Integrate Fullstory with Mixpanel
Fullstory helps companies record and analyze their customer communications by recording user sessions, providing detailed step-by-step logs of everything customers did during their sessions and storing that information for later retrieval and analysis. Fullstory can then be searched for specific events, including link usage, rage clicks or dead clicks. In addition to data on individual sessions, Fullstory can also retrieve analytics on aggregate customer behavior, showing the most clicked items, the most rage clicked areas, the most navigated to sites, etc.
Mixpanel gathers product usage data, including metrics like what features are being used most frequently, the number of active users, and when user engagement rises or drops. It also automatically collects data on all user actions and uses that data to provide a variety of useful insights, such as automatic suggestions for how to improve customer retention and lead acquisition. Since usage data is collected from the start, Mixpanel can also track newly defined metrics using historical data.
Integrate Fullstory With Mixpanel Today
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Fullstory's End Points
Provide a user ID and/or email address to get a list of every session associated with a specific user up to the defined limit. Entries in that list include the user ID and email address, the time the session occurred, and the Fullstory session URL, all of which can be used to access the data from that session if desired.
Retrieve a list of 20 available data bundles from a specific timestamp onward. Then, export the most valuable data bundles from that list so that they can be integrated with other relevant data sources to give you a deeper overall view of your customer’s experience.
Mixpanel's End Points
Get any or all raw event data that has been collected by Mixpanel, including what events have occurred, when they happened, and any relevant properties about those events. Then, integrate this raw data with other data sources to get new or deeper usage analytics.
Retrieve data about a customer’s journeys through your funnel. This data contains the customer’s timeline from start to finish - including how many steps in the funnel the customer completed during that time - which can be used to identify which steps during a funnel most commonly include specific events, such as losing a customer.
Gather event data that is filtered into segments by an array of properties, such as date range, country, and specific search terms. Then, use that filtered data to get deeper, more detailed analytics into your product performance.
Track customer engagement data, including a customer’s name and email address, as well as the date and time they last accessed your product. This allows you to run predictive analytics, which can show when engagement will likely drop or increase based on historical engagement data.
Get retention data for a specific cohort of customers by tracking signups and other relevant events during a specified date range. Then, you can feed that data into your analytics to provide a more comprehensive view of your retention trends over time.