AI Content Opportunity Scout

🧠 What It Is

The AI Content Opportunity Scout is the second analysis stage, acting as the keyword and strategy expert in the ecosystem. It takes the trending topics identified by the Topic Trend Aggregator and enriches them with valuable SEO and keyword data.

Currently, this actor uses mock data to simulate calls to the Google Ads API, allowing for full pipeline testing without incurring API costs.

✨ Key Features

• Keyword Enrichment: For each topic, it simulates a Google Ads API call to fetch key metrics like average monthly search volume, competition level, and estimated top-of-page bid costs.
• AI Cluster Score: It calculates a proprietary ai_cluster_score (0-100) that synthesizes the topic's trend score, search volume, and competition level into a single, actionable metric. It also boosts the score for topics relevant to AI and technology.
• Strategic Recommendation: Based on the competition level and AI score, the actor determines the best_strategy for content creation, such as "Top Opportunity," "Niche Topic," or "High Competition, Worth the Investment."
• Long-Tail Keyword Extraction: It processes the key entities from the source articles to identify and analyze relevant long-tail keywords, providing deeper content opportunities.

⚙️ How It Works

1. Topic Ingestion: The actor fetches the dataset of trending topics from the upstream Topic Trend Aggregator, filtering for topics that meet a minimum trend_score.
2. Concurrent Keyword Lookups: It runs concurrent (mock) API calls for each high-priority topic to gather keyword metrics efficiently.
3. Scoring and Strategy Analysis: For each topic, it merges the keyword data, calculates the ai_cluster_score, and determines the best_strategy.
4. Data Output: The actor pushes the final, enriched data to its default dataset, making it available for the next stage in the pipeline, the Sentiment Compass.

📥 Inputs

• source_dataset_id: The ID of the dataset from the Topic Trend Aggregator to be used as input.
• min_trend_score: A threshold to filter out topics with low momentum.
• language_code and location_ids: Parameters to define the target language and region for the (mock) keyword metric lookups.
• Secret API Keys: While currently using mock data, the input schema is configured to securely accept all necessary API keys for a future live integration with Google Ads and OpenAI.

📤 Outputs

The actor enriches the incoming dataset, adding several key fields to each topic to provide a comprehensive strategic overview:

• search_volume (Integer): The estimated average monthly searches for the topic.
• competition (String): The competition level for the topic ("Low," "Medium," or "High").
• ai_cluster_score (Integer): The proprietary score indicating the overall opportunity.
• best_strategy (String): The AI-generated recommendation for how to approach content creation.
• long_tail_opportunities (Array): A list of related long-tail keywords with their own volume and competition data.