In the browsing era, marketers optimized for one thing: being findable in Google. Today, the goal is different. You want to be citable in AI answers because that’s where customer decisions now begin.

AI assistants like ChatGPT, Perplexity, and Gemini are among the fastest-growing consumer apps of all time. Fifteen million US adults treat ChatGPT and other GenAI platforms as their go-to for online search—and that number is expected to more than double by 2028. Letting ChatGPT search, synthesize, and summarize is a far better experience than scrolling through pages stuffed with ads and SEO-bait.

Today, AI platforms are the front door to your business.

When they cite your brand, the users who click through are better qualified and more likely to convert. But the playbook for earning those citations looks nothing like it did for SEO. Most brands are still stuck in the mindset of tracking human traffic. To navigate to the new AI-first customer journey, you need to start tracking AI traffic. And not all AI traffic is the same. Each bot visiting your site has a different job, and each type of traffic tells you something different about your visibility in AI answers:

🐕 Retrievers: What is the job of a retrieval AI agent?

These are bots to prioritize because their job is to service live demand from the human behind the prompt.

When a human types a prompt into ChatGPT or Perplexity—say, “What’s the best project management software for startups?”—a retriever bot like ChatGPT-User visits to your site to fetch content in real time. This is the closest thing to customer intent you’ll ever see in your logs.

If the bot can access and cite your page, you’ve just shaped a buying decision in the moment it matters. If it can’t, the opportunity goes to a competitor instead. Retrieval is the “front line” of AI traffic, and optimizing for it should always be the priority.

🗄️ Indexers: What is the job of an index bot?

Indexers crawl the web continuously, cataloging and refreshing content so AI platforms have an up-to-date pool of information to draw from.

You may not feel their impact immediately—indexing doesn’t connect to a single user query the way retrieval does—but without them, retrieval bots may never find your pages at all. Think of indexers as the infrastructure of visibility: if you’re not indexed, you’re invisible.

👟 Trainers: What is the job of a trainer bot?

Trainers’ job is to train an LLM.

They aren’t chasing live queries, they’re scraping your content to feed back into the model itself, shaping what the system “knows” in the long run.

This is more of a long term strategy—creating canonical content that becomes part of the model’s background knowledge. When a future version of GPT or Gemini recalls the basics of your category, your pricing model, or your product differentiators, it’s because training bots ingested your material months earlier.

Looking at AI bot traffic as a single, undifferentiated metric isn’t all that helpful. Retrieval is about demand capture. Indexing is about discoverability. Training is about reputation and comprehension over time. Knowing which is which lets you separate signal from noise and focus your efforts where they count most. Retrieval should always take priority, since that’s where the citations and conversions come from.

But if you’re still relying on traditional website analytics, there’s a lot you’re not seeing. Google Analytics and other traditional analytics tools were built for a world of human visitors clicking links, not AI agents fetching and synthesizing information on behalf of those humans. These bots don’t trigger pageviews or events in your dashboards. They don’t bounce, convert, or show up as referral traffic—even when they’re powering a real user query with real intent on the other end. What used to look like background noise in your server logs is now some of the most valuable traffic you have. When a retriever bot visits your site, it’s effectively standing in for a person asking, researching, or deciding—and traditional analytics can’t tell you that’s happening.

You can’t optimize what you can’t see, and without AI-aware monitoring, you’re flying blind to one of your most qualified sources of demand.

That’s why the marketer’s dashboard itself needs to evolve. In the browsing era, it revolved around pageviews, bounce rates, and keyword rankings—metrics that made sense when your goal was to lure people into a funnel. But in an AI-first world, those numbers miss the point. Today, the better questions are:

• How often are AI platforms citing my brand in live answers?
• Which platforms (ChatGPT, Perplexity, Gemini, etc.) drive that activity?
• Which AI agents are indicating intent and which are just indexing my site?
• Which of my pages are being surfaced most often, and are they the ones that actually showcase my differentiators?

The brands that win in this environment won’t be the ones who cling to old SEO dashboards or obsess over keyword density. They’ll be the ones who treat AI traffic as seriously as they do human traffic, build content that is easy for those systems to understand, and measure success by how often they’re cited at the exact moment a buying decision is made. Because in the age of AI search, visibility isn’t about who clicks, it’s about who gets cited.