Meta Ads Report Automator: AI-ready analytics without the routine.
Meta Ads Report Automator: AI-ready analytics without the routine in Ads Manager
Problem: The main pain point for media buyers and marketers when running campaigns in Meta is the collection and structuring of statistics. To analyze results using AI, one has to spend hours digging through the dashboard: taking screenshots, gathering exports, copying numbers, and manually consolidating data so that the neural network receives the correct context.
Solution:
I developed a local CLI tool in Node.js + TypeScript that turns this routine into a single terminal command. The service directly accesses the Meta Graph API and instantly collects a complete slice of data across all campaign levels, generating a ready-made, structured .md report.
This file is perfectly optimized for uploading to ChatGPT (or other LLMs). As a result, you receive concentrated analytics, conclusions, and an optimization strategy without unnecessary actions. Instead of manually collecting data, focus on decision-making and in-depth work.
Key functionality:
Deep data export: collection of data on campaigns, ad sets, specific ads, placements, and demographics (age/gender).
Flexible period comparison: instant slices for today, yesterday, last_7d, or maximum.
AI-Ready format: automatic generation of a complete Markdown report, ready for feeding to neural networks.
Quick access: a set of CLI commands (via npm scripts) for daily monitoring without opening a browser.
Security: automatic token and access rights verification for advertising accounts.
Metrics collected (Full funnel):
Base: Impressions, Reach, Spend, Frequency.
Engagement: Clicks, Link Clicks, Video Views.
Effectiveness (Unit economics): Leads, Cost per Lead (CPL), CPC, CTR, CPM.
Practical value for business:
The tool provides instant answers to critical questions without the need to build custom dashboards in Meta:
Which specific combinations, creatives, and placements are generating results right now?
Which audience (gender/age slice) brings the cheapest leads?
Campaign verdict: scale, optimize, or turn off budget-burning combinations.
Technology stack:
Node.js
TypeScript
Meta Graph API
The project was created as an internal architectural tool to accelerate traffic work, proving its effectiveness in real combat conditions.
#nodejs #typescript #backend #api #cli #graphapi #development #architecture #WebDevelopment
#metaads #facebookads #automation #marketing #analytics #mediabuying #targeting #marketingautomation #dataanalysis #traffic
#ai #chatgpt #neuralnetworks #aiintegration #businessanalytics #optimization/acceleration
Problem: The main pain point for media buyers and marketers when running campaigns in Meta is the collection and structuring of statistics. To analyze results using AI, one has to spend hours digging through the dashboard: taking screenshots, gathering exports, copying numbers, and manually consolidating data so that the neural network receives the correct context.
Solution:
I developed a local CLI tool in Node.js + TypeScript that turns this routine into a single terminal command. The service directly accesses the Meta Graph API and instantly collects a complete slice of data across all campaign levels, generating a ready-made, structured .md report.
This file is perfectly optimized for uploading to ChatGPT (or other LLMs). As a result, you receive concentrated analytics, conclusions, and an optimization strategy without unnecessary actions. Instead of manually collecting data, focus on decision-making and in-depth work.
Key functionality:
Deep data export: collection of data on campaigns, ad sets, specific ads, placements, and demographics (age/gender).
Flexible period comparison: instant slices for today, yesterday, last_7d, or maximum.
AI-Ready format: automatic generation of a complete Markdown report, ready for feeding to neural networks.
Quick access: a set of CLI commands (via npm scripts) for daily monitoring without opening a browser.
Security: automatic token and access rights verification for advertising accounts.
Metrics collected (Full funnel):
Base: Impressions, Reach, Spend, Frequency.
Engagement: Clicks, Link Clicks, Video Views.
Effectiveness (Unit economics): Leads, Cost per Lead (CPL), CPC, CTR, CPM.
Practical value for business:
The tool provides instant answers to critical questions without the need to build custom dashboards in Meta:
Which specific combinations, creatives, and placements are generating results right now?
Which audience (gender/age slice) brings the cheapest leads?
Campaign verdict: scale, optimize, or turn off budget-burning combinations.
Technology stack:
Node.js
TypeScript
Meta Graph API
The project was created as an internal architectural tool to accelerate traffic work, proving its effectiveness in real combat conditions.
#nodejs #typescript #backend #api #cli #graphapi #development #architecture #WebDevelopment
#metaads #facebookads #automation #marketing #analytics #mediabuying #targeting #marketingautomation #dataanalysis #traffic
#ai #chatgpt #neuralnetworks #aiintegration #businessanalytics #optimization/acceleration
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Arseny Antonenko
 Kyiv 14 0
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Available for hire
14 Safes completed
1 arbitration
On the service 4 years
Offer work