Data Export allows your enterprise data analytics teams of Data Engineers, Data Analysts, and Data Scientists to extract valuable LaunchDarkly event data into their preferred set of data analysis tools including Amazon Redshift and Google BigQuery. Use LaunchDarkly to help power your predictive analytics and AI programs or blend the raw event data with other data sources to analyze a feature’s effect on metrics like conversion, revenue and application performance.
Use Data Export to slice and dice experiment results by any custom attribute that’s relevant to your business like gender, customer satisfaction score, location, device, etc. Combine LaunchDarkly event data with additional data sources in tools like Segment, Adobe, or any other analytics tool, to do incredibly robust analysis. Take action on your data analysis by using the LaunchDarkly API to turn experiments on or off, or to give all users the winning flag variation.
Use feature flag evaluation and explanation data to enhance your customer data profiles within your customer data platform. By adding supplemental user evaluation data into platforms like Clearbit, you'll gain a 360 degree view on how users are interacting with your features. This powerful data can help power your ML, predictive analytics and AI programs.
Data Export is the only way to see each and every feature flag evaluation for debugging purposes. Use Data Export to have full visibility into feature flag evaluations and allow your team to go back and dig deeper for anomalies that your team wasn't able to see in the 30-minute window the in-app debugger provides.
Data Export is quick and easy to set up. Configure a destination and all event data from the configured LaunchDarkly environment will be sent to the destination. We currently support Amazon Kinesis and Google Cloud PubSub as destinations, with many additional destinations coming soon including Segment and mParticle.
Feature Events - Gather all the evaluation data on a single feature flag including the users impacted, their evaluation date and the flag result.
Summary Events - Capture a total count for all feature evaluations and their results over a certain timeframe.
Custom Events - Setup and capture custom event data by defining an explicit custom call to the SDK.