Masterclass
Track and Optimize AI Search Preformance
52:24
intermediate
March 27, 2025
In this webinar, you will learn how to extract and analyze AI-generated search results using Bright Data’s scraping infrastructure, monitoring platforms like Google SGE, ChatGPT and Perplexity to understand how your brand is represented, which sources are cited, and how to adapt your content strategy for AI-driven search.
In This Tutorial, You’ll Learn How To:
  • Simulate AI search queries
  • Extract AI-generated answers
  • Analyze citation sources
  • Optimize content for AI
  • Monitor brand search visibility
  • Automate tracking workflows
  • Adapt SEO for AI
Start Free Trial
Start Free Trial
Speakers
Ariel Shulman
CPO @Bright Data

“AI is changing how people search—and how they find your brand. If you’re still stuck in the old SEO mindset, it’s time to adapt.” – Ariel Schulman, CPO

In this webinar hosted by SEJ, we will share how we’re helping brands stay visible in a world where AI is rewriting the rules of search.

In this guide, I’ll walk you through how I track and optimize AI-generated search results using Bright Data’s tools. Whether you’re a marketer, SEO expert, or tool developer, this tutorial will give you the framework and tools to understand how AI engines like ChatGPT, Perplexity, and Google’s SGE (Search Generative Experience) are impacting your brand—and how to stay ahead.

Let’s dive in.

Why AI Search Optimization Matters

A few years ago, SEO was all about ranking on Google. But now, users are getting direct answers from AI-powered tools—without ever clicking a link. This shift is massive.

Today, people are asking full questions like “What’s the best protein powder for a 25-year-old who lifts weights 3x a week?” instead of just typing “protein powder 2025.” And AI engines like ChatGPT and Perplexity are answering those questions instantly—often using your content, but without sending traffic to your site.

At Bright Data, we’ve seen this firsthand. We’ve worked with thousands of brands and noticed a sharp drop in organic traffic—even when rankings stay the same. That’s because AI-generated answers are replacing traditional search results.

So we built a system to track, analyze, and optimize how brands appear in AI search. And in this guide, I’ll show you exactly how it works.

The Architecture of an AI Search Monitoring System

Here’s a high-level overview of the system we’ll build:

  1. AI Query Simulation: Send real user-like queries to AI tools like Google SGE, ChatGPT, and Perplexity.
  2. AI Answer Extraction: Scrape and parse the AI-generated responses, including citations and source links.
  3. Content Optimization: Analyze which content is being cited and adjust your own to match.
  4. Monitoring & Automation: Track changes over time and identify trends in visibility.

Let’s break it down step by step.

Step 1: Simulating AI Search Queries

To understand how AI tools are presenting your brand, we first need to simulate real-world queries. These are the kinds of questions your customers are asking AI tools every day.

For example:

  • “Is Bright Data a good web scraping company?”
  • “What are the best alternatives to Bright Data?”
  • “How does Bright Data compare to ScraperAPI?”

We use Bright Data’s Web Unlocker and Scraper APIs to send these queries to AI tools like Google SGE and Perplexity.

Here’s how it works:

  • Launch a headless browser using Bright Data’s Browser Extension or API.
  • Set up a proxy to simulate a user from a specific location (e.g., US, UK).
  • Type the query into the AI interface using human-like keystrokes.
  • Wait for the AI-generated answer to load.
  • Extract the full HTML of the response.

This process mimics a real user interaction, which is critical because AI tools often render content dynamically and may block bots.

Step 2: Extracting AI-Generated Answers and Citations

Once we have the response, we need to extract the actual answer and any source links the AI used.

Let’s say we ask Google SGE: “Does honey ever expire?”

The AI-generated answer might say:

“Honey never spoils due to its low moisture content and high acidity. Archaeologists have found edible honey in ancient Egyptian tombs.”

We use Bright Data’s HTML parser to extract:

  • The full AI-generated text
  • Any citations or source URLs
  • The structure of the answer (e.g., bullet points, lists, headers)

This gives us insight into which sites are being cited and how the AI is summarizing the information.

💡 Pro Tip: If your site is being cited, that’s great! If not, look at the structure and language of the sites that are—and adjust your content accordingly.

Step 3: Optimizing Your Content for AI Inclusion

Now that we know what the AI is looking for, we can optimize our content to increase the chances of being included in future answers.

Here’s what we’ve found works best:

  • Use natural, conversational language. AI prefers content that sounds human.
  • Structure your content clearly. Use H1 for the main topic, H2s for subtopics, and bullet points for clarity.
  • Keep it fresh. Update your content regularly and include publish/update dates.
  • Make your site indexable. Ensure your robots.txt file allows AI bots like PerplexityBot and ChatGPT-User to crawl your content.

Example robots.txt snippet:

User-agent: PerplexityBot
Allow: /

User-agent: ChatGPT-User
Allow: /

We applied these changes to our own documentation site (docs.brightdata.com) and saw a measurable increase in traffic from ChatGPT citations.

Step 4: Monitoring Your Brand in AI Search

Once your content is optimized, it’s time to track how you’re performing in AI-generated results.

We recommend monitoring three types of queries:

  1. Brand Queries
    Ask questions like “What is Bright Data?” or “Is Bright Data reliable?”
  2. Category Queries
    Try “Best web scraping tools” or “Top data providers 2024.”
  3. Competitive Queries
    Ask “Is Bright Data better than ScraperAPI?” or “Bright Data vs. Oxylabs.”

Using Bright Data’s API, you can automate these queries and store the results in a database (e.g., PostgreSQL or Supabase). Then, build a dashboard to visualize trends over time.

You’ll be able to see:

  • Which queries trigger AI answers
  • Whether your brand is mentioned
  • Which competitors are being cited
  • How your visibility changes week to week

Bonus: What Happens Under the Hood

For the techies out there, here’s a peek behind the scenes.

When we send a query to ChatGPT or Perplexity, we:

  • Launch a cloud browser
  • Simulate human typing
  • Wait for the AI to generate a full response
  • Parse the HTML and extract the answer
  • Store the result in a structured format (JSON or Markdown)

We even simulate follow-up questions to see how the AI conversation evolves. This gives us a complete picture of how a user might interact with the AI—and how our brand appears throughout.

What’s Next? Take Your AI Monitoring to the Next Level

Once you’ve built your AI search monitoring system, here are a few ways to expand it:

  • Set up alerts for when your brand is mentioned (or not mentioned) in AI answers.
  • Track changes in AI citations over time to identify trends.
  • Compare your AI visibility with competitors.
  • Use AI to generate recommendations for improving your content.
  • Integrate with tools like Slack or email for real-time updates.

You can even build a Retrieval-Augmented Generation (RAG) system to create your own chatbot that answers questions using your brand’s content.

Wrapping It Up

AI is changing how people search—and how they find your brand. If you’re still focused only on traditional SEO, you’re missing a huge part of the picture.

By combining Bright Data’s scraping infrastructure with a smart content strategy, you can track your visibility in AI-generated answers, optimize your content, and stay ahead of the competition.

The Data You Need
Is Only One Click Away.