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Frase

Frase generates blogs backed by topic research and outlines.

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Frase Features & Overview

Frase uses LLMs for generation, NLP for entity extraction, and a live SERP parser to convert a keyword into a working outline. You run a Content Report, pull competitors, entities, and questions, then build a structured brief with headings and coverage targets. The Content Editor tracks a Topic Score as you write, so gaps show up early. Rank-Ready AI Documents create full articles on demand, priced per document, which lets you scale without extra seats. SEO Analytics connects to Google Search Console, uncovers growth and decay, and flags quick wins. Content Opportunities alerts you when a page slips or a query opens up. Brand Voice and preferred Terms keep tone consistent. Reference Docs ground generation in product facts, policies, and FAQs. WordPress, Google Docs, and a Chrome extension bring the same guidance into tools your team already uses.

Core Features

  • Content Reports and Briefs: Pull competitors, entities, and questions, then build a brief in minutes
  • Content Editor with Topic Score: Real-time coverage guidance, length targets, and optimization cues
  • Rank-Ready AI Documents: Generate full drafts, pay per document, bundle credits for scale
  • SEO Analytics with GSC: Sync Search Console, track performance by query and page
  • Content Opportunities: Get alerts for pages that need attention and keywords worth pursuing
  • Brand Voice and Terms: Save voice profiles, lock approved terminology
  • Reference Documents: Ground the model with your internal docs for accurate drafts
  • Multi-query Projects: Combine up to five queries for stronger topical coverage

Supported Platforms / Integrations

  • WordPress plugin for optimization and scoring in the editor
  • Google Docs add-on for real-time research and editing in Docs
  • Chrome extension for in-browser drafting and optimization
  • Google Search Console integration for analytics and monitoring
  • API add-on for programmatic access to scraping and NLP endpoints
  • Frase Answers chatbot powered by your content

Use Cases & Applications

  • Agencies: Standardize AI-backed briefs, draft faster, triage refreshes from Content Opportunities
  • In-house SEO and content: Build topic coverage from entities and questions, grade drafts before approval, defend rankings with GSC data
  • Publishers and affiliates: Produce long-form at scale with Rank-Ready AI Documents, track movement, tune pages on a schedule

Pricing

  • Starter: $45 per month, 1 user, 15 Content Projects, 1 Brand Voice, 3 Reference Docs, 30 preferred Terms, SEO Analytics for 1 domain, Content Opportunities for 50 pages, Rank-Ready AI Documents from $2 per doc in bundles
  • Professional: $115 per month, 3 users included, 75 Content Projects, 5 Brand Voices, 15 Reference Docs, 100 preferred Terms, unlimited domains for SEO Analytics, 200 pages in Content Opportunities, priority support, API add-on available, extra seats $25 per month
  • Enterprise: custom terms with volume pricing, governance, multi-account integrations, advanced security

Why You’d Love It

  • Research, briefs, drafting, and optimization sit on one repeatable track
  • Topic Score, Brand Voice, and Terms align writers without long review cycles
  • GSC analytics and alerts keep wins healthy and put refresh work on time

Pros & Cons

Pros

  • Clear jump from SERP data to brief to graded draft
  • Rank-Ready AI Documents speed long-form production
  • GSC-driven analytics and Content Opportunities for upkeep
  • WordPress, Docs, and Chrome integrations that meet teams where they write

Cons

  • Project quotas on lower tiers cap very high monthly output
  • Pay-per-doc model adds variable cost at scale

Conclusion Frase gives SEO and content teams an AI-first system for planning, drafting, and ongoing care. You turn live SERP signals into briefs, write against a measurable Topic Score, publish faster with Rank-Ready AI Documents, and protect performance with GSC analytics and timely alerts. Output rises, edits shrink, and refresh work follows real search data.

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