# Experiment Result Exports

> For AI agents: a documentation index is available at [/llms.txt](/llms.txt). Append `.md` to any page URL for markdown, or send `Accept: text/markdown`.

## How experiment result exports work

Statsig lets you export both the reports and the raw data your feature rollouts and experiments generate.

## Export methods

1. [Download experiment results](https://docs.statsig.com/experiments/interpreting-results/export#how-to-export-pulse-data) from the Console as a CSV file, including a summary view, exposures, and the raw data. This method is for one-off downloads and analysis.

![Pulse results export interface](https://docs.statsig.com/images/exports-pulse.png)

2. [Programmatically export the data underlying Pulse](https://docs.statsig.com/console-api/introduction).
3. For ongoing data exports, Statsig supports [data integrations](https://docs.statsig.com/integrations/introduction) through customer data platforms like Segment, RudderStack, and mParticle. There's also a [generic webhook](https://docs.statsig.com/integrations/event_webhook) if you want to build your own integration. To set up a daily export into your data warehouse, go to [Data warehouse exports](https://docs.statsig.com/integrations/data-exports/data_warehouse_exports).

![Grid of event export integrations such as Amplitude, Braze, and Webhook](https://docs.statsig.com/images/exports-events.png)

## Validate exported data

Many teams audit and compare their data in Statsig with what they have in other systems. Statsig uses well-recognized statistical methods and industry best practices, so you can reproduce results yourself.

Tips for validation:

1. Start small: Use a single day of data to reduce variables. When comparing experiments, use a full day (not days the experiment started or stopped, where there's partial data).
2. Third-party ad and tracking blockers can block events sent to third-party services. A server-side integration or [proxying requests through your domain](https://docs.statsig.com/infrastructure/api_proxy/custom_proxy) removes this issue.
3. Check for time zone conversion issues to confirm you use a consistent definition of "day".
4. Statsig applies [winsorization](https://docs.statsig.com/experiments/statistical-methods/variance-reduction#winsorization) on metrics to remove outliers.
5. Statsig applies CUPED to reduce variance on metrics using pre-experimental data. Disable CUPED when comparing console results to external data.