Google Ads API — AI Automation Tools

Overview

Mark is actively developing a suite of AI-powered tools that connect directly to the Google Ads API and Google Search Console. The goal is to enable natural-language querying of client ad account performance — removing the need to manually navigate dashboards for routine analysis and auditing tasks.

As of the September 30, 2025 ops sync, these tools are described as near completion.

Capabilities (In Development)

Google Ads Performance Summaries

Query a client's Google Ads account in plain language and receive a structured performance summary. Example prompt:

"Go to Google Ads for Blue Sky Capital and summarize their performance over the last week."

The AI will surface key metrics, trends, and anomalies — going beyond what a manual review might catch.

Conversion Tracking Validation

Ask the tool to verify whether Google Tag Manager is firing correctly and whether conversions are being reported accurately. This addresses a recurring operational pain point: in the September 30 sync, Mark noted that American Extraction's ads were not running for over a week without anyone catching it. Automated auditing would flag this kind of issue proactively.

"Is Google Tag Manager tagging everything properly? Are conversions being reported properly?"

Google Search Console SEO Summaries

Similar natural-language querying for SEO performance:

"Go to Google Search Console and summarize the SEO performance of this website."

Motivation

The impetus for this tooling is twofold:

1. Accountability gaps — Manual monitoring has proven unreliable. Client-facing issues (e.g., ads not running, campaigns underperforming) have gone undetected for days or weeks. Automated AI-driven audits reduce dependence on individual team members catching problems.
2. Analyst leverage — The AI is described as "a lot smarter than I am" at pattern recognition across large account datasets, surfacing insights that might be missed in a manual review.

Status

• In development by Mark Hope as of 2025-09-30
• Described as "very close" to completion
• Planned to be demonstrated at the upcoming AI professional development session (October 2025)

Related

• ^[1] — Overview of when to use NotebookLM, Claude, Perplexity, Gemini, and ChatGPT
• ^[2] — Technique for bouncing outputs across AI tools to improve quality
• ^[3] — Source meeting where this was discussed
• ^[4] — Broader accountability concerns that motivate automated monitoring