How to Build an Agent That Analyzes Competitors’ Content on TikTok & Instagram Using GPT-5

STEP 1: Set Up Your Form Input

Create a form trigger to capture your account handle and up to 3 competitor accounts
Add checkbox options for platform selection (Instagram / TikTok)
Include a number field to specify how many posts to analyze per account

STEP 2: Configure API Credentials

Open the workflow configuration node and add your OpenAI API key
Set up Apify credentials in n8n for Instagram and TikTok scrapers
Connect your Google Sheets account for result logging
Create a spreadsheet with columns:
- timestamp
- own_account
- competitors
- platforms
- posts_analyzed
- summary

STEP 3: Build Platform Routing Logic

Add a switch node to detect which platforms the user selected
Create separate routes for Instagram and TikTok scraping
Configure the router to support parallel execution when both platforms are selected

STEP 4: Scrape Content from Platforms

Configure the Apify Instagram scraper with account URLs and post count limits
Set up the Apify TikTok scraper using profile handles and results-per-page
Increase memory allocation to 2048 MB to handle large batches
Add a filter node to extract only image posts with valid URLs

STEP 5: Analyze Images with GPT-5 Vision

Create a code node that sends each image URL to the OpenAI Vision API
Structure prompts to extract:
- Color palette (3–5 hex codes)
- Composition style
- Mood / emotion
- Text and design elements
Implement JSON parsing to handle AI responses reliably
Attach account name and platform metadata to each analysis result

STEP 6: Aggregate and Generate Report

Use an aggregate node to collect all image analysis results into a single object
Send the aggregated data to GPT-5 with a competitive analysis–focused prompt
Structure the report into:
- Competitive matrix
- Platform-specific patterns
- Cross-platform insights
- Recommended actions

STEP 7: Log Everything to Google Sheets

Map the analysis summary and metadata to spreadsheet columns
Append a new row with timestamp, accounts analyzed, platforms, and total posts
Enable update mode to track historical analyses over time

📝 Blog Post Article

How to Build an AI Agent That Analyzes Competitors’ TikTok & Instagram Content with GPT-5

In competitive digital marketing, understanding why certain visuals perform well is just as important as knowing what was posted. With the rise of multimodal AI, it’s now possible to automate competitive visual analysis across platforms like TikTok and Instagram.

This guide walks through how to build an end-to-end AI agent that scrapes competitor content, analyzes visual patterns using GPT-5 Vision, and generates structured competitive insights—fully automated.

1. Capturing the Right Inputs

The foundation of your agent starts with structured inputs. A simple form trigger allows users to define:

Their own social account
Up to three competitor accounts
Which platforms to analyze
How many posts per account should be included

This makes the workflow flexible, reusable, and scalable for different competitive scenarios.

2. Secure API & Tool Configuration

The agent relies on three key integrations:

OpenAI (GPT-5) for image and competitive analysis
Apify for scraping Instagram and TikTok content
Google Sheets for logging and historical tracking

By centralizing credentials in your workflow configuration, you keep the system secure and easy to maintain.

3. Intelligent Platform Routing

Not all analyses require every platform. Using a switch or router node, the agent dynamically routes execution based on user selection:

Instagram-only
TikTok-only
Or both, running in parallel

This reduces unnecessary API calls and speeds up execution.

4. Scraping Only What Matters

Instead of collecting everything, the agent focuses on image-based posts—the most visually comparable content type across platforms.
Filters ensure only valid image URLs are passed downstream, while increased memory allocation allows for larger batch processing without failures.

5. Visual Intelligence with GPT-5 Vision

This is where the agent becomes truly powerful.

Each image is analyzed by GPT-5 Vision to extract:

Dominant color palettes
Visual composition styles
Emotional tone and mood
Typography and text layout patterns

Results are returned in structured JSON, enriched with account and platform metadata, making them easy to aggregate and compare.

6. Automated Competitive Reporting

Once all images are analyzed, the agent aggregates the results and sends them back to GPT-5—this time with a higher-level competitive analysis prompt.

The final report includes:

A competitor comparison matrix
Platform-specific design trends
Cross-platform visual insights
Clear, actionable recommendations

This turns raw visual data into strategic intelligence.

7. Persistent Logging & Trend Tracking

Every run is logged to Google Sheets with timestamps and metadata. Over time, this creates a historical dataset you can use to:

Track competitor evolution
Spot emerging visual trends
Measure how your own content strategy adapts

Final Thoughts

By combining automated scraping, multimodal AI, and structured reporting, this agent transforms competitor analysis from a manual task into a repeatable system. It’s not just about seeing what competitors post—it’s about understanding the visual language that drives performance.