> ## Documentation Index
> Fetch the complete documentation index at: https://help.trfyx.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Analytics overview

> Navigate Trfyx analytics and interpret traffic, engagement, and conversion metrics.

# Analytics overview

The analytics overview helps you understand what is happening across your website or product. Use it to establish a baseline, spot changes, and decide which questions need deeper investigation.

## Start with a specific question

Analytics is most useful when it answers a decision-oriented question. For example:

* Did qualified traffic increase this week?
* Which landing pages bring visitors who continue to signup?
* Where does the signup flow lose the most people?
* Did a release change how users move through the product?
* Which acquisition sources are associated with valuable outcomes?

Write down the question and the time period before exploring reports. This keeps the investigation focused and makes comparisons more consistent.

## A practical reading workflow

<Steps>
  <Step title="Choose the right project and date range">
    Confirm that you're viewing the intended website or product and select a time period that matches your question. For trend analysis, compare equivalent periods when possible.
  </Step>

  <Step title="Establish the baseline">
    Review the available traffic and engagement metrics first. Check whether the current result is unusual relative to the previous period rather than judging a number in isolation.
  </Step>

  <Step title="Break down the change">
    Where the report supports it, segment by relevant dimensions such as source, landing page, device, geography, or campaign. Avoid applying many filters at once; change one dimension at a time so the reason for a difference remains understandable.
  </Step>

  <Step title="Connect metrics to behavior">
    Use [user journeys](/user-journeys), [funnels](/funnels), and [session replay](/session-replay) to investigate what users did after arriving.
  </Step>

  <Step title="Record the conclusion">
    Note the period, filters, relevant findings, and the next action. A screenshot or shared [embedded dashboard](/embedded-dashboards) can help teammates review the same evidence.
  </Step>
</Steps>

## How to interpret a metric responsibly

A change in a metric is evidence of a change in recorded data, not automatically proof of what caused it. Before drawing a conclusion, check whether the tracking implementation, campaign tagging, site releases, consent behavior, or data imports changed during the period.

Keep these distinctions in mind:

* **Counts** tell you how much activity was recorded.
* **Rates** relate one event or stage to another; always understand the denominator.
* **Trends** show how a metric changes over time, but can be affected by seasonality and traffic mix.
* **Segments** help explain where a result is concentrated, but small sample sizes can be misleading.
* **Attribution reports** describe how recorded acquisition context is associated with outcomes; they do not, by themselves, prove causation.

## Troubleshooting unexpected numbers

If a report is empty or a value looks implausible, verify the date range, selected project, hostname, filters, and event collection first. Check for duplicate trackers, test traffic, blocked requests, and delayed imports. See [Troubleshooting](/troubleshooting) for a structured checklist.

## Recommended next steps

<CardGroup cols={2}>
  <Card title="Build a funnel" href="/funnels" icon="git-branch">Measure conversion through a multi-step flow.</Card>
  <Card title="Define a goal" href="/goals" icon="target">Give an important user action a clear definition.</Card>
  <Card title="Inspect session replay" href="/session-replay" icon="film">Add qualitative context to aggregate trends.</Card>
  <Card title="Connect revenue data" href="/revenue-attribution" icon="badge-dollar-sign">Investigate the relationship between acquisition and revenue.</Card>
</CardGroup>


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