# DataForSEO Integration Guide ## Overview DataForSEO provides real keyword data, competitor intelligence, and AI search optimization metrics. This replaces guesswork with data-driven decisions. **MCP Access:** DataForSEO tools are available through MCP. Use them directly in your research workflow. ## Budget Protocol - **Per session limit:** $0.50 (unless user explicitly approves more) - **Monthly budget:** ~$10 - **Always report:** Show user what API calls you're making and estimated cost ## Core Principle Start with seeds → expand with related → filter by opportunity → verify with SERP. Don't chase high-volume competitive keywords. Find gaps where we can win. --- ## For @spy: Competitive Intelligence ### Competitor Keywords ``` Tool: dataforseo_labs_google_ranked_keywords Use: See what keywords competitors rank for Target: fal.ai, replicate.com, runware.ai, cloudinary.com ``` ### Backlink Analysis ``` Tool: backlinks_summary, backlinks_referring_domains Use: Where competitors get links, potential outreach targets ``` ### Domain Intersection ``` Tool: dataforseo_labs_google_domain_intersection Use: Find keywords multiple competitors rank for (validated demand) ``` ### LLM Mentions (GEO) ``` Tool: ai_optimization_llm_mentions_search Use: Check if Banatie or competitors mentioned in AI responses Platform: chat_gpt, google (AI Overview) ``` --- ## For @strategist: Keyword Research ### Search Volume ``` Tool: keywords_data_google_ads_search_volume Use: Get real monthly search volume for keyword list Input: Up to 1000 keywords per request ``` ### Keyword Difficulty ``` Tool: dataforseo_labs_bulk_keyword_difficulty Use: Score 0-100, lower = easier to rank Filter: KD < 50 for realistic targets ``` ### Related Keywords ``` Tool: dataforseo_labs_google_related_keywords Use: Expand seed keywords, find long-tail opportunities Depth: 1-4 (start with 1, go deeper if needed) ``` ### Search Intent ``` Tool: dataforseo_labs_search_intent Use: Classify keywords as informational/navigational/commercial/transactional Match: Content type should match intent ``` ### AI Search Volume (GEO Priority) ``` Tool: ai_optimization_keyword_data_search_volume Use: Keywords popular in AI search (ChatGPT, Perplexity) Why: Early indicator of emerging queries ``` ### Research Workflow 1. **Start with seeds** (3-5 per topic) 2. **Get search volume** for seeds 3. **Expand** top 3 by volume with related keywords 4. **Filter:** Volume > 50, KD < 50 5. **Check intent** for finalists 6. **SERP analysis** for top candidates --- ## For @seo: Optimization & Verification ### SERP Analysis ``` Tool: serp_organic_live_advanced Use: See current top 10 results, SERP features present Check: Featured snippets, PAA, video results ``` ### On-Page Analysis ``` Tool: on_page_instant_pages Use: Technical SEO check of specific URL After: Publishing, verify optimization ``` ### LLM Responses (GEO) ``` Tool: ai_optimization_llm_response Use: See how AI models answer our target queries Why: Optimize content for AI citations ``` --- ## Key Learnings **Problem-aware keywords often have zero volume.** People search for solutions, not problems. "placeholder images slow" = 0 volume. "generate images api" = real volume. **Related keywords > seed keywords.** Your initial guesses are rarely the best targets. Let data guide expansion. **Brand keywords are useless.** "cloudinary pricing" means they already chose Cloudinary. Target problem/solution queries. **Low KD + decent volume = opportunity.** Don't chase "ai image generation" (KD 80+). Find "generate images for nextjs" (KD 30, volume 200). --- ## Output Format When reporting keyword research: ```markdown ## Keyword Research: [Topic] ### Seeds Analyzed | Keyword | Volume | KD | Intent | |---------|--------|----|----| | ... | ... | ... | ... | ### Top Opportunities | Keyword | Volume | KD | Rationale | |---------|--------|----|----| | ... | ... | ... | Why this is a good target | ### Recommendations [What content to create based on this data] ### API Calls Made [List of tools used, estimated cost] ```