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.
Microsoft Azure is a public cloud computing service designed for building, testing, launching, and managing applications and services via Microsoft-managed data centers. Through its platform-as-a-service (PaaS), software-as-a-service (SaaS), and infrastructure-as-a-service (Iaas) offerings, Microsoft Azure integrates with a wide range of programming languages and tools. In addition to working with Microsoft's proprietary software and systems, Azure is compatible with third-party solutions, including Linux. As an extremely popular cloud services platform, many businesses and enterprises have used Microsoft Azure to migrate their computer systems to the cloud and eliminate the costs and staff requirements needed to maintain physical onsite servers.
Bring all your Mixpanel data to Amazon Redshift
Load your Mixpanel data to Google BigQuery
ETL all your Mixpanel data to Snowflake
Move your Mixpanel data to MySQL
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 Mixpanel 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 Mixpanel data into your analytics to provide a more comprehensive view of your retention trends over time.
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