DataForSEO Brain

Play: Content Strategy Brief

4 min read

Play: Content Strategy Brief

Turn a topic into a writer-ready brief: scrape the live SERP, map demand and intent with Labs, and read citation sentiment with Content Analysis. Sits under DataForSEO Brain → Flows.

Overview

This flow produces a data-backed content brief. It reads the actual SERP a piece must compete in (SERP API), sizes and shapes demand around the topic (Labs keyword and market analysis), and gauges how the topic is discussed across the web (Content Analysis sentiment and trends). The result is a brief that tells a writer what to cover, at what depth, and with what angle.

Trigger

A content topic is selected and needs a brief: a new article in a cluster, a refresh of an underperforming page, or a pillar build. Inputs are the target keyword/topic plus location_code and language_code.

Endpoints used (in order)

  • POST /v3/serp/google/organic/live/advanced (the live competitive SERP).
  • POST /v3/dataforseo_labs/google/keyword_ideas/live and /related_keywords/live (subtopics).
  • POST /v3/dataforseo_labs/google/search_intent/live (intent of the topic + subtopics).
  • POST /v3/dataforseo_labs/google/top_searches/live (demand/trend context).
  • POST /v3/content_analysis/search/live and /summary/live (citation corpus).
  • POST /v3/content_analysis/sentiment_analysis/live (sentiment + connotations).

Pipeline

  1. Scrape the SERP: call serp/google/organic/live/advanced for the target keyword. Read result.items[] to capture the ranking organic URLs (titles, descriptions, is_featured_snippet), the item_types present (people_also_ask, featured_snippet, ai_overview, video, etc.), and the people_also_ask/related_searches elements for questions to answer.
  2. Map subtopics: run Labs keyword_ideas and related_keywords to build the semantic field around the topic, with search_volume and inline keyword_difficulty to weight coverage.
  3. Tag intent: pass the topic plus key subtopics through search_intent to confirm whether the brief should be informational, commercial, etc., and shape the format accordingly.
  4. Add demand context: use Labs top_searches (and optionally Keywords Data trends) to see rising vs declining interest and seasonal timing.
  5. Read the discourse: run Content Analysis search for the topic to pull the citation corpus (titles, snippets, page_category, domain_rank, and content_info.sentiment_connotations), then summary for the aggregate view.
  6. Gauge sentiment: run sentiment_analysis for connotation_types (positive/negative/neutral) and sentiment_connotations (anger, happiness, love, sadness, fun) plus top_domains and text_categories to pick an angle and tone.
  7. Assemble the brief: target keyword + subtopics to cover, the questions (PAA) to answer, SERP features to win, recommended depth/format from competitor analysis, intent, and a tone/angle informed by sentiment.

Cost & cadence

  • SERP live/advanced bills $0.002/request (cost-log). Run a few queries per topic (main keyword + a couple of variants).
  • Labs ideation bills about 0.0105; search_intent about $0.0011 (cost-log).
  • Content Analysis is Live-only and pricier per call: the cost-log shows search at 0.02003; budget accordingly and cache results.
  • Cadence: per content brief (on demand). Refresh the SERP scrape near publish time since live SERPs move.

Output

A writer-ready content brief: target keyword and weighted subtopics, the questions to answer, SERP features to target, competitor depth/format benchmark, intent classification, and a sentiment-informed angle. Feeds the editorial pipeline and complements play-keyword-research-workflow.

Pitfalls / limits

  • Use Live SERP here (not Labs) because the brief must reflect the current competitive page set; Live results are not stored, so capture them when received.
  • Keyword special operators in the SERP query trigger a 5x charge; keep the topic query clean.
  • Content Analysis is the costliest step per call; scope it with page_type, filters (max 8), and limit instead of pulling the full corpus.
  • Labs intent is Google-specific and language-only; do not pass a location to it.
  • Content Analysis runs over a citation database, not a live crawl, so very fresh content may be under-represented.

Decisions in play

  • dec-labs-vs-live-apis: use Live SERP for the competitive page set (must be current) but Labs for the cheaper subtopic/demand expansion.
  • dec-which-api-for-which-job: SERP for the competitive surface, Labs for demand/intent, Content Analysis for discourse sentiment.
  • dec-cost-control-strategy: Content Analysis is the costliest step per call, so scope it with page_type, filters, and limit rather than pulling the full corpus.

Sources

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