Integrate Recurly with Mixpanel
Recurly is a subscription management service that is designed to provide a variety of billing models to its users - per month, per usage, etc., - and then process recurring charges through those models. Recurly can use data gathered from subscriptions to generate analytics for a company. It also supports integrations with other sales management tools. These can provide users with a more seamless experience and deeper analytic data.
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.
Popular Use Cases
Bring all your Recurly data to Amazon Redshift
Load your Recurly data to Google BigQuery
ETL all your Recurly data to Snowflake
Move your Recurly data to MySQL
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
Integrate Recurly With Mixpanel Today
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Recurly's End Points
Track data about the status of a customer’s subscription - recurring, new, canceled, etc., - and which plans they are subscribing to. This data can help demonstrate the success or failure of various subscription models and show the most popular time periods to subscribe.
Retrieve data about any purchase or payment processed through Recurly, including the amount of the transaction, customer contact information and the status of the transaction i.e.,whether it is declined, voided, or successful. This data can then be used to provide analytics about the actual revenue being generated by your company.
Gather all of the information related to an invoice that has been sent to a customer, including charges, refunds, credits and discounts. This field also includes the payment history for invoices, which can be used to track trends and help with predictive analysis.
Set up and detail the various plans that your subscriptions use. This field includes data about the plans - how much they costs, what the billing rates are, etc., - and also provides customer data about who is using what plans. This can assist in scoring leads and segmenting your customers by lifecycle stage.
Store all of your data about a customer’s account, including contact information and billing history. You can also use this to track a customer’s current and historical subscription data, which can provide you with insights into your general business performance and help you determine which subscription plans are most profitable.
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.