Track How Often ChatGPT and Perplexity Cite Your Brand

Your brand lives in two places now. The old one is Google, where rank tracking has been the standard for 20 years. The new one is ChatGPT, Perplexity, and Claude, where a buyer asks "what is the best [your category] tool?" and the answer that comes back is either your brand or a competitor. In 2026, 31% of US internet users run at least one query per day on an answer engine, and that share is climbing.

Most marketing teams are flying blind on the second one. Here is a tactical approach to tracking how often AI models cite your brand that you can ship in a day.

Step 1: Define the Prompts That Matter

Start with the 10-20 prompts a buyer in your category would naturally ask. These are not your marketing keywords, they are conversational:

• "What is the best SERP API in 2026?"
• "Top alternatives to SerpAPI"
• "Cheapest Google search API for startups"
• "What search API works best with LangGraph?"

Step 2: Query the Answer Engines Daily

Scavio's /ask endpoint lets you query ChatGPT, Perplexity, and Claude programmatically. Here is a Python script that runs the daily tracker:

import os, re, requests

API_KEY = os.environ['SCAVIO_API_KEY']
PROMPTS = ['best SERP API 2026', 'top SerpAPI alternatives']
BRANDS = ['Scavio', 'SerpAPI', 'Serper', 'Tavily', 'Brave']

def ask(engine, prompt):
    r = requests.post('https://api.scavio.dev/api/v1/ask',
        headers={'x-api-key': API_KEY},
        json={'platform': engine, 'prompt': prompt})
    return r.json().get('answer', '')

for engine in ['chatgpt', 'perplexity']:
    for prompt in PROMPTS:
        answer = ask(engine, prompt)
        mentions = {b: len(re.findall(rf'\b{b}\b', answer, re.I)) for b in BRANDS}
        print(engine, prompt, mentions)

Step 3: Log and Visualize

Pipe the output into Postgres, SQLite, or a Google Sheet. Chart the mention count per brand over time. Two weeks in, the trend lines tell you whether you are gaining or losing share of AI recommendations.

Step 4: Act on the Data

The whole point of tracking is to change the outcome. When a competitor is cited more often than you, the fix is usually:

• Source audit: find which sources Perplexity cites, and pitch them content or fixes.
• Comparison content: write "X vs Y" pages that rank on Google and get ingested by answer engines.
• Reddit seeding: answer engines heavily weight r/subreddit discussion for category queries. Show up there honestly.
• Wikipedia and G2: both are cited often. Make sure your presence is accurate.

Why This Works

Traditional rank tracking measures what search engines show. AEO tracking measures what AI models believe. The latter is less volatile per-day but more load-bearing: a single AI recommendation converts better than a #1 Google ranking because the buyer treats it as an endorsement, not a list.

Get a free Scavio key and run your first AEO audit in under 10 minutes.