Integrate AppsFlyer with Mixpanel
AppsFlyer provides users with centralized and accurate ROI tracking for each of their marketing campaigns and advertising sources. This includes both traditional advertising sources - like TV and social media - as well as harder-to-measure sources like in-app advertisements. It then sends all of this data to one consolidated dashboard to be viewed and analyzed.
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.
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AppsFlyer's End Points
Configure a large, daily export of raw data - including organic installs, impressions, uninstalls and in-app events - which is sent to a dedicated AWS bucket. Then, access that exported data whenever you need to and integrate it with other data sources for an even broader variety of insights and metrics.
Appsflyer reports fall into four categories: performance, re-targeting, fraud prevention, and raw data reports. You can export any of these reports to get an array of useful data, including the number of installations in a date range, the number of lost leads that were successfully retargeted, and the number of in-app events that occurred in a set period. This allows you to gauge your true ROI as accurately as possible.
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.