Automation Developer Needed – Google Display Ads Campaign Creation Using Claude Code / AI Overview

@rajat07me

Your bottleneck is not campaign creation itself — it’s turning 20–40 new clients a day into a reliable pipeline without publishing weak or broken Display campaigns. The right way to build this is as a production workflow with queueing, status tracking, validation, retry logic, and approval checkpoints, not a brittle sheet-to-API script. I’d structure it so each client moves from sheet intake to site analysis, asset/copy generation, campaign build, QA, and then human review when confidence is low. I’ve worked on AI automation and API-driven workflow systems where the real challenge was scale, exception handling, and making outputs usable by an operations team. For this project, Google Ads API, Sheets sync, website extraction, asset rules, duplicate prevention, and controlled launch logic are the core pieces, and that is the side of automation I focus on rather than just “making AI generate something.” I can also help define a clean review dashboard/status model so your team only touches flagged cases. - Do you already have a fixed campaign template/rule set for budgets, audiences, exclusions, and naming? - Should version one generate image assets automatically, or should it first prioritize copy + campaign build using client-site assets where available? - Do you want this bid to cover the first working phase/MVP, or the full end-to-end production system in one go?

@Tanmoy236

Hi There! I specialize in AI automation and Google Ads API development, with 9+ years of experience building scalable production systems for high-volume campaign workflows. Here’s how I can help: 1. Automate Google Sheets intake, website analysis, AI creatives, and ad copy. 2. Build Google Ads API campaign creation with targeting, budgets, and statuses. 3. Add QA, error handling, logging, and scalable processing for 20–40 clients daily. Can you share your current Google Sheet structure and Google Ads API setup?

@arturg6

Hello, "Claude‑Driven Google Ads Pipeline From Sheet To QA" – you need a production‑grade system that reads new display clients from Google Sheets, uses AI to build creatives and copy, then pushes campaigns into Google Ads with proper safeguards and status tracking. I’ve built AI automation systems before — for example, an LLM‑powered modular proposal engine with structured workflows and API integration: https://www.freelancer.com/projects/ai-content-creation/Powered-Modular-Proposal-Engine/reviews. My plan here is: a Python/Node backend with queues that watch your Google Sheet, fetch website data, run Claude prompts to extract business/branding and generate headlines/descriptions, call an image‑generation API for responsive display assets, then use the Google Ads API to create campaigns following your standard structure. Every step writes status back (Ready → Processing → Creative Generated → Campaign Created → QA → Live/Error), with error handling, retries and a simple dashboard for human review before anything goes live. Which part should we prototype first — the Sheets → website analysis → Claude summary, or the Google Ads API campaign creation flow? Looking forward to working with you. Artur Giżycki

@arshman18

Hi, I appreciate the opportunity to help automate your Google Display Ads campaign creation process. It sounds like you need a robust system that efficiently handles a high volume of clients, from analyzing their websites to generating tailored ad creatives and setting up campaigns in Google Ads. My approach would involve building a seamless integration between Google Sheets, Claude Code, and the Google Ads API to ensure a streamlined workflow. I have extensive experience with AI automation and API integrations, particularly with the Google Ads API, which is crucial for your needs. By prioritizing reliability and including necessary checkpoints for quality control, I can create a system that not only processes campaigns efficiently but also flags any issues for manual review when needed. Best regards, Muhammad Arshman

@nazmussakib

Hello Sir, Consider it as done. Able to start right now and build the production workflow from Google Sheets → website analysis → AI creative/copy generation → Google Ads API campaign creation → QA → approval/launch. I can structure it with Python, Google Sheets/API integrations, web data extraction, AI APIs, OAuth, queues, logging, retries, duplicate prevention, and human-review checkpoints so 20–40 new clients per day can be processed reliably. I’ll design the system to write clear statuses and errors back to a management layer rather than guessing when required information is missing. For the AI layer, I can integrate Claude/API-based processing with image-generation services and automate the campaign rules you provide. I’ll focus on scalable architecture, API rate limits, validation, and exception handling so the system can grow toward hundreds or thousands of campaigns. Thanks, Nazmus S

@ranjika08

The main risk here is scale: when 20–40 display clients are coming in daily, even small failure points in scraping, creative generation, or Google Ads API calls can create a serious backlog. I’d approach this as a staged automation system with a queue, processing states, validation rules, retry/error logging, and a manual-approval layer so the workflow handles volume without blindly pushing campaigns live. My experience is strongest where AI has to work inside real operational systems rather than in isolated demos. In your case, the important part is connecting Google Sheets, website analysis, Claude-driven content generation, asset preparation, and Google Ads campaign creation into one dependable flow that your team can supervise. That is very different from a light no-code automation, and your brief correctly points that out. A practical first build can automate the 90% repetitive layer and route uncertain cases to your staff cleanly. - Are the Google Ads accounts already under one manager structure with standardized permissions/auth flow? - Do you already have approved brand/creative rules for industries that need tighter compliance handling? - Would you prefer statuses to remain inside Google Sheets first, or do you want a lightweight dashboard from the beginning?

@Joya1996

The main risk here is scale: when 20–40 display clients are coming in daily, even small failure points in scraping, creative generation, or Google Ads API calls can create a serious backlog. I’d approach this as a staged automation system with a queue, processing states, validation rules, retry/error logging, and a manual-approval layer so the workflow handles volume without blindly pushing campaigns live. My experience is strongest where AI has to work inside real operational systems rather than in isolated demos. In your case, the important part is connecting Google Sheets, website analysis, Claude-driven content generation, asset preparation, and Google Ads campaign creation into one dependable flow that your team can supervise. That is very different from a light no-code automation, and your brief correctly points that out. A practical first build can automate the 90% repetitive layer and route uncertain cases to your staff cleanly. - Are the Google Ads accounts already under one manager structure with standardized permissions/auth flow? - Do you already have approved brand/creative rules for industries that need tighter compliance handling? - Would you prefer statuses to remain inside Google Sheets first, or do you want a lightweight dashboard from the beginning?

@webdinfotech

Hello, I would be happy to build an automation system for creating Google Display Ads campaigns using Claude Code, Google Sheets plus the Google Ads API. I have strong experience in AI automation, Google Ads, API integrations and workflow development, I can automate the flow from client data to website analysis, creative generation, ad copy and campaign setup. The system can read Google Sheets, extract business and branding information from websites, and use Claude/API workflows to generate headlines, descriptions, CTAs and display assets. I can also build the Google Ads API integration for campaign creation, budgets, targeting, ad groups, Responsive Display Ads, assets and landing pages while following your campaign rules. OAuth, queues, logging, retries and duplicate prevention will support your 20–40 new clients per day. My focus will be reliability and controlled automation. I’ll implement status tracking such as Ready → Processing → Creative Generated → Campaign Created → QA → Live/Error, with validation for missing data, invalid URLs, API failures and creative issues. Anything uncertain can be routed for human review. I can review your Google Sheet, campaign structure and rules first, then recommend the architecture and flow. The goal will be to automate 90%+ of repetitive setup while keeping QA checkpoints. Please share your client sheet and campaign rules, and we can discuss the scope, budget and timeline on a call. Best Regards, Manmohan

@TechizeBuilder

Dear Client, I read "Automation Developer Needed – Google Display Ads Campaign Creation Using Claude Code / AI Overview" carefully and understand you need hands-on Claude/Anthropic expertise to build or integrate an AI assistant that actually works reliably. My hands-on experience with Claude (Anthropic), Claude Code aligns directly with what you need. I've built production integrations with the Claude API — prompt engineering, tool use, agentic workflows and RAG pipelines — tuned for accuracy, cost and latency, and I can bring that same rigor to your project. A few quick questions to get us started: 1. Which Claude model and use case are you targeting — chat assistant, agent, RAG, or something else? 2. Do you have existing prompts/data, or should we design the pipeline from scratch? 3. What's your expected usage volume, so we can plan for cost and rate limits? Thanks & Regards, Deepak

@binayatri

Hi, The key here is building a reliable production pipeline, not just connecting a few APIs. I’d structure it around Google Sheets → queued job → website/brand extraction → AI copy & creative generation → Google Ads API campaign creation → automated QA → approval/live, with retries, rate-limit handling, duplicate protection, logging, and manual review for uncertain cases. I have 13+ years in full-stack development, AI automation, Python/Node.js, API integrations, web extraction, Google services, and production workflow systems. I’d keep the architecture modular so the same pipeline can scale from 20–40 clients/day to much higher volume. I can build the complete system and document the flow clearly. Happy to discuss your existing campaign structure and Google Ads API setup. Let's connect and get started soon. Best regards, Binaya T.

@mayr81

Build a production-grade automation to create Google Display (Responsive Display) campaigns at high volume. Pipeline: poll Google Sheets for new “Ready” clients → analyze website content for services, locations, brand cues → generate ad copy and asset plans with Claude Code (plus image APIs when needed) while reusing provided logos/images/colors → assemble compliant responsive display assets → create campaigns via Google Ads API with your naming/budget/targeting rules → run QA gates (URL validity, missing assets, duplication checks, API error handling, disapproval risk) and write statuses back to the Sheet. Include queue management, retries, idempotency, rate-limit handling, detailed logging, and human approval checkpoints so nothing goes live without confidence. The system will process 20-40 clients/day reliably with robust error reporting and “flag for manual review” flows for edge cases.

@emrahg7

Hi, I'd build this as a queue-based pipeline, not a single script, because that's the only way it survives running 20-40 clients a day without falling over. Each client moves through its own tracked job (Ready, Processing, Creative Generated, etc.), so if one site fails to scrape or one Google Ads call errors out, that one client gets flagged for review and everything else keeps moving. Flow-wise: a worker reads new rows from Sheets, scrapes the site for branding, colors, logo, copy angles, and service area, then hands that to Claude for ad copy and an image pipeline for display assets. Once assets pass basic checks, it builds the campaign through the Google Ads API and drops it into a QA/approval state before going live. I've built retry logic and rate-limit handling for API-heavy systems like this before, and duplicate prevention is baked in from the start, not bolted on later. I've used Claude Code extensively for exactly this kind of content and decision-making step. Given the scope, I'd estimate 2 days to get a working version processing real clients. What's your current Google Ads account structure, one MCC with sub-accounts per client, or something else? Best, Emrah

@SidUSA

Hi We are available to take this on and get your automated Google Display Ad creation system working perfectly. The main issue with high-volume automation pipelines is usually handling queue management, rate limits, and asset validation across the Google Ads API specifically. Are you planning to use Python with robust queuing for better retry handling and do you want the status updates written back as a clean table or structured logs in your tracking dashboard? We recently fixed a similar production automation for a marketing firm that needed custom metadata and high-volume asset generation injected into ad campaigns. I used the Google Ads API to hook into campaign creation events and built an AI-powered pipeline that validated inputs before using API batching to update accounts. I corrected their rate-limit handling and error structures to ensure campaigns didn't fail during high-load syncing. Our fix stopped their campaign data from being lost during spikes and made the whole scaling process way faster for their team. We are eager to discuss the project further. Reach out to initiate a conversation! Best regards, Quantum Code Solutions

@RaqiOfficial

Hello, At 20 to 40 new clients per day, the critical problem is not generating a single Google Display campaign, but building a reliable pipeline that can process accounts repeatedly without silently creating bad campaigns. I would structure the workflow around Google Sheets status management, website extraction, AI-assisted creative and copy generation, Google Ads API operations, validation, retries, and explicit manual-review states. The Google Ads API layer should be idempotent so retries do not create duplicate campaigns, while each stage should record its inputs, outputs, errors, and API identifiers. Creative generation also needs validation before submission because missing assets, incorrect dimensions, policy issues, or incomplete client data can stop an otherwise automated workflow. Claude can handle reasoning and content generation, while deterministic code should control campaign creation and QA. The key architectural question is whether each client maps to a separate Google Ads customer account or multiple campaigns within shared accounts, since that changes authentication, permissions, and campaign creation logic substantially. Have a nice day

@AndrewJSMAN

I've built and scaled automated Google Ads campaign systems using Claude Code, Google Ads API, and Google Sheets API for high-volume clients. This is routine work—Claude handles scraping and content extraction while the Google Ads API pushes campaigns; Google Sheets tracks status via webhooks. I'll deploy a Python-based worker queue (Celery) that pulls new rows from Sheets, runs Claude for site analysis, generates creatives with image APIs, validates assets, then pushes campaigns via the Google Ads API with exponential backoff and duplicate checks. Errors route to a dedicated QA dashboard; manual review only when confidence drops below 95%. All rate limits, retries, and logging are handled through the queue, ensuring reliability at 40+ clients/day. I can start immediately. Thanks, Andrii.

@nicolasarmandoc

Hi, This is the kind of AI automation where the important part is not just generating ads, but making the whole pipeline reliable at 20 to 40 clients per day. I’d build it as a proper queued workflow with clear states, retries, validation, and human approval rather than a fragile chain of automations. Are you already using a Google Ads Manager Account with API access across all client accounts, or should the OAuth and account authorization layer be included as well? I’d use Python or Node.js for the orchestration layer, Google Sheets as the intake/status interface initially, and a database plus queue for processing state and idempotency. Website analysis would extract structured branding, services and content, then the AI layer would generate copy and creative inputs. The Google Ads API would handle campaign and asset creation, with validation before anything reaches the approval stage. Rate limits, duplicate detection, retries, API errors and manual-review cases would all be logged. I can build this with future scale in mind rather than treating it as a simple automation. Best regards, Nicolas.

@Aqsa4400

Hello, I have carefully reviewed your project description and understand your need for an experienced AI Automation Developer to create an automated system for Google Display Ad campaign creation using Claude Code, AI, Google Sheets, and the Google Ads API. With over 5 years of experience in Google Ads, I am confident in my ability to design and build a reliable production system that can efficiently process a large volume of clients while ensuring accuracy and quality. To get a better sense of my skills, please visit my portfolio: https://www.freelancer.pk/u/Aqsa4400 I would love to discuss your project further. Please start a chat so we can explore how I can help you achieve your automation goals. Best regards, Aqsa Usman

@C0RETECHIES

Hi, You need an asynchronous engine that pulls client data from Google Sheets, scrapes their websites for brand assets, and uses Claude to generate responsive display ad copy. It must then push configurations to Google Ads via API, staging them for manual review. Technical approach: A Node.js backend using a Redis queue (BullMQ) to handle rate limiting and API retries. We will use Google Sheets API for ingestion, Puppeteer for scraping, Claude 3.5 Sonnet for copy/context synthesis, and the Google Ads API for campaign construction. Core modules: - Ingestion Queue: Polls Sheets, queues jobs, and tracks state. - Extraction Engine: Scrapes URLs for logos, branding, and service data. - Generative Pipeline: Feeds scraped context to Claude for headlines/descriptions. - Ads API Connector: Builds Ad Groups, assets, and geographic targeting. - Exception Handler: Flags API rejections or missing assets for QA. Relevant systems: - Automation Lead Gen (8-Agent AI pipeline mapping web data to automated workflows) - AI Content Generator (Structured content creation via multi-step LLM chains) Implementation strategy: My Claude experience centers on complex enterprise data extraction. I will build this starting with an MVP connecting Google Sheets directly to the Ads API. Once stable, I will inject the scraping and Claude generation layers. All campaigns will default to a paused state for your team's QA. Regards, Rohit

@emilesd617

Hi, I am a database developer with 8 years of rich experience in software development, with a background in database administration and data analysis. I am familiar with SQL, Oracle, Database Administration, Database Programming, Data Analysis, Project Management, AI Research, and AI Content Creation. I can help with the technical and data-related parts of your dissertation research, including preparing SQL/Oracle data, organizing and analyzing research data, and supporting the study of how product and project managers experience AI-generated outputs in their work. I can also help structure the data and analysis process so the results are clear, consistent, and easy to review. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.