Managing Google Ads campaigns manually is like trying to juggle dozens of balls at once, one small mistake can waste thousands in ad spend. With hundreds of metrics, keywords, and ad groups to track, it’s nearly impossible for a campaign manager to optimize campaigns 24/7.
This is where an AI-powered Google Ads optimizer agent built with n8n can help. Automating repetitive tasks not only saves time but also improves ROI and reduces errors.
Why Automate Google Ads Optimization?
Manual campaign optimization is time-consuming and error prone.
Here’s what the data shows:
- 67% of marketers spend 8+ hours weekly on manual campaign optimization tasks – DoubleVerify study
- North American agencies lose approximately $17,000 annually per team member to repetitive tasks – Reference
- 49% marketers plan to implement automated solutions and AI into their daily repetitive tasks – Reference
- 63% of their data-related time, on average, is spent on tasks that could be partially or fully automated – Reference
Automation helps free up time for strategy and higher value tasks- while ensuring campaigns are still run efficiently around the clock
Understanding the Problem with Manual Optimization
Running digital ad campaigns manually may sound manageable, but in reality it’s a huge challenge. A campaign manager at an agency is not only responsible for creating and optimizing campaigns but also for reporting, client calls, preparing presentations, answering internal queries, updating management, and even setting up new campaigns. With so many tasks packed into a single day, optimization often takes a back seat.
The truth is, you simply cannot check every parameter every day.
For example, in Google Ads there are 50+ factors that can affect performance, bids, budgets, keywords, search terms, ad copy, placements, targeting, and more. Manually reviewing all of these on a daily basis is next to impossible.
Even the most dedicated manager is bound to miss things. Human errors are common, and missing just one poorly performing keyword or ad group can lead to wasted budget. Manual optimization often results in money being spent on the wrong search terms, irrelevant audiences, or underperforming ads.
This is where automation stands out. Unlike humans, a system can follow fixed rules, check every parameter consistently, and optimize campaigns 24/7 without fatigue. Manual optimization struggles with time, workload, and accuracy, and that’s exactly why automated solutions are becoming essential for improving ROI.
What Do You Need Before You Start?
Before you starting building your agent in n8n there are few things that you will need in place.
➥ Access to Google Ads MCC Account
- If you are an agency you are most likely to have a MCC account that is managing different client account under it
- If you are a brand, you will need a MCC account to fetch data via the API and then directly make changes to it once you approve of the changes
- The important part is that you will need a minimum of ‘Standard’ access to the MCC account.
➥ Developer Token
- Developer token is a unique alphanumeric string which acts like the access key that google provides so your app or scripts connect to the Google Ads API
- Without the token, you can’t make authorized requests to the Google Ads API (to pull reports, create campaigns, adjust bids, etc.).
- The token is tied to your Google Ads manager account and lets Google know which developer or company is making API calls.
- You can go to Admin → API center where you will find the developer token
➥ API Access Level
There are 3 access levels:
- Test account access: This is the default access upon initial sign up . This allows you to make API calls to test accounts, which don’t serve live ads
- Basic access: This lets you make calls to both test and live accounts and has a limit of 15000 operations which is usually enough for developers
- Standard access: This provides access to unlimited operations per day for most services. This is mainly for large companies that need high volume
➥ OAuth Client ID Set-up:
- Google ads API uses OAuth 2.0 for authorization. This is how your application gets permission for a user to access their Google ads data.
- Service account: Its a special google ads account that can be used by an application to make API calls on its behalf without a user’s direct interaction
- OAuth Client ID: Used for user-facing applications where a user needs to grant your application permission to access their account
- How to create OAuth Client ID:
- Create a Google Cloud Project.
- Enable the Google Ads API
- Configure the OAuth Consent Screen
- Create the OAuth Client ID
- Configure Credentials in n8n
➥ N8n account:
- N8n is the workflow automation tool where your optimizer logic will live
- There are 2 options:
- N8n Cloud: quick to set up, no server management needed
- Self-hosted n8n: more flexible and cost effective if you have IT resources
- Connect n8n to Google Ads API using HTTPs/Google Ads nodes and start building your workflow
Designing the optimization workflow
To create an effective Google Ads optimization agent using n8n, it’s important to design a workflow that takes the right data, analyzes it intelligently, and acts on it, either automatically or with human oversight.
➥ Define your input data
Decide what data your optimizer agent needs to deliver actionable insights. This could include: eg: Budget/ Goals/ Targets
➥ Trigger Your Workflow
Once your input is defined, it can trigger the n8n workflow automatically.
➥ Fetch Required Data via Google Ads API
Use Google Ads API to pull the dimensions & metrics you want to include: Eg:
- Campaign & Ad group performance
- Keyword performance
- Ad performance
- Search term performance & more
This steps ensure you have complete data to be fed further to the agent
➥ Process and Filter the Data in n8n
You can now use different nodes like filter (to filter irrelevant data/below certain impressions/ exceeding certain amount) or to merge/split data from various nodes
➥ Add an AI Agent for Optimization
Once the input is ready, feed it to the AI-powered agent – this could be ChatGPT, Gemini or other large language models (LLMs)
- This agent gives an output through which decisions can be made on : pausing ad groups/campaigns/keywords, increasing or reducing bids/budgets & more
- The AI essentially acts as your 24/7 campaign analyst, processing large amounts of data faster than any human could.
➥ Apply Recommendations with or without Human Oversight
After AI generates suggestions, you have 2 options:
- Direct Automation: Push changes suggested straight to Google ads API. Good for low risk adjustments
- Human in the Loop: Share recommendations with the campaign manager responsible for the campaign for verification and let him approve/ignore and then the system applies the approved ones directly in google ads
➥ Feedback Loop for Continuous Learning
- Once done, suggestions are fed back into the system for the agent to learn and give further output based on the feedback received. So there is continuous learning that happens. This feedback loop helps your Google Ads optimizer become smarter and more precise with every iteration.
Example Use Cases For Google Adwords Optimizer Agent:
- Keyword optimizer that helps remove non performing keywords, change match types/ suggests new keywords
- Search Term optimizer that helps to add them as keywords and remove non performing based on relevancy
- Bid optimizer across all dimensions like age, gender, device, day of the week, hour of the day, geography & more
- Ad creator and optimizer that creates new ad based on performance, removes/suggests removing non performing ads
- Placement/ URL optimizer that removes/suggests removal of negative URLs based on client relevancy/spends/goal & many more such use cases
Look into this video to check how Tatvics Google ad optimizer agent helps boost ROI and reduces waste spend & time via Agentic AI – Video link
How To Implement In n8n
Once you have your workflow designed and input data defined, the next step is to implement it in n8n. n8n is a powerful no-code workflow automation tool that allows you to connect your Google Ads account with AI agents, filters, and notifications to automate optimization
- Set up HTTPs node (Gets live data from the google ads account)
- Set up other nodes to filter/edit/merge/split (Keep the data you wish to)
- Set up the AI agent – write a precise prompt (Test out the best models to get the most precise output, try different versions of gemini, gpt and other LLMs)
- Get the output on email (you will need to create credentials for this which can be used to send output over email to anyone you want to)
This is a simple workflow that can be used but when you need to process a lot of data via the API the workflow will be more complex
Best Practices
With automation you need to ensure that it delivers accurate results that are reliable
- Start Small: Build a very small workflow to test if the output is accurate or not and then keep expanding
- If changes are automated, log actions and see if that change made an impact or not based on that learnings you can modify actions
- Monitor results for 1-2 weeks initially, look at the impact of ROAS, CPA, CTR, Conversions
Future Enhancement
There are a lot of possibilities for further enhancement. You can keep enhancing your workflow by adding/integrating GA4, MMPs, third party solutions, alert system, looker studio for graphical representation, anomaly detection & more. This is how you can consolidate everything into one and do everything in lesser time at an optimal spend. This keeps the advertiser, the agent and the campaign manager happy!
Then why waste time & money with doing things manually?
Do things different and catch up with the market
