Integrate Recurly with Appsee
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.
Appsee enables mobile app publishers and developers to track, understand and improve the user experience in their apps, and act on insights delivered by our SaaS platform.
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 Appsee data to Amazon Redshift
Load your Appsee data to Google BigQuery
ETL all your Appsee data to Snowflake
Move your Appsee data to MySQL
Integrate Recurly With Appsee 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.
Appsee's End Points
Track a variety of data related to events that happened during user sessions, such as the number of total events in a given period, the properties associated with those events and the number of occurrences of a specific property. This endpoint can also be used to signal when an event occurrence might warrant further examination of the video recording to see when and why it occurred.
Monitor how users interact with your screens, including how many times a screen was accessed, what types of gestures were used, and what screen was accessed next. This can give you a broader view of how your users interact with your app. Use this information to gauge the effectiveness of your screen designs and know which features are being used more or less frequently.
Get analytics data for your app, including the number of users that accessed it and the number of sessions that occurred. This data can be filtered by a set of parameters, including country, date, OS, device, and session duration.
Request data about a user’s session, which can be filtered by things like user ID, included events, device type and screen. Appsee will return any pertinent data and include information like the video URL, crashes that occurred and any other events that occurred during the session.
Retrieve data about your conversion Appsee funnels and sort it by parameters, including date range, app version, device and platform. Then, Appsee will return a list of steps in the funnel, along with how many users accessed that step and what their completion percentage was.