Tracking MRR is great, but are you tracking your "Citability Score"?
We all know the standard indie hacker metrics: MRR, Churn Rate, CAC, and Daily Active Users. But as user behavior shifts radically from "Searching on Google" to "Asking an AI Assistant," there is a massive blind spot in how we measure acquisition.
If a potential customer asks Perplexity or Claude, "What is the best tool for [Your Niche]?" — do you know where you rank? Do you even show up?
I've spent the last few months deeply analyzing how LLMs retrieve and cite SaaS products, and I realized we need a new metric for the Generative AI era. I call it the Citability Score.
What makes up a Citability Score? It's not about backlinks anymore. To an LLM, your authority is based on:
Brand Entity Recognition: Does the AI associate your brand name with the correct category of software? (e.g., CitableHub = AI Visibility).
Feature Mapping Accuracy: When the AI describes your tool, does it hallucinate features, or does it accurately pull from your latest documentation?
Contextual Retrieval: How likely is the AI engine to pull your product into its active context window when a user asks a high-intent question?
Sentiment Indexing: Is the training data surrounding your product generally positive across the web?
Why you need to measure this today: If your Citability Score is low, you are essentially invisible to the next generation of internet users. Traditional SEO tools can't measure this because they track keyword volume, not semantic entity recognition.
I built the dashboard at CitableHub specifically to track this. When you plug your SaaS into our discovery engine, we calculate your current Citability Score and give you a Generative Engine Optimization (GEO) audit to show you exactly where the AI is getting confused about your product.
As founders, we can't afford to be invisible to AI. I'm opening up the dashboard for free testing today. How do you currently track if AI assistants are recommending your tool? Let's discuss below.
