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.
As an advanced, high-speed data analytics platform, Mode helps you understand the information in your data warehouses. As a hybrid solution Mode lets (1) data teams customize queries and visualizations in Python, SQL, or R; and (2) empowers non-tech-savvy users to dive into visualizations and explore live-updating reports to get the data they need.
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 Mode data to Amazon Redshift
Load your Mode data to Google BigQuery
ETL all your Mode data to Snowflake
Move your Mode data to MySQL
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.
Mode's SQL editor features a schema browser to explore the tables and columns of your connected data sources. It also has an autocomplete function to assist with query writing, a query history to browse and reuse old queries, and advanced logic tools for creating loops, IF statements, and more.
The technology behind Mode's analytics solution is Helix, a high-performance in-memory data engine that combines modern drag-and-drop business intelligence tools with a code-first (SQL, Python, R) data science platform to offer an instantly responsive user experience. Mode streams query results into the Helix data engine to reduce database load, provide quick responsiveness, and give users the ability to visually navigate as much as 10 gigabytes of data.
Powered by SQL, Python, and R, Mode dashboards display automatically-refreshing metrics without the need for proprietary tools. Customize your dashboards the way you want, with on-brand reporting and interactive features to facilitate collaboration with others across your organization.
Mode features native Python and R Notebooks. This allows you to query in SQL, send the results to a dataframe in R or pandas, and conveniently access them in the platform's native Notebook. At the same time, a sidebar provides tips, shortcuts, and documentation to help you get the most of these features.