Visibility Analytics: Track Your AI Brand Presence

Monitor your brand mention rate, share of voice, and average position across 17 AI platforms—including coding agents, answer engines, and frontier models.

Visibility Analytics is the core monitoring dashboard in Lightsage. It runs your defined prompts across 17 AI platforms on a daily or alternate-day schedule and aggregates the results into a single view: how often AI mentions your brand, where you rank relative to competitors, and which prompts are driving or losing visibility.

What Visibility Analytics tracks

Every run captures three top-level metrics across all active platforms:

• Visibility Score — a composite rate measuring how frequently your brand appears in AI-generated responses for your tracked prompts
• Share of Voice — your mention count as a percentage of all brand mentions (yours plus competitors) for the same prompt set
• Average Position — where your brand appears in a response, averaged across all platforms that mentioned you

These roll up into a single dashboard so you can spot trends without switching between platforms.

The two types of AI platforms

Lightsage tracks 17 platforms split across two categories. Understanding the difference matters because they drive different business outcomes.

Answer engines (7)

ChatGPT, Google AI Overviews, Google AI Mode, Gemini Search, Perplexity, Claude, Microsoft Copilot

These platforms answer questions in prose. Visibility here drives brand awareness — developers learning your name before they start building.

Coding agents (10)

Claude Code, OpenAI Codex, Cursor, GitHub Copilot, Gemini CLI, OpenClaw, OpenCode, Hermes, Pi, Kilo

These platforms write and execute code. Visibility here drives adoption — agents recommending and implementing your API directly in a developer's project.

Setting up prompt tracking

Prompts are the queries Lightsage sends to each AI platform to check whether your brand is mentioned. The quality of your prompts directly determines the quality of your data.

The four prompt types

Brand queries Prompts about your company or product by name.

Examples:

• "What is Acme API?"
• "How does Acme API work?"
• "Is Acme API reliable?"

Purpose: Establish a baseline mention rate. If you score low on brand queries, the AI platforms either don't know about you or have outdated information.

Category queries Prompts about the broader category you compete in.

Examples:

• "Best payment API for startups"
• "Top authentication libraries for Next.js"
• "Open source vector database options"

Purpose: Measure share of voice against competitors. These prompts reveal whether AI systems recommend you when a developer is evaluating options.

Comparison queries Head-to-head prompts comparing you with specific competitors.

Examples:

• "Acme API vs Stripe — which should I choose?"
• "Auth0 or Acme Auth for a SaaS app?"

Purpose: Detect where you're winning and losing direct comparisons. Answer engines frequently surface comparison content verbatim, so these prompts also tell you whether your comparison pages are being read.

Implementation queries Prompts about how to build something using your product. These matter most for coding agents.

Examples:

• "Add Acme payments to my Next.js app"
• "Integrate Acme Auth with Express"
• "Fix Acme API 401 error"

Purpose: Test whether coding agents recommend you when a developer is actively building. A high mention rate here correlates directly with real usage.

Adding prompts

1. Go to Visibility Analytics Open the Visibility Analytics section in your Lightsage dashboard and select Manage Prompts.

2. Add brand queries first Start with 3–5 direct brand queries. These establish your baseline and are the fastest to set up.

3. Add category and comparison queries Add 5–10 category queries covering your main use cases. Then add at least one comparison query per major competitor.

4. Add implementation queries for coding agents Add 3–5 implementation prompts — one per top use case. Phrase these as a developer would actually type them into a coding agent.

5. Select platforms and schedule Choose which platforms to run each prompt on. Answer engine prompts cost 1 credit per run; coding agent prompts cost 5 credits per run. Set the frequency to daily for high-priority prompts or alternate days for lower-priority ones.

Understanding the Visibility Score

Your Visibility Score is a number from 0 to 100 that represents your weighted brand mention rate across all tracked platforms and prompts.

The score accounts for:

• Mention presence — whether your brand appears at all in a response
• Position — responses where you're mentioned first score higher than ones where you're buried at the end
• Platform weight — coding agent mentions weight more heavily than answer engine mentions for developer tool companies
• Prompt relevance — implementation and comparison prompts weight more than brand queries

A score of 60 doesn't mean you're mentioned in 60% of responses. It's a composite index. Use it to track direction over time rather than interpret as an absolute percentage.

Share of Voice explained

Share of Voice (SoV) measures what percentage of total brand mentions in a prompt set belong to you versus your tracked competitors.

Formula: Your mentions ÷ (your mentions + all competitor mentions) × 100

If Claude Code mentions your API 4 times and your two competitors 6 times combined across 10 category prompts, your Share of Voice is 40%.

Reading SoV over time

The SoV trend line is more valuable than the current number. Look for:

• Rising SoV: Your improvements are working. Continue the current strategy.
• Flat SoV with rising Visibility Score: Both you and competitors are growing together. You're not losing ground, but you're not winning either.
• Falling SoV: A competitor is improving faster than you. Open the competitor breakdown to see which prompts they're winning.

Prompt run frequency

Daily runs give you the tightest feedback loop when you're actively making changes. Alternate-day runs are more credit-efficient for stable prompts where you've already established a baseline.

Metrics reference

Tips for choosing effective prompts

Match real developer intent Write prompts the way a developer would actually type them — not how you'd describe your product in marketing copy. "Best auth API" outperforms "What authentication solutions are available?"

Cover multiple frameworks Add implementation queries for each major framework your users work in: Next.js, Express, FastAPI, Rails. Agent recommendations are framework-specific.

Include your competitor names Comparison queries like "[Your API] vs [Competitor]" produce some of the most actionable data. They directly reveal whether AI systems recommend you in head-to-head comparisons.

Avoid overly broad queries "Best API" produces noisy results across too many categories. "Best payment API for SaaS" or "Best auth API for Node.js apps" gives you targeted data on prompts you can actually win.

Reading and acting on results

After each run, the Visibility Analytics dashboard shows a breakdown by prompt, platform, and time period. Use this workflow to turn data into action:

1. Check the trend line first. Is your Visibility Score up, down, or flat over the past 30 days?
2. Look at Share of Voice by prompt type. Are you losing on category queries, comparison queries, or implementation queries?
3. Identify which platforms are dragging you down. Low scores on coding agents but high on answer engines suggests a discoverability problem (robots.txt, llms.txt). Low scores everywhere suggests a content problem.
4. Open the Opportunities Engine. Lightsage automatically surfaces prioritized fixes based on your Visibility Analytics data.