*This is the markdown version of this page, for agents. To see the web page, open https://trodo.ai/ai-product-analytics?view=html (or use the Human / Agent switch at the bottom)*

# Your users talk to an agent now. See whether it keeps them.

Trodo joins every checked agent trace to the user behind it, so funnels, retention and adoption show whether the agent helped, not only what the user clicked.

- Funnels, retention and flows
- Every trace joined to a user
- Adoption of agent features
- Rage clicks and UX health

## What changes when a product runs on an agent?

Classic product analytics counts clicks and page views. In a product built on an agent, the most important step often happens inside a conversation: the user asks, the agent works through tools, and the answer is right or wrong. None of that is a click.

So the questions change. Did the agent’s answer lead to the next step in the funnel? Do users whose first conversation failed come back? Which agent feature do people adopt, and which do they try once and abandon?

Trodo answers them by joining two kinds of data that usually live in separate tools: product events from your app and traces from your agent, both tied to the same user.

## What Trodo gives product teams. One view of users and agents.

### Funnels and retention

Funnels, retention, flows and cohort comparisons over your product events. ([Product analytics in the docs](https://docs.trodo.ai/product-analytics/overview))

### Traces joined to users

Every trace belongs to a user and a conversation. Go from a drop in a funnel straight to the conversations behind it. ([Identify users](https://docs.trodo.ai/observability/features/users/identification))

### Agent feature adoption

Which jobs people bring to your agent, how often they come back, and which ones they give up on. ([Capabilities in the docs](https://docs.trodo.ai/capabilities))

### Quality you can act on

Every trace is checked, so a failing answer shows up next to the user it happened to, not in a support ticket a week later. ([How checks work](https://docs.trodo.ai/evaluations/overview))

### UX health

Rage clicks, form abandonment, errors and page performance, in the same place as the agent data.

### Lucid, not queries

Ask Lucid for a retention chart or a funnel by plan in plain English and get it with the data behind it. ([Lucid in the docs](https://docs.trodo.ai/lucid))

## Product analytics for agent products, compared

| | Trodo | Classic product analytics | LLM tracing tools |
|---|---|---|---|
| Funnels and retention | Yes | Yes | No |
| Agent traces joined to users | Yes | No | Partial |
| Every trace checked | Yes | No | No |
| Agent feature adoption | Yes | Partial | No |
| Questions in plain English | Yes | Partial | Partial |

## Questions

### What is product analytics for agent products?

Measuring how people use a product built on an agent: funnels, retention and adoption, joined to what the agent did in each conversation.

### How is it different from Mixpanel or Amplitude?

Those count events in your interface. Trodo also sees the agent’s side: each trace, whether it was right, and what it cost, tied to the same user.

### Can I keep my existing analytics?

Yes. Trodo can run alongside your current tools; many teams start by sending agent traces and add product events later.

### How are product events counted?

Each product event is one unit, the same as each trace and span. Developer includes 10,000 units a month and Pro 250,000, with every feature on both.

## Further reading

- [Product analytics for agent products: the 2026 guide](https://trodo.ai/blog/ai-product-analytics-guide-2026)
- [What actually changes from traditional analytics](https://trodo.ai/blog/ai-product-analytics-vs-traditional-analytics)
- [Adoption metrics for agent features](https://trodo.ai/blog/ai-feature-adoption-metrics)
- [Mixpanel vs Amplitude vs Trodo](https://trodo.ai/blog/mixpanel-vs-amplitude-vs-trodo)
- [Retention for agent products](https://trodo.ai/blog/agentic-ai-user-retention)

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Web version: https://trodo.ai/ai-product-analytics?view=html · Everything about Trodo for agents: https://trodo.ai/index.md · Site index: https://trodo.ai/llms.txt