Explore how Search Atlas helps you generate, evaluate, and structure AI-powered content using real SEO intelligence. This section breaks down Topical Maps, Semantic Scoring, SCHOLAR, and key performance dashboards.
What is Deep Freeze, and how do I use it?
What is Deep Freeze, and how do I use it?
Deep Freeze is a feature that allows you to pause an OTTO project without losing your deployed SEO fixes. It’s ideal for situations where you need to pause billing but want to preserve your gains.
🧊 What Deep Freeze does:
Captures the current state of your live OTTO fixes
Stops the OTTO pixel from loading (no active script needed)
Keeps all deployed SEO content visible to Google and users
Prevents new edits until the site is “unfrozen”
🧩 When to use Deep Freeze:
A client cancels or pauses the service
You’re migrating to a new platform
You want to retain SEO wins without ongoing edits
You’re archiving a site but want public content intact
⚙️ How to activate it:
Go to Project Settings of the OTTO site
Click “Deep Freeze Site”
Confirm the action
You’ll see a countdown showing when your next freeze credit is available
📋 Rules & Limits:
You can freeze one site every 14 days
Available for Growth, Pro, and Legacy accounts
Once frozen:
No new AI fixes can be deployed
Pixel is no longer required or counted toward your quota
Unfreezing restores edit access
Note: Deep Freeze lets you preserve OTTO SEO changes without keeping the pixel active or continuing edits. Ideal for paused clients, migrations, or cancelation archiving.
How do I build entity authority using Quest?
How do I build entity authority using Quest?
The SEO paradigm is shifting to AEO (Answer Engine Optimization) with LLMs generating billions of pieces of content. QUEST enables LLM visibility benchmarking, helping you optimize for AI-generated content ecosystems.:
If your content isn’t indexed in GPT, you won’t appear in AI-generated answers.
Influence what ChatGPT, Claude, and others say—at the source level.
Use QUEST to:
Find out whether your domain, brand, or topics are visible in models like GPT.
Identify source documents that inform LLM-generated answers.
Launch targeted digital PR campaigns to modify those sources and increase brand mentions.
🛠️ How to do it
Go to Search Atlas and navigate to Content → QUEST.
Enter a topic, brand, or keyword (e.g., “best cat treats”, “plant-based protein powder”).
QUEST will:
Run your query across LLMs.
Extract the full AI answer.
Identify the source URLs informing that answer.
Review the list of source documents.
Click “Create Campaign” to:
Find contact info for authors, editors, or contributors.
Launch email or SMS outreach sequences.
Use prebuilt templates or custom messages.
Interpretation Tips
Focus on recurring sources: If multiple LLM answers cite the exact domains, prioritize them.
Look for brand mentions vs. non-brand documents: Not all citations include your brand; identify relevant editorial angles.
Target contributors: QUEST helps you find not just site editors, but also guest authors with a wide presence.
QUEST is deeply integrated with the Publisher Exchange and Digital PR tools in Search Atlas. You can cross-filter sites by:
LLM visibility
Inclusion in Google News
Indexation via Bing, Common Crawl, and others
Use this to prioritize outreach where AI already shows semantic trust.
What is a Topical Map, and why is it important for SEO?
What is a Topical Map, and why is it important for SEO?
A Topical Map is a content blueprint that helps you cover a subject in-depth and rank better in search engines.
🧠 Why it matters:
Organizes content into thematic clusters
Highlights keyword gaps and under-covered topics
Helps auto-generate SEO articles for full topical coverage
Strengthens internal linking between related pages
🔍 Search Atlas builds Topical Maps using KBT (Knowledge-Based Topics) — combining Google Search Console data with NLP to surface high-impact topics.
What’s the best way to optimize internal linking automatically?
What’s the best way to optimize internal linking automatically?
You can automate smart, SEO-friendly internal linking directly through OTTO.
🧠 How it works:
Go to the OTTO > Internal Linking tab
OTTO suggests semantic anchor text based on page context
Links are created from high-authority to underperforming pages
Uses the OTTO Pixel to auto-insert links without changing your CMS
🛠️ Deploy links:
Per page, by section
Or bulk deploy across your site
What is Semantic Score, and how is it calculated?
What is Semantic Score, and how is it calculated?
The Semantic Score is a proprietary metric used in Search Atlas to evaluate how well your content aligns with Google’s expectations for topical depth and semantic relevance.
📊 What goes into the score:
✅ Topical Map Coverage → Checks if your content addresses key subtopics in the topical cluster
🧩 Entity Co-occurrence → Looks for the presence of related entities commonly found in high-ranking pages
🗝️ Keyword Spread & Variation → Measures how naturally and comprehensively your content uses primary and secondary keywords
📐 Structure & Readability → Analyzes headers, paragraph flow, and formatting for user and crawler experience
⚙️ When it updates:
Every time you generate a new AI draft
When you apply a content fix or manually edit the article
After internal linking or entity suggestions are added
What’s the difference between Topical Maps and Keyword Gap tools?
What’s the difference between Topical Maps and Keyword Gap tools?
While both tools help you plan smarter content, Topical Maps and Keyword Gaps serve very different SEO goals:
📚 Topical Maps = Content Depth + Entity Coverage
Built using NLP + GSC + KBT (Knowledge-Based Topics)
Designed to structure your content around entities and semantic relevance
Automatically suggests articles, internal links, and supporting content
Goal: Improve topical authority, not just keyword count
🧩 Keyword Gap Tool = Competitive Benchmarking
Compares your domain to top-ranking competitors
Shows keywords they rank for, but you don’t
Helps you identify opportunities to close ranking gaps
Goal: Win SERP visibility by covering missed intents
🔍 Use both together:
Run Keyword Gap to see what content you're missing
Use Topical Maps to structure that content semantically
Deploy articles and links via OTTO for max impact
🛠️ Where to find:
Topical Maps → AI Content > Topic Clusters
Keyword Gap → Keywords > Gap Analysis
What is SCHOLAR, and how does it score AI content?
What is SCHOLAR, and how does it score AI content?
SCHOLAR (Semantic Content Heuristics for Objective Language Assessment & Readability) is the NLP scoring engine behind all AI-generated content in Search Atlas.
It evaluates not just keywords, but how well your content performs semantically in context, using Google’s language patterns, entity graphs, and readability metrics.
🧠 What SCHOLAR measures:
Topical Coverage
Check alignment with your Topical Map or target entity
Rewards articles that address core + supporting topics
Entity Co-occurrence
Verifies that the right-named entities (e.g., brands, locations, tools) appear naturally
Inspired by Google’s Knowledge Graph standards
Keyword Spread + Synonym Use
Look for semantic variation, not just keyword repetition
Penalizes keyword stuffing or unnatural phrasing
Readability + Structure
Evaluates sentence complexity, header hierarchy, and paragraph length
Optimized for UX, conversion, and Google’s Helpful Content System
Anchor Distribution (for internal links)
Assess whether the anchor text is relevant, varied, and semantically justified
Used when articles are generated with internal linking enabled
📈 What your score means:
90–100 (Excellent): Ready to publish, highly optimized
70–89 (Good): Minor improvements suggested
50–69 (Needs Work): Improve structure or keyword depth
Below 50: Rewrite or regenerate — lacks semantic alignment
🔧 Where to find SCHOLAR Scores:
In Content Genius > Drafts
Also visible in Report Builder and article exports
Automatically updated after each generation or edit
What is the SCHOLAR Engine, and how does it optimize my content?
What is the SCHOLAR Engine, and how does it optimize my content?
The SCHOLAR Engine is Search Atlas’s proprietary AI model that scores your content the same way search engines evaluate relevance and authority.
It powers the Semantic Score, giving you real-time insight into how well your content meets SEO expectations, based on structure, meaning, and topical alignment.
🧪 How it works:
SCHOLAR analyzes each draft using advanced Natural Language Processing (NLP), entity extraction, and competitive SERP benchmarks. It checks for:
📚 Topical Coverage
Detects whether your content addresses all relevant subtopics, themes, and search intents based on your Topical Map.
🧠 Entity Density
Scores mention of related brands, people, places, and industry-specific terms (based on Google's Knowledge Graph).
📐 Semantic Structure
Assess title tags, H1–H3 hierarchy, internal links, and paragraph length for SEO readability.
🔁 Keyword Spread
Checks if your draft includes LSI terms, synonyms, and modifiers — not just the main keyword repeated.
🧷 UX Signals
Evaluates layout logic, transitions, and call-to-action placement to align with SEO and engagement best practices.
⚙️ Where SCHOLAR is used:
✍️ Content Genius (AI article drafts)
🗺️ Topical Maps (final score on mapped articles)
🧩 Live Editor (post-generation refinements)
🔍 Semantic Score Panel (real-time updates per change)
📈 How to improve your Semantic Score:
🧭 Start with a Topical Map to guide your structure
📝 Add supporting paragraphs under each H2
🔗 Include relevant internal links (OTTO recommends them!)
🗣️ Use natural language with real-world brand/entity mentions
📊 Insert FAQs, lists, or comparison tables to increase depth
What is KBT, and how does it power AI and Topical Maps?
What is KBT, and how does it power AI and Topical Maps?
🧠 What is KBT?
KBT (Knowledge-Based Topics) is the core semantic engine behind Search Atlas. It analyzes your site, industry, and keyword universe to generate topic clusters based on Google’s understanding of entities, not just raw keywords.
KBT draws from:
🧠 Your connected GSC account (top pages + queries)
📚 Competitor content and search rankings
📈 NLP-based clustering and entity detection
🗂️ Search Atlas's proprietary topic models across industries
🤖 How it powers the platform:
Topical Maps: KBT powers your auto-generated content hierarchy
Content Genius: Suggests headings, outlines, and semantic improvements
Semantic Score: Evaluates your content’s alignment with KBT structure
Internal Linking: Builds clusters around knowledge themes
🔁 Continuous Learning
KBT improves as you:
Connect more data sources (GSC, GBP)
Publish and deploy OTTO changes
Expand topic maps and content drafts
How does the AI Content Planner work with Topical Maps and Bulk Article Generation?
How does the AI Content Planner work with Topical Maps and Bulk Article Generation?
The AI Content Planner in Search Atlas connects your topical strategy with efficient, high-quality content production, including bulk article generation for entire silos or clusters.
📌 Planner + Topical Maps Workflow:
Create or import a Topical Map
Based on keyword themes, entities, or GSC data
Organized by clusters and subtopics
Open AI Content Planner
Automatically displays all articles suggested by the map
You can edit titles, assign writers, or generate with AI
Select generation mode:
🧠 One-click: AI writes a full draft with headings, FAQs, and internal links
📦 Bulk mode: Generate 5–100 articles in a single queue
💬 Human-AI hybrid: Assign drafts to team members for manual writing
Track status and SCHOLAR scores
Monitor progress from “Planned” → “Generated” → “Published”
Optimize low-performing drafts based on NLP feedback
⚙️ Optional automations:
Auto-insert internal links using OTTO’s pixel
Push content to WordPress or Webflow
Add metadata, schema, and OG tags automatically
📈 Ideal for:
Agencies needing full-topic coverage
Niche sites scaling content by 100s of pages
In-house teams working with AI + editors
What’s the difference between Content Genius and Bulk Writer?
What’s the difference between Content Genius and Bulk Writer?
⚖️ Key Differences at a Glance:
Feature | Content Genius | Bulk Writer |
🧠 Purpose | Manual, single-article generation | Mass content generation at scale |
🎯 Control Level | High (edit structure, tone, schema) | Medium (structure guided by prompts) |
🗺️ Topical Map Integration | Yes | Optional (can import map topics) |
⚙️ AI Credits Used | 1–20 credits per task | 1 credit per article |
📤 Output Volume | 1 article at a time | Up to 100 articles in batch |
📝 Ideal For | Agencies, editors, experts | Affiliate sites, multi-location pages, eCommerce |
What is the SEO Metrics Dashboard, and how should I use it?
What is the SEO Metrics Dashboard, and how should I use it?
The SEO Metrics Dashboard in Search Atlas provides a real-time overview of your entire project’s SEO performance across content, technical health, backlinks, local optimization, and AI activity.
📌 What’s included:
Traffic + Visibility
Sessions, impressions, CTR, and GSC keyword growth
Weekly and monthly change deltas
Integrated with GSC (optional)
Content Performance
Number of AI articles deployed
Topical Map coverage percentage
SCHOLAR Score average
Fix Deployment Log
OTTO SEO fix history
Status: pending, deployed, failed
Click to view the page or redeploy
Authority Building
CloudStack links created
Press releases published
Referring to domain growth (tracked weekly)
Local SEO
GBP post count
Review replies and Q&As published
Local visibility score (from heatmaps)
🎯 How to use it:
Set project baselines and KPIs
Spot underperforming areas (e.g., content not indexed, links not active)
Share snapshots with clients via Report Builder
Combine with automations to maintain SEO momentum
🛠️ Where to find it:
Go to any Project > Dashboard tab (visible on Growth, Pro, and Enterprise plans)
How does the AI use GSC data to improve keyword performance?
How does the AI use GSC data to improve keyword performance?
Connecting GSC to Search Atlas allows the platform to access your top-performing pages, queries, and click-through trends directly from Google, turning your actual performance data into optimization insights.
This enables AI tools like Topical Maps, Content Genius, and OTTO to work with your real search footprint, not just assumptions.
🤖 What does the AI do with GSC data?
Once connected, Search Atlas can:
🗺️ Generate Topical Maps
Uses your most-searched pages to auto-cluster related keywords into a silo structure.
📉 Detect Keyword Gaps
Finds high-impression, low-click keywords that your content doesn’t yet target.
✍️ Prioritize Drafting
Suggests article creation or optimization based on missed opportunity terms.
📈 Track Click/Impression Trends
Highlights downward or upward movements in keyword performance, and auto-suggests AI actions.
⚙️ Where it’s used:
Topical Maps creation
AI Suggestions panel inside Content Genius
OTTO Optimization Recommendations
Coming soon: GSC + Semantic Score Overlay
🔐 Security Note:
Your GSC data is read-only, used solely for content optimization, and never modified or shared.
What’s the fastest way to create a high-performing landing page with AI?
What’s the fastest way to create a high-performing landing page with AI?
You can build a fully optimized landing page in minutes using Hyperdrive’s AI builder.
🛠️ Steps to create:
Go to Hyperdrive > New Page
Enter your topic or product focus
Let AI generate:
SEO-optimized layout (H1, subheaders, keywords)
Conversion-ready copy (hero, features, CTA)
(Optional) Add AI-generated images for a full visual page
⏱️ Estimated time:
Text only: ~1 minute
With images: ~5–7 minutes
With AI content generation aligned to real SEO metrics, you’re equipped to create smarter, more strategic content. Revisit this section as you refine your topical strategy or optimize content performance.