# Total leads

Track how many leads your experiment generated.

> **Tracking required**
>
> Track the [Lead generated](/reference/event/types/engagement/lead-generated) event to feed data into this widget.

This chart shows the total number of leads generated, broken down by each variant of your experiment.

A lead typically refers to a user who has demonstrated an interest in your product or service by performing a particular action, such as filling out a form, requesting a quote, signing up for a newsletter, or registering for a waiting list.

This metric helps you understand how the variants in your experiment are influencing lead generation.

## Metrics

![Total leads widget](/assets/reference/analytics/experiment/total-leads.png)

The chart includes:

1. **Total leads**\
   The number of leads generated during your experiment.
2. **Leads per variant**\
   The number of leads generated by users who were impacted by each variant in your experiment.

> **Question: What does the comparison over the last period mean?**
>
> It represents the growth or decline of the metric compared to the previous period.
>
> The *last period* refers to the date filter you selected. For example, if the filter is set to the **last 7 days**, the *last period* will be the **7 days immediately before that range**.

## Interpretation

This chart helps you understand how many leads your experiment is generating and how each variant contributes to that result.

This metric is especially useful when assessing whether a new layout, message, or call to action in a given variant is more effective at driving users to complete key lead-generation actions. For example, if Variant B introduces a simplified form or clearer value proposition, you can track whether the total number of leads increases among users assigned to that variant.

### What the number tells you

Here are some common insights you can get from this widget:

- A rising lead count for a given variant suggests that the version shown to that group is influencing user behavior positively and helping more visitors convert.
- A decline or consistently low count for a given variant may point to issues with the content, audience alignment, or form flow in that variant, signaling an opportunity for refinement or further testing.
- Similar lead counts across variants may indicate that the differences between versions are too subtle to influence decisions.
- Sudden spikes or drops in leads generated might be linked to external factors, such as campaigns, traffic changes, or seasonal trends affecting the experiment.

## Explore

- [Events](/reference/event/overview#event-types): Learn how to track user events for analytics and personalization.
- [Audiences](/explanation/audience): Understand how to delivery content to specific groups of users.