 day events.

Schedule temporary budget increases for promotional periods with automatic reversion.

Build and execute a seasonal keyword calendar 4-6 weeks before peak periods.

Deploy promotional extensions, countdown customizers, and seasonal ad copy during events.

Apply negative seasonality adjustments after events when conversion rates drop.

Update Shopping/PMax product titles with seasonal keywords before peak periods.

Analyze prior-year data for seasonal periods to set realistic targets and inform investment decisions.

Build robust first-party data collection through email signups, loyalty programs, and CRM systems.

Evaluate adoption of AI Max for Search, applying PMax-style AI to standard Search campaigns.

Review Smart Bidding Exploration settings that use flexible ROAS targets to explore new traffic.

Evaluate whether Smart Bidding is layered with manual guardrails (scripts, rules, monitoring).

Assess whether campaigns provide diverse, high-quality modular creative across text, image, and video.