--- title: AI-Driven Google Ads Analysis Workflow type: article created: '2025-10-29' updated: '2025-10-29' source_docs: - raw/2025-10-29-weekly-call-w-gilbert-97690098.md tags: - google-ads - ai-workflow - gemini - claude - performance-marketing - ppc layer: 2 client_source: null industry_context: null transferable: true --- # AI-Driven Google Ads Analysis Workflow ## Overview A structured workflow for using AI tools — primarily Gemini and Claude — to analyze Google Ads campaign and search term reports, generate actionable recommendations, and track performance over time. This process was demonstrated live during a weekly performance review using the Bluepoint ATM account as a test case, revealing critical campaign flaws that manual review had missed. This workflow is intended to be run weekly by account managers and the performance marketing team as a complement to (not a replacement for) hands-on campaign management. --- ## Why Gemini and Claude Instead of ChatGPT Different AI tools have different strengths: | Tool | Best For | |---|---| | **Gemini** | Web scraping, reading URLs, uploading and parsing files, Google Ads analysis | | **Claude** | Marketing analysis, nuanced recommendations, document Q&A | | **ChatGPT** | General conversation and quick questions; degrades on heavy analytical tasks | ChatGPT sometimes fails to open URLs depending on a site's `robots.txt` settings. Gemini is more reliable for file uploads and link-based research. Claude tends to produce higher-quality marketing reasoning. > *"When I really want to do internet stuff, like where I'm going to look at links or scrape something, I use Gemini. And if you're asking marketing questions, oftentimes Claude's better."* — Mark Hope --- ## Step-by-Step Workflow ### 1. Start a Dedicated Chat Create a **new chat** for each client or topic. Do not mix accounts or unrelated campaigns in the same conversation. - Keeping chats focused prevents the AI from conflating context across unrelated accounts. - A focused chat is also easier to search and return to later. **Opening prompt pattern:** > *"I want to talk about Google Ads for [Client Name]. I'm going to upload some documents. Wait for my questions."* This prevents the AI from generating premature analysis before all data is loaded. ### 2. Download and Upload Reports From Google Ads, download the relevant reports as CSV files for the desired date range (typically last 30 days): - **Campaign Report** — overall spend, impressions, clicks, conversions, impression share - **Search Term Report** — actual queries triggering ads, especially useful for identifying PMax waste Drag and drop the CSV files directly into the Gemini or Claude chat window. You can also paste a screenshot using a screen snipping tool if a quick visual check is sufficient. ### 3. Provide Campaign Context AI tools do not inherently know the business model behind a campaign. You must tell it: - **Campaign type:** B2B lead gen, B2C e-commerce, brand awareness, etc. - **Known issues or recent changes:** e.g., "We just switched the landing page from the homepage to a dedicated landing page." - **What to disregard:** e.g., for B2B lead gen, instruct it to ignore conversion value (which is set to $1 as a placeholder) and focus on CPA and lead volume instead. **Example clarifying prompt:** > *"Disregard conversion value. This is a B2B lead gen campaign."* Without this context, the AI will flag a $1 conversion value as a critical error — which is technically correct but misleading for lead gen accounts. ### 4. Ask Targeted Questions Once reports are uploaded and context is set, ask specific questions rather than requesting a generic summary: - *"Evaluate the impression share loss. What's causing it?"* - *"Which search terms in the PMax campaign are irrelevant and should be negated?"* - *"The cashless campaign has a 61% conversion rate. Should we increase its budget?"* - *"What if I increased the bid from $1 to $3? What would you expect to happen?"* - *"We changed the landing page last week. Are you seeing any trends that suggest it's improving?"* The AI can also be used to compare periods, predict outcomes, and prioritize action items. ### 5. Maintain Chat History for Weekly Tracking Return to the **same chat** each week. The accumulated context makes the AI progressively more useful: - It can compare this week's data to last week's. - It can confirm whether previously recommended changes had the expected effect. - It builds a running record of decisions and outcomes. **Weekly return prompt pattern:** > *"It's been a week. Here are the updated reports. Last week you recommended [X]. Can you tell if it worked?"* --- ## What the AI Can Catch The Bluepoint ATM demonstration surfaced three issues that had not been explicitly flagged before: | Issue | Detail | |---|---| | **Conversion value misconfigured** | Total recorded conversion value was $1 — correct for lead gen but flagged as a data quality problem without context | | **93% impression share lost to rank** | The "Traditional" search campaign was nearly invisible due to poor Quality Score, almost certainly caused by a weak landing page | | **PMax wasting spend on irrelevant queries** | Search terms like *"how to increase sales in retail footwear"* were triggering ads and consuming budget with zero conversions | See [[clients/bluepoint-atm/_index]] for the full account context and remediation actions. --- ## Tips and Best Practices - **One chat per client or topic.** Mixing accounts pollutes the context window and makes searches harder. - **Save important outputs.** Copy key recommendations into a Google Doc — chat search is not always reliable. - **Use transcripts too.** Fathom call transcripts can be pasted into a chat to ask specific questions: *"What did Melissa say about the landing page?"* - **Upload PDFs and large documents.** The AI can summarize or answer questions about any document you drag in. - **Don't over-engineer prompts.** For Google Ads analysis, plain-language questions work well. The AI already understands campaign structure. --- ## Related - [[clients/bluepoint-atm/_index]] - [[clients/cellarize/_index]] - [[knowledge/google-ads/pmax-search-term-hygiene]] - [[knowledge/google-ads/impression-share-loss-rank-vs-budget]] - [[knowledge/performance-marketing/lead-gen-conversion-tracking]]