Oct 15 (edited) • General discussion
n8n Automation using GenAI to Analyze Digital Ad Campaign Performance in 7 Steps
Are you running several ads across various digital platforms like Google, Meta, LinkedIn and others? It becomes cumbersome to collate all the data and analyze it effectively.
Check this step-by-step guide to create a n8n automation workflow to analyze all the ad campaigns you run and get a report with suggestions within minutes!
Step 1 - Fetch campaign data from each platform
- Node: HTTP Request / native n8n integrations for Google Ads, Facebook Ads, Instagram Ads, LinkedIn Ads.
- Pull metrics for campaigns: impressions, clicks, CTR, spend, conversions, landing page URL, UTM tags, dates.
- Filter for desired time period (e.g., last 7/30 days).
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Step 2 - Normalize & merge data
- Node: Set / Merge / Function.
- Standardize column names across platforms: campaign_name, product_service, impressions, clicks, CTR, spend, conversions, cost_per_action, landing_page_url.
- Add a platform column to identify origin.
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Step 3 - Group data by product/service
- Node: GroupBy / Function.
- Sum impressions, clicks, spend, conversions for each product/service across campaigns within each platform.
- Calculate derived metrics: CTR, cost-per-click (CPC), conversion rate, cost-per-action (CPA).
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Step 4 - Analyze engagement & conversions per platform
- Node: Function / HTTP Request (Gemini).
- For each platform, pass grouped metrics to Gemini and ask it to:
- - Identify engagement trends.
- - Compare reach vs actions.
- - Detect underperforming campaigns (low CTR, high CPC, low conversions).
Suggested concise Gemini instruction: “Analyze these grouped campaign metrics per platform. Highlight trends, underperforming campaigns, and suggest why performance may be low.”
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Step 5 - Cross-platform comparative analysis
- Node: Gemini.
- Input: aggregated metrics for each product/service across platforms.
- Ask Gemini to:
- - Compare performance across platforms.
- - Suggest which campaigns to increase budget for.
- - Recommend tweaks to ad copy, targeting, or landing pages.
- - Identify overall strengths and weaknesses.
Output: JSON with insights, recommendations, suggested budget shifts, landing page improvements.
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Step 6 - Store results
- Node: Google Sheets Append Row.
- Save per-product/service: platform-wise metrics, comparative insights, recommendations, date, campaign IDs.
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Step 7 - Send report
- Node: Email / Slack.
- Summary of key insights: top-performing campaigns, underperformers, suggested actions, and recommended budget changes.
- Attach Google Sheet link for detailed review.
Please share your questions and feedback in the comments.
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n8n Automation using GenAI to Analyze Digital Ad Campaign Performance in 7 Steps
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