How the Citation Engine Works: Finding & Seeding High-Authority Threads

MentionLayer's discovery engine runs a multi-step pipeline to find the highest-value threads for your brand.

Step 1: SERP Scanning — For each of your keywords, MentionLayer searches Google for Reddit, Quora, and Facebook Group results. It looks for queries like "site:reddit.com best music licensing" and captures the top 20 results per keyword. Threads ranking high on Google are the ones AI models are most likely to reference.

Step 2: AI Probing — MentionLayer asks Perplexity and ChatGPT buying-intent questions about your keywords and collects the source URLs they cite. These are threads that AI models already reference — the highest-value targets for citation seeding.

Step 3: Deduplication — Content hashing ensures the same thread never appears twice in your queue, even if discovered through multiple keywords or scans.

Step 4: Thread Enrichment — Full thread content gets pulled: the original post, top 15 comments (2 levels deep), upvote counts, comment counts, and post dates. This context is essential for generating relevant responses.

Step 5: AI Classification — Claude Sonnet analyzes each thread against your brand brief to determine intent (informational, transactional, commercial), relevance score, whether your brand can be naturally mentioned, and a suggested response angle.

Step 6: Opportunity Scoring — A composite score (0-100) ranks threads by their potential value. Threads scoring 70+ auto-advance to your queue. Threads scoring 40-69 stay for manual review. Below 40 get auto-skipped.

The thread queue is where you spend most of your time in MentionLayer. It's a filterable, sortable table of all discovered threads for your selected client.

Key columns: - Platform — Reddit, Quora, or Facebook Groups (color-coded badges) - Community — The specific subreddit, Quora topic, or Facebook Group - Title — The thread title (click to open on the source platform) - Keyword — Which of your keywords matched this thread - SERP Position — Where this thread ranks on Google (lower = better) - Intent — Informational, transactional, commercial, or navigational - Relevance — How closely this thread matches your brand (0-100 bar) - Comments — Thread engagement level - Date — When the thread was posted - Status — New, classified, queued, responded, posted, or skipped

Filters: Narrow your view by platform, intent type, relevance range, status, date range, or search by title text. The default view shows "queued" threads sorted by opportunity score (highest first).

Pro tip: Focus on threads with opportunity scores above 70 first. These are the ones where a well-placed response has the highest chance of being seen by both humans and AI crawlers.

Click "Generate" on any thread to create three response variants using Claude Opus. Each variant is crafted to sound like a genuine community member — not a marketer.

Casual Helper — Short, punchy, conversational. Mentions the brand as "I've been using X" or "a friend put me onto X." Feels like a quick helpful reply between meetings. Best for high-traffic Reddit threads where brevity wins.

Expert Authority — Leads with substantial advice that would be helpful even without the brand mention. Positions the brand as one option among several. Structured, thorough, credible. Typically the highest quality score. Best for Quora and in-depth Reddit threads.

Story-Based — Opens with "I was in the exact same boat as you..." and shares a personal experience where the brand mention feels incidental. Emotionally engaging. Best for threads where the OP is asking for personal recommendations.

What makes these responses different from AI slop: - Never starts with "Great question!" or generic openers - References specific details from the thread (OP's situation, other comments) - Provides genuine value before any brand mention - Matches platform culture (Reddit casual, Quora formal) - Occasionally mentions competitors positively (credibility through balance) - Uses imperfect formatting on Reddit (markdown, "edit: typo" style)

Each response includes a quality score (0-100), tone match score, and indicators for whether it mentions the brand name or URL.

MentionLayer generates responses but never auto-posts them. You copy and paste manually. This is intentional — human review ensures quality and lets you adapt to the thread's current state.

Before posting: 1. Read the thread — Click the thread link to open it on the source platform. Check if new comments have been added since enrichment. 2. Pick the right variant — Match the variant to the thread's tone. Casual threads don't need expert-length answers. Emotional threads deserve stories. 3. Edit if needed — Click "Edit" to modify before copying. Adjust references, add personal touches, or tweak the brand mention placement. 4. Check timing — For threads older than 30 days, the response automatically includes a "late to this thread but..." opener. For very old threads, consider whether posting is still valuable.

After posting: 1. Mark as Posted — Click "Mark as Posted" in MentionLayer to track your placement rate. 2. Monitor the thread — Check back after 24-48 hours. Upvotes and replies indicate the response landed well. 3. Track in AI Monitor — Set up monitoring prompts to see if your seeded citations start showing up in AI model responses.

Account management tips: - Use established Reddit/Quora accounts with karma and post history - Don't post responses to multiple threads in the same subreddit within minutes - Vary your language patterns — don't post all three variants across different threads - Engage naturally: upvote other helpful comments, reply to follow-ups