Keyword Strategy For Loans Report
AI Agent Training Prompt Objective: Identify keywords related to "student loan forgiveness" that meet the following criteria: High Search Volume (prioritize keywords with consistent monthly searches). Low Competition (keywords with low difficulty scores or fewer authoritative domains ranking for them). Buyer Intent (keywords indicating users are ready to take action, e.g., "apply," "consultation," "services," "calculator," "eligibility check"). Key Instructions for the Agent: Focus on Keyword Types: Long-tail phrases (e.g., "student loan forgiveness application requirements"). Question-based queries (e.g., "How to qualify for Biden student loan forgiveness?"). Buyer-intent keywords (e.g., "student loan forgiveness lawyer consultation" or "best loan forgiveness programs for teachers"). Localized terms (e.g., "student loan forgiveness California"). Avoid: Generic terms (e.g., "student loans"). Overly competitive keywords (e.g., "FAFSA"). Informational-only queries (e.g., "what is student loan forgiveness?"). Data Sources & Tools (hypothetical): Use SEO tools (e.g., SEMrush, Ahrefs, Ubersuggest) to analyze search volume and competition. Scrape forums, Reddit, or Q&A sites (e.g., Quora) for recurring questions/pain points. Analyze competitor gaps (websites ranking for loan forgiveness content). Prioritization Framework: Score Keywords: Combine search volume, competition, and buyer intent signals. Content Angles: Highlight keywords that align with conversion goals (e.g., "student loan forgiveness application help," "PSLF certification specialist"). Example Output Format: Keyword: "student loan forgiveness eligibility calculator" Search Volume: [e.g., 5k/mo] Competition: Low (Difficulty Score: 25/100) Intent: Buyer (users likely seeking tools/services) Content Strategy: Create a free eligibility calculator tool with a lead magnet. Keyword: "PSLF form help 2024" Search Volume: [e.g., 3k/mo] Competition: Medium (Difficulty Score: 40/100) Intent: Buyer (users needing assistance with paperwork) Content Strategy: Offer a paid document review service or webinar. Additional Analysis to Include: Competitor Gaps: Identify keywords competitors rank for but lack detailed/updated content. Trends: Highlight rising keywords (e.g., "new SAVE plan loan forgiveness"). Content Ideas: Blog posts, landing pages, or tools tailored to high-priority keywords.
subagent1
SUBAGENT 1: "Keyword Researcher" Final Output: keywords_raw.csv Sequence of Actions: 1) Research Topic • Description: Briefly research "student loan forgiveness" to gather core subtopics. • Output: A short research summary (roughly 300-500 characters). 2) Brainstorm Keywords • Description: From the research summary, provide about 5 relevant keywords aligned with the user's criteria. • Output: A brief list of 5 keywords with minimal commentary. 3) Compile Raw CSV • Description: Convert the 5 keywords into a text-based CSV file (keywords_raw.csv) with one keyword per line. SUBAGENT REQUIRED INPUT: {taskObjective} SUBAGENT FINAL OUTPUT: [keywords-raw]
subagentX-refined
[subagent1-refined]
subagentXmermaid
graph TD A[Start: Receive Task Objective] --> B[Generate Research Summary] B --> C[Store Research Summary] C --> D[Generate 5 Keywords] D --> E[Store Keywords List] E --> F[Convert to CSV Format] F --> G[Save keywords_raw.csv] G --> H[End: Return keywords-raw] subgraph Research Phase B C end subgraph Keyword Generation D E end subgraph CSV Creation F G end style A fill:#f9f,stroke:#333 style H fill:#f9f,stroke:#333 style B fill:#bbf,stroke:#333 style C fill:#bbf,stroke:#333 style D fill:#ddf,stroke:#333 style E fill:#ddf,stroke:#333 style F fill:#bfb,stroke:#333 style G fill:#bfb,stroke:#333
https://static.aiz.ac/1738651545-mermaid/mermaid-1.png