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Impressions

An impression refers to the count of the total number of times a specific piece of content, such as an advertisement, post, or a webpage, is displayed, regardless of whether it was clicked or not. Impressions are a key metric used to measure the reach or visibility of a piece of content.

For example, if a user sees an advertisement on a webpage, that counts as one impression. If the same advertisement is displayed to the user again on a different page, that would count as a second impression.

Impressions are a valuable metric in understanding user engagement and the effectiveness of content or advertising campaigns. They provide insight into how often a piece of content is being displayed, which can be used to gauge visibility and reach.

In the context of Statsig, impressions can be used to monitor the rollout of a product or feature. For instance, watching usage/impressions start to ramp up in a specific region or for a new feature. They can also be used to watch for spikes in error logs, understand which users are being affected and when, and monitor the rollout of a fix as errors return to baseline.

It's important to note that impressions do not provide information about user interaction with the content. An impression is counted whenever the content is displayed, regardless of whether the user interacts with it or not. For more detailed engagement metrics, other measures such as clicks, conversions, or time spent on page might be used in conjunction with impressions.

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What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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