Workflow Description: Automated Market Research & LinkedIn Ads Analysis Agent

This workflow leverages AI and a suite of specialized tools to automate the process of market research focused on LinkedIn ads, including competitor analysis, marketing copy extraction, and media (image) analysis. It is designed for scalability and automation, making it ideal for marketing teams, researchers, or agencies looking to streamline insights gathering and reporting.

Overview & Goal

The main objective of this workflow is to enable an AI Agent to:

• Receive a keyword, preferred country, and date range from the user.
• Research LinkedIn ads associated with this keyword.
• Identify top competitors running ads for the keyword.
• Analyze both the text and media (images) of the ads to extract high-converting marketing patterns.
• Present the findings in a visually appealing markdown report, including tables and analysis for better readability and decision-making.

This process, when done manually, is time-consuming and prone to human error. By automating it, you can scale your market research efforts, ensure up-to-date analysis, and quickly adapt strategies based on real-time competitor activity.

Workflow Structure

1. User Input & Attachments

• Chat Input: The workflow starts by accepting user input, including keywords and parameters, and optionally, image attachments.
• Chat History: Recent chat messages are stored and retrieved to provide context for follow-up queries, ensuring smooth multi-turn conversations.

2. Information Retrieval Tools

• Google Search Tool: Allows the agent to search Google for relevant information, limited to 3 results per query, in English, focused on the US and New York, and leveraging caching for efficiency.
• URL Retriever: Fetches and extracts content from a list of URLs (including LinkedIn ad library URLs), processes the web pages, and returns structured documents. It can include headings, paragraphs, and select metadata such as product information. The strategy ensures a balanced extraction from all sources.
• Current Date Tool: Provides the current date and time in UTC, which the agent can use to set or validate date ranges for the research.

3. Vision Tool

• Image Analysis: If a LinkedIn ad contains images, the Vision Tool uses AI to extract information from visual content, enabling the agent to include insights from media, not just text.

4. AI Engine

• Anthropic Claude Model (Claude 3.7 Sonnet): The workflow uses this advanced language model to power the agent’s reasoning, summarization, and report generation capabilities.

5. AI Agent Orchestration

• The AI Agent node receives:
  • User input and chat history for context.
  • The Claude LLM for natural language understanding and output.
  • Tools (Google Search, URL Retriever, Vision Tool, Current Date) to augment its capabilities.
  • A specific goal: to analyze LinkedIn ads, identify competitors, extract marketing strategies, and generate a detailed markdown report.
• The agent executes up to 10 iterations or up to 5 minutes per request, using caching and progress reporting for efficiency.

6. Output

• Chat Output: The resulting report is displayed to the user in a chat interface, formatted as markdown with tables and emojis, listing competitors, links, and conversion analysis.

Data Flow Diagram

Why This Workflow is Useful for Scaling and Automation

• Automates Manual Research: Eliminates the need for repetitive manual searches and data extraction, saving significant time.
• Multi-Modal Analysis: Combines text and image analysis for a comprehensive understanding of competitors’ ad strategies.
• Up-to-Date & Repeatable: Always uses the latest ad data and can be run as often as needed, ensuring current insights.
• Customizable Parameters: Easily adjust keyword, country, and date range to suit different market segments or campaigns.
• Consistent Reporting: Produces standardized, visually appealing markdown reports with actionable insights.
• Scalable: Can be run for multiple keywords, markets, or time periods without additional manual effort.
• Integration-Ready: Designed to fit into broader marketing intelligence or automation platforms.

Example Use Cases

• Marketing Teams: Quickly compare competitor ad strategies for new campaigns.
• Agencies: Deliver regular, data-driven LinkedIn ad analyses to clients.
• Growth Hackers: Identify and emulate high-converting ad patterns in new markets.
• Product Managers: Monitor how competitors position similar products over time.

Summary Table: Main Components

By automating the entire workflow, users can obtain rich, actionable competitor ad intelligence with minimal effort, enabling faster and smarter marketing decisions.