Project Name:

Advertising Campaign Performance Optimization with AI

Tools Used

Dropbox: For file storage and triggering the workflow.

Make.com: The automation platform connecting all tools.

Google Gemini API: For AI-powered ad optimization suggestions and predictions.

Clay: For further data processing or CRM integration.

Flow Overview

This automated Make.com flow streamlines the process of analyzing LinkedIn ad performance, using AI to provide actionable optimization strategies and future predictions. By simply uploading a CSV file to Dropbox, you trigger a sequence that extracts key ad metrics, feeds them to the Google Gemini AI for analysis, and then delivers the insights to Clay for further action or reporting. This ensures your ad campaigns are continuously optimized for better results with minimal manual effort.

Step 1: Dropbox - Watch for a New Ad Performance File

The flow begins by constantly monitoring a specified folder in Dropbox. As soon as a new CSV file containing LinkedIn ad performance data is uploaded, it triggers the entire automation sequence.

Step 2: Dropbox - Download the Ad Performance File

Once a new file is detected, Make.com securely downloads the CSV file from Dropbox, preparing it for data extraction.

Step 3: CSV - Parse CSV Data

The downloaded CSV file is then processed by Make.com's CSV parser. This step reads the structured data, converting rows and columns into an accessible format for subsequent operations.

Step 4: Tools - Text Aggregator

The parsed CSV data, which contains individual ad performance records (like impressions, clicks, CTR, spend, and CPC for each campaign), is then consolidated by the Text Aggregator. This combines the relevant data points into a single, cohesive text string, specifically formatted to be understood by the Google Gemini API. This is where your prompt text is created, dynamically inserting the ad performance data.

Step 5: Add a filter

You need to add a filter between step 3 and 4, in order to skip all the empty cells which are imported.

Step 6: HTTP - Make a Request to Google Gemini API

This is the core AI step. The aggregated ad performance data is sent as a prompt to the Google Gemini API via an HTTP POST request. The prompt asks Gemini to analyze the provided data, suggest three specific optimizations to improve performance, and predict the CTR (Click-Through Rate) and CPC (Cost Per Click) for the upcoming week based on current trends.

Step 6 (Optional): Send to Clay

Finally, the intelligent insights, optimization suggestions, and predictions generated by the Google Gemini AI are sent to Clay. This could be used to update a CRM, trigger notifications, populate a dashboard, or initiate further automated marketing actions based on the AI's recommendations.