RankinLLM QuickStart Guide

RankinLLM helps you understand how your brand shows up inside AI answers (ChatGPT, Claude, Gemini, Perplexity, etc.) and what to do to improve it. This guide walks you step-by-step through your first setup and first insights.

Step 0: Create Your Organization (1 minute)

• Click Get Started (New Organization)
• This is your workspace where all brands, prompts, and reports live

Think of this like creating a Google Analytics account — once done, everything else plugs into it.

Step 1: Add Your Website (2 minutes)

1. Enter your website URL (Example: https://yourdomain.com)
2. Select your primary country
3. (Optional) Enable auto-join for teammates using the same email domain
4. Click Continue

RankinLLM now knows which brand it is tracking.

Step 2: Define Your Brand Profile (2 minutes)

Here you teach RankinLLM who you are, so AI models interpret your brand correctly.

This context is used across all AI model evaluations.

Step 3: Add Your Competitors (2 minutes)

• Add 3–5 competitors you want to track against
• RankinLLM compares who AI recommends instead of you

This unlocks Share of Voice, replacement risk, and comparison prompts.

Step 4: Add Base Prompts (3 minutes)

Base prompts are seed questions people ask AI tools. RankinLLM automatically expands them into multiple variations, runs them across AI models, and tracks brand mentions and sentiment.

Tip: Start with non-branded, buyer-intent prompts.

Step 5: Choose AI Models & Schedule (1 minute)

Select which AI models you want to track (ChatGPT, Claude, Gemini, Copilot, Grok, Perplexity) and choose your review schedule (Daily or Weekly).

RankinLLM will now continuously monitor your AI visibility.

Step 6: Run Your First Analysis (Automatic)

Once setup is complete, RankinLLM runs your prompts across models, captures AI responses, and detects brand mentions, competitors, and sentiment.

Step 7: Understand Your Dashboard

1. Run History

See how often RankinLLM has tested AI responses, track progress over time, and compare visibility week-by-week.

2. Responses Table

This shows exact AI answers. For each prompt, you see which model answered, brand mentions, competitor mentions, sentiment, and full response text. This is your ground truth.

3. Attribute Heatmap (Visibility Intelligence)

Shows what AI associates your brand with (e.g., User experience, Affordability, Trust). Green = Strong association, Red = Weak. This tells you what content AI needs next.

Share of Voice Trend

Brand Mentions Trend

Sentiment Score Trend

Top Citation Sources & Competitor Analysis

Step 8: Use AI Content Optimization Tools (Power Features)

These tools convert insights into action.

LLMs.txt Generator

Creates AI-friendly content maps to help AI models crawl your site better.

FAQ Generator

Generates AI-optimized FAQs based on real AI search behavior.

Content Optimizer

Improves existing pages by suggesting AI-visibility improvements.

Schema Generator

Improves structured data (JSON-LD) to make your content easier for AI to interpret.

Step 9: Analyze Server Logs

• Upload server logs
• Detect AI bot visits
• Understand crawl behavior from AI systems

Step 10: Understand Where AI Is Getting Its Information From (Top Citation Sources)

This shows which websites AI models trust most when answering questions in your category.

How to read this: Higher bars = AI relies on that source more. If your own website is missing or low, AI is telling your story through others.

Why this matters: AI recommendations are citation-driven, not opinion-driven. Move from "AI talks about us via others" → "AI cites us directly".

Step 11: Competitor Analysis (Who AI Prefers Today)

For each competitor, RankinLLM shows: % of AI mentions, Sentiment (Positive/Neutral/Negative).

How to interpret this: These are AI preference scores, not Google rankings. A higher % means AI recommends them more often.

Insight: If competitors are ahead, it's usually because of broader content coverage, stronger citation networks, and better structured information. This is not about ads or backlinks, it's about AI trust.

Step 12: Your Core AI Visibility Metrics (The 4 Numbers That Matter)

Step 13: Trends

RankinLLM shows trends over time so you don't rely on one snapshot.

• Sentiment Trend: Lines typically represent Positive, Neutral, Negative mentions. If neutral is rising but positive is flat → AI knows you exist but doesn't endorse you yet.
• Brand Mentions Trend: Falling line = losing mindshare. Flat line = stagnant. Rising line = expanding coverage. This tells you if your content updates are working.
• Share of Voice Trend: This is the single most important chart. If this is flat or declining → competitors are becoming more authoritative, even if your content is improving.

Step 14: Content Optimizer (Turn Insights Into Fixes)

This is where RankinLLM becomes actionable.

Output: What AI expects but doesn't find, What competitors explain better, What sections to add or restructure.

This is AI-first optimization, not SEO keyword stuffing.

Step 15: LLMs.txt Generator (Teach AI How to Read Your Site)

This creates a standardized file that explains your site structure to AI systems, highlights important docs, FAQs, pricing, APIs, and improves direct citations.

• Summary of your site
• Docs/blog links
• FAQs
• Pricing routes
• Contact info
• Citation instructions

Why this matters: AI models don't crawl like Google. This file acts as "Here's how to understand and trust our website."

Step 16: Full Report (Executive-Level Intelligence)

This is a ready-to-share strategy report, not raw data.

Example insights: Over-reliance on Wikipedia/third-party blogs, Weak direct citations from your own domain, Competitors winning decision-level queries, High visibility but low authority conversion.

This report is boardroom ready.