The Google Ads AI Prompt Library: 30 Prompts Organized by Use Case

Each prompt is written as a template with variables in brackets []. Replace the variables with your actual data.

**Variable detail level = result quality.** The more specific you are, the more useful the AI output. "[product]" gives a generic result. "[men's trail running shoes, 80-150 USD range, US brand]" gives an actionable result.

**Claude or ChatGPT?** Both work. Claude tends to be more rigorous on constraints (text length, output format). ChatGPT tends to be more creative on copywriting. Test both on your critical prompts.

**P1: Structure audit** ``` Here is my current Google Ads account structure: [Campaigns > Ad Groups > Main Keywords]

My business: [industry, products, markets] Total monthly budget: [amount] Primary objective: [ROAS X / CPA Y / visibility]

Analyze the strengths and weaknesses of this structure. Recommend an optimized structure with the rationale behind each choice. ```

**P2: Campaign architecture for a new account** ``` I'm launching a Google Ads account for [business]. Products/services: [list] Starting budget: [amount/month] Objective: [conversions / brand awareness / traffic] Geographic market: [areas]

Propose a complete campaign architecture: number of campaigns, types, ad group structure, keyword segmentation logic. ```

**P3: Keyword segmentation** ``` I have these keywords for [product]: [list of 20-50 keywords]

Segment them into coherent thematic groups for distinct ad groups. Identify keywords to exclude (too generic or off-target). Format: table with Group | Included Keywords | Grouping Logic. ```

**P4: Negative keywords** ``` My business: [industry] My products: [list] Current keywords: [main list]

Generate a list of 30 negative keywords to add to avoid irrelevant clicks. Classify them by category: off-target competitors, wrong purchase intent, geographies, free/DIY terms. ```

**P5: Naming convention** ``` I need to create a naming convention for my Google Ads campaigns. Context: [agency with X clients / internal account with X markets] Elements to include in the name: [country, campaign type, network, objective, creation date]

Propose 3 different naming convention formats with an example for each. Indicate pros and cons. ```

**P6: Keyword expansion** ``` My main keywords for [product]: [list] I'm looking to expand coverage without losing relevance.

Generate 20 keyword variations classified by: high transactional intent / informational intent / specific long-tail. Format: table with estimated volume (high/medium/low) and intent. ```

**P7: Search intent analysis** ``` For these search queries extracted from my search terms report: [list of 20-30 queries]

Classify each query by intent: imminent purchase / comparison / information / navigation / no commercial intent. Recommend the action for each category: target / exclude / capture with content. ```

**P8: Keywords for Performance Max** ``` I have a Performance Max campaign for [product]. My current exact keywords in other campaigns: [list]

Generate a list of audience signals (search terms) to use as an asset in PMax. Include: purchase intents, market segments, relevant long-tail queries. ```

**P9: Search terms report analysis** ``` Here is my search terms report from last month: [PASTE CSV with columns: term, impressions, clicks, CTR, conversions, cost]

1. Identify terms to add as exact match (volume + performance) 2. Identify terms to exclude (irrelevant traffic) 3. Identify opportunities for new ad groups Format: 3 separate lists with justification. ```

**P10: Long-tail keyword strategy** ``` Industry: [sector] Product/service: [precise description] Estimated competition on main keywords: [high/medium/low] Budget: [limited / comfortable]

Propose a long-tail keyword strategy to capture qualified volume with reduced CPC. Include examples of query formats and the targeting logic. ```

**P11: Bidding strategy selection** ``` My Google Ads account: - Account age: [months] - Conversions/month volume: [number] - Current CPA: [amount] / Target CPA: [amount] - Current ROAS: [value] / Target ROAS: [value] - Monthly budget: [amount]

Which bidding strategy do you recommend (manual CPC, target CPA, target ROAS, maximize conversions)? Justify based on the data. When should I move to the next strategy? ```

**P12: tCPA/tROAS troubleshooting** ``` My Google Ads campaign with target CPA of [amount] isn't hitting objectives: - Current CPA: [amount] - Conversions/month volume: [number] - Budget: [amount] - spent at [%] - History: launched [X weeks] ago

Diagnose the likely causes and propose adjustments in priority order. ```

**P13: Multi-campaign budget distribution** ``` Total monthly budget: [amount] My campaigns and their current performance: [list: campaign | ROAS/CPA | conversion volume | current spend]

Recommend an optimized budget distribution. Justify each allocation based on performance and scaling potential. ```

**P14: Scaling simulation** ``` My current campaign: budget [$X/day], CPA [$Y], volume [Z conversions/month]. I want to increase the budget to [$2X/day].

What are the risks on CPA? What precautions should I take during scale-up? At what pace should I increase the budget? What metrics should I monitor? ```

**P15: Impression share loss analysis** ``` My campaign has a lost impression share of: - [X]% due to budget - [Y]% due to rank

Campaign: [type], budget [amount], target CPA [amount].

Explain what these numbers mean and recommend priority actions to reduce impression loss. ```

**P16: Sudden performance drop diagnosis** ``` My Google Ads campaign dropped this week: - Impressions: [before] vs [now] - Clicks: [before] vs [now] - Conversions: [before] vs [now] - Recent changes: [list of changes made]

Give me a structured diagnostic list to identify the cause. Rank by probability. ```

**P17: Low Ad Strength analysis** ``` My RSA has an Ad Strength of [Poor/Good/Excellent]. Current headlines: [list] Current descriptions: [list] Issues identified by Google: [list]

Explain how to improve each dimension to reach "Excellent". Propose alternative headlines and descriptions. ```

**P18: Quality Score optimization** ``` Ad group: [name] Keywords: [list with QS if known] Current CTR: [value] Landing page: [URL or description]

How to improve Quality Score? Give specific actions on the 3 components: ad relevance, expected CTR, landing page experience. ```

**P19: Seasonality analysis** ``` Industry: [sector] Performance history (if available): [known trends] Current period: [month]

What seasonal trends should I anticipate for the next 3 months? How should I adapt my bids, budgets, and creatives accordingly? ```

**P20: Before/after change comparison** ``` Before change (period A): [key metrics: impressions, clicks, CTR, CPA, ROAS]

After change (period B): [same metrics]

Change made: [precise description]

Analyze the impact of the change. Is it significant? Are there unexpected side effects? Should I maintain, adjust, or revert? ```

**P21: Declining conversions troubleshooting** ``` My conversions dropped [X]% this month. Stable clicks: [yes/no] Conversion rate: [before] vs [now] Recent tracking changes: [yes/no, description] Landing page changes: [yes/no, description]

Help me identify whether this is a tracking, traffic, page, or market problem. ```

A prompt library is a living asset. Maintenance strategy:

**1. Dedicated folder**: create a Notion, Google Docs, or Obsidian folder "PPC Prompts". Organize by category.

**2. Version and date**: note when each prompt was tested and with which AI version. Models evolve, some prompts become obsolete.

**3. Success rate**: for each prompt, note "Excellent / Good / Needs improvement" after 3-5 uses.

**4. Collective enrichment**: if you work in a team, share prompts that work. A collaborative Google Sheet with a "Created by" and "Tested by" column is enough.

**5. Continuous testing**: try one new prompt per week on a real task. Add it to the library if it produces value.