Configure Claude Cowork for Google Ads Workflows

Claude Cowork gives paid search teams a faster way to handle repetitive Google Ads work. It operates inside a chosen desktop folder, so it can read exports, create files, revise drafts, and package outputs without requiring code. Once configured, it can review account data, write RSA assets, assemble negative lists, prep Google Ads Editor imports, and check A/B test significance from one place.

What you can do with it in Google Ads

Claude Cowork is useful for several common PPC jobs:

Performance review: inspect Google Ads CSV exports and surface wasted spend
RSA drafting: produce 15 headlines and 4 descriptions per ad group, with character-limit checks
Negative keyword creation: turn search term reports into negative lists
Editor-ready outputs: generate CSV files for Google Ads Editor
Experiment analysis: measure statistical significance for A/B tests

Requirements before you begin

You only need two items:

Claude Desktop (macOS)
A paid Claude plan — Pro at $20/month or higher

Basic setup that takes about five minutes

Install the desktop app

Download it here:

claude.ai/download

Open Cowork

Launch Claude Desktop and select the Cowork tab at the top.

Create a clean workspace folder

Make a folder such as ~/google-ads-workspace/ and add these subfolders:

exports/ — CSVs downloaded from Google Ads
creatives/ — ad copy drafts
reports/ — performance summaries
uploads/ — files ready to import

Add reusable paid-media instructions

Skills are Markdown instruction files that teach Claude repeatable workflows. After you load them, Claude can pick the right skill automatically when the task matches.

Free skills for paid ads teams

There are 17 free marketing skills for paid ads marketers on GitHub:

github.com/irinabuht12-oss/marketing-skills

A few of the most helpful for Google Ads work:

Google Ads Audit — identifies wasted spend, search term leaks, and negative keyword gaps
A/B Test Analyzer — calculates significance and sample size requirements
Landing Page Audit — finds conversion blockers and CTA problems
Competitor Teardown — examines competitor positioning and messaging
UTM & Tracking Generator — keeps UTM links and GA4 event names consistent
Ad Spend Allocator — supports budget reallocation across channels

The full set also covers Meta, LinkedIn, Reddit, SEO, email, and more.

How to load the skill files

Download the ZIP from GitHub or clone the repository.
In claude.ai, open Projects → Create Project.
Drag the .md skill files into Project Knowledge.
Claude will auto-activate them when relevant.

Two ways to bring ad data into Claude

There are two main connection paths.

Manual MCP setup from GitHub

This option is for read-only analysis. It suits technical marketers who want more control. Plan for roughly 30-60 minutes to get it running.

Clone the MCP repository: git clone https://github.com/cohnen/mcp-google-ads
Create Google Ads API credentials:
- In Google Cloud Console, create a project and enable the Google Ads API
- Under Credentials, create an OAuth Client ID for a Desktop App
- Download client_secret.json
Get the developer token:
- In Google Ads, go to Tools → API Center
- Copy the Developer Token. It begins as a test token. You can apply for production access later.
Install the MCP server:

cd mcp-google-ads
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Create a .env file:

GOOGLE_ADS_AUTH_TYPE=oauth
GOOGLE_ADS_CREDENTIALS_PATH=/path/to/client_secret.json
GOOGLE_ADS_DEVELOPER_TOKEN=your_token
GOOGLE_ADS_LOGIN_CUSTOMER_ID=your_mcc_id

Edit the Claude Desktop config at ~/Library/Application Support/Claude/claude_desktop_config.json and add:

{
  "mcpServers": {
    "googleAdsServer": {
      "command": "/path/to/.venv/bin/python",
      "args": ["/path/to/google_ads_server.py"],
      "env": {
        "GOOGLE_ADS_AUTH_TYPE": "oauth",
        "GOOGLE_ADS_CREDENTIALS_PATH": "/path/to/credentials.json",
        "GOOGLE_ADS_DEVELOPER_TOKEN": "YOUR_TOKEN",
        "GOOGLE_ADS_LOGIN_CUSTOMER_ID": "YOUR_MCC_ID"
      }
    }
  }
}

Restart Claude Desktop. The Google Ads tools should then appear.

Example prompts to test the connection:

Show campaigns with ROAS below 2 in last 30 days.
Which ad groups have highest CPC but lowest conversions?
Run a YoY analysis on my Search campaigns.

More information is in the repository: cohnen/mcp-google-ads

Automated connection through a service

If you want less manual setup, a service can connect your accounts automatically.

Five strong starter tasks for Google Ads

Scale RSA creation for weak ad groups

Prep: Export ad performance data from Ads & Extensions → Download as CSV in Google Ads, then place the file in /exports.

Prompt:

I've placed a Google Ads performance export in the /exports folder. 
TASK: Generate new RSA copy for underperforming ad groups. 

STEP 1 - ANALYSIS: 
- Load the CSV and identify the bottom 25% of ads by CTR 
- For these underperforming ads, analyze what the TOP 25% are doing differently 
- Note patterns: emotional hooks, specificity, numbers, CTAs, keyword placement 

STEP 2 - GENERATION: For each underperforming ad group, generate: 
- 15 headlines (STRICT 30 character max including spaces) 
- 4 descriptions (STRICT 90 character max including spaces) 

RULES: 
- At least 3 headlines must include the primary keyword 
- At least 2 headlines must include a number or statistic 
- At least 2 headlines must be benefit-focused (not feature-focused) 
- No exclamation marks 
- Every description must end with a clear CTA 
- Vary the angles: price, speed, quality, trust, urgency, social proof 

STEP 3 - OUTPUT: Create a CSV file in /uploads with these exact columns: Campaign, Ad Group, Headline 1, Headline 2, Headline 3, Headline 4, Headline 5, Headline 6, Headline 7, Headline 8, Headline 9, Headline 10, Headline 11, Headline 12, Headline 13, Headline 14, Headline 15, Description 1, Description 2, Description 3, Description 4 
Also create a summary.md showing: 
- Which ad groups were flagged as underperforming 
- What patterns you found in top performers 
- Character count verification for each headline/description

What Claude handles in this workflow:

reviews performance data
identifies copy patterns in top performers
writes new assets within Google Ads limits
saves a Google Ads Editor-ready CSV

Mine search terms and produce negatives

Prep: Export the Search Terms report from Keywords → Search Terms → Download and place it in /exports.

Prompt:

I've placed a Google Ads Search Terms report in /exports. 
TASK: Clean up search terms and build negative keyword lists. 

ANALYSIS - Find and categorize: 
1. IRRELEVANT TERMS (no purchase intent for my product): 
- Job seekers ("jobs", "careers", "salary", "hiring") 
- DIY/free seekers ("free", "how to", "tutorial", "template") 
- Wrong industry/context 
- Competitor brand searches (unless we're targeting them intentionally) 

2. BUDGET BURNERS: 
- Terms with spend > $50 and 0 conversions in the date range 
- Terms with CPA > 3x our target CPA of $[YOUR_TARGET_CPA] 
- Terms with CTR < 1% and significant impressions (>500) 

3. OPPORTUNITY TERMS: 
- High-converting terms not yet added as exact match keywords 
- Terms revealing new keyword themes we're missing 
- Long-tail variations worth breaking into their own ad groups 

OUTPUT - Create 3 files in /uploads: 
1. negative-keywords.csv 
Columns: Keyword, Match Type, Campaign, Ad Group, Reason 
- Group similar negatives by theme 
- Use phrase match for most, exact match for edge cases 
- Format ready for Google Ads Editor upload 
2. new-keywords.csv 
Columns: Keyword, Match Type, Suggested Bid, Campaign, Ad Group, Source Term, Conversions 
- Suggest match type based on volume/intent 
- Suggest bid based on the source term's CPC 
- Include which search term it came from 
3. search-term-analysis.md 
- Total wasted spend on flagged terms 
- Top 10 budget burners with spend amounts 
- Negative keyword themes identified 
- New keyword opportunities with projected impact 

Customize: Replace $[YOUR_TARGET_CPA] with your actual target CPA.

Run a complete account review

Prep: Export these three reports from Google Ads for the last 30 days and place all CSVs in /exports:

campaign performance
ad group performance
keyword performance

Prompt:

I've placed 3 Google Ads performance reports in /exports: 
- Campaign performance 
- Ad group performance 
- Keyword performance 

TASK: Run a full account audit and prioritize actions. 

FLAG THESE ISSUES: 
CAMPAIGN LEVEL: 
- CPA above $[YOUR_TARGET] (my target is $[X]) 
- ROAS below [YOUR_TARGET] (my target is [X]) 
- Budget-limited campaigns (Lost IS Budget > 20%) that have ROAS above target 
- Campaigns with <3 active ad groups 
- Any campaign spending >$500/week with ROAS < 1 

AD GROUP LEVEL: 
- CTR below 2% with >1000 impressions 
- Ad groups with fewer than 3 active ads (Google recommends 3+) 
- Ad groups with 0 conversions but >$100 spend 
- Ad groups where top performing ad has <50% impression share 

KEYWORD LEVEL: 
- Quality Score below 6 (flag 5 and below as critical) 
- Keywords with >$200 spend and 0 conversions 
- Keywords with CPC > 2x the ad group average 
- Broad match keywords that should be phrase or exact 
- Exact match keywords with low search volume (<100 impressions) 

WEEK-OVER-WEEK: 
- Any metric change >20% vs previous period (flag direction: improving/declining) 

OUTPUT: 
1. audit-report.md 
Structure: 
- Executive Summary (3 bullet max) 
- Critical Issues (fix immediately) 
- High Priority (fix this week) 
- Medium Priority (fix this month) 
- Quick Wins (easy fixes, fast impact) 
- Each issue: what's wrong, why it matters, specific fix, estimated impact 
2. action-items.csv 
Columns: Priority, Level (Campaign/AdGroup/Keyword), Entity Name, Issue, Recommended Action, Estimated Monthly Impact 
Sorted by estimated impact descending 

Customize: Replace $[YOUR_TARGET] , $[X] , [YOUR_TARGET] , [X] with your actual targets.

Study competitor messaging and spot openings

Prep: Export competitor ads from sources such as Google Ads Transparency Center, SpyFu, or **SEMrush. You can also paste ad copy into a document. Save everything in /exports.

Prompt:

I've placed competitor ad data in /exports. 
These are my main competitors: [LIST YOUR COMPETITORS] 
My product/service: [DESCRIBE YOUR PRODUCT IN 1-2 SENTENCES] 
My main differentiators: [LIST 3-5 THINGS THAT MAKE YOU DIFFERENT] 

TASK: Analyze competitor messaging and find gaps we can own. 

FOR EACH COMPETITOR, ANALYZE: 
1. VALUE PROPOSITIONS 
- What's their primary promise? 
- What benefits do they lead with? 
- What proof points do they use? 
2. MESSAGING THEMES (categorize their headlines): 
- Price/discount focused 
- Speed/convenience focused 
- Quality/premium focused 
- Trust/social proof focused 
- Urgency/scarcity focused 
- Feature-specific 
- Benefit-specific 
3. LANGUAGE PATTERNS 
- Common phrases across competitors 
- Typical headline structures 
- CTA patterns 
4. GAPS - WHAT THEY'RE NOT SAYING: 
- Benefits they ignore that we can claim 
- Audiences they're not speaking to 
- Objections they're not addressing 
- Angles no one is using 
5. SPECIFICITY SCORE (1-10): 
- Are their headlines specific or generic? 
- Do they use numbers, timeframes, guarantees? 

OUTPUT: 
1. competitor-analysis.md 
- Side-by-side comparison table 
- Gap analysis with opportunities 
- Recommended positioning for our brand 
2. differentiated-headlines.csv 
Columns: Headline, Character Count, Angle, Why It's Different 
- Generate 25 headlines that: 
- Attack gaps competitors ignore 
- Use specific numbers/proof points 
- Lead with our unique differentiators 
- Are NOT generic ("Best [Product]", "Top Rated", etc.) 
- All headlines STRICT 30 character max 

Customize: Replace bracketed sections with your actual competitors, product, and differentiators.

Audit ad-to-page consistency

Prep: Export your active ad copy to a document. Save screenshots or HTML for the matching landing pages. Put those files in /exports.

Prompt:

I've placed ad copy and landing page files in /exports. 
TASK: Check message match between ads and landing pages to improve Quality Score. 

FOR EACH AD + LANDING PAGE PAIR, CHECK: 
1. HEADLINE MATCH 
- Does the ad headline promise appear on the landing page? 
- Is it above the fold? 
- Is the language identical or just similar? 
Score: Exact Match / Partial Match / No Match 
2. CTA CONSISTENCY 
- Does the ad CTA match the landing page CTA? 
- Examples of mismatch: Ad says "Get Free Quote" but page says "Contact Us" 
Score: Match / Mismatch 
3. VALUE PROP PRESENCE 
- Every benefit mentioned in the ad: is it on the landing page? 
- List which ad claims are NOT supported on the page 
4. KEYWORD PRESENCE 
- Is the primary keyword on the landing page? 
- Where? (Headline, subhead, body, none) 
5. TRUST SIGNALS 
- Does the ad mention reviews/ratings? Are they on the page? 
- Does the ad mention guarantees? Are they on the page? 
6. QUALITY SCORE RISK ASSESSMENT 
- High Risk: No headline match, CTA mismatch, missing value props 
- Medium Risk: Partial headline match, keyword not prominent 
- Low Risk: Minor copy differences 

OUTPUT: 
1. message-match-audit.md 
For each ad/landing page pair: 
- Match score (1-10) 
- Specific issues found 
- Risk level 
- Recommended fixes 
2. landing-page-fixes.csv 
Columns: Landing Page URL, Issue, Current Copy, Recommended Copy, Priority 
- Specific copy changes to improve message match 
- Prioritized by impact on Quality Score 
3. ad-copy-fixes.csv 
Columns: Campaign, Ad Group, Current Headline/Description, Issue, Recommended Change 
- Cases where it's easier to fix the ad than the page

Build custom skills for repeated tasks

If you run the same process often, custom skills save time and keep outputs consistent. Good uses include:

Brand Voice — tone rules, approved terms, banned phrases
RSA Generator — character limits, keyword insertion rules, CSV format
Performance Reviewer — KPI thresholds, alert triggers, report structure
Negative Keyword Builder — industry-specific irrelevant terms
Campaign Naming Convention — your naming taxonomy

Write your own `SKILL.md`

You can structure it like this:

---
name: my-rsa-generator
description: Generate RSA copy that follows our brand guidelines and Google Ads character limits. Use when creating ad copy.
---
## Rules
- Headlines: max 30 characters
- Descriptions: max 90 characters
- Include 2+ headlines with primary keyword
- No exclamation marks in headlines
- Every description ends with clear CTA

## Output
CSV with: Campaign, Ad Group, Headline 1-15, Description 1-4

Then upload it through Settings → Capabilities → Skills → Add.

Have Cowork create the skill for you

Use a request like this:

Help me build a Claude skill for RSA generation. Here's how I currently do it: [describe your process]. Enforce character limits, use our brand voice, and always output as Google Ads Editor CSV.

Tips that improve output quality

Start with one task, such as search term cleanup or ad copy refresh
Write naturally and explain the task like you would to a colleague
Use real campaign exports instead of invented data
Combine skills, such as Brand Voice + RSA Generator + Performance Reviewer
Review every output before launch. Claude is a strong starting point, but your judgment still matters
Use Cowork for multi-step jobs. It consumes more usage than regular chat

Additional resources to explore

Key takeaways

Claude Cowork can analyze, draft, and format Google Ads work without coding
You need Claude Desktop (macOS) and a paid Claude plan starting at $20/month
There are 17 free marketing skills on GitHub
You can connect data through a manual MCP setup or through an automated service.
The quickest wins are audits, search term cleanup, RSA generation, competitor analysis, and message-match checks

All guides

What you can do with it in Google Ads

Requirements before you begin

Basic setup that takes about five minutes

Install the desktop app

Open Cowork

Create a clean workspace folder

Add reusable paid-media instructions

Free skills for paid ads teams

How to load the skill files

Two ways to bring ad data into Claude

Manual MCP setup from GitHub

Automated connection through a service

Five strong starter tasks for Google Ads

Scale RSA creation for weak ad groups

Mine search terms and produce negatives

Run a complete account review

Study competitor messaging and spot openings

Audit ad-to-page consistency

Build custom skills for repeated tasks

Write your own SKILL.md

Have Cowork create the skill for you

Tips that improve output quality

Additional resources to explore

Key takeaways

Write your own `SKILL.md`