Integrate Stripe with Mode
Stripe is a SaaS payment management tool. It is built to be an all-in-one payment solution for any business, whether that business offers an on-demand service, traditional product sales, or subscription-based services. Stripe’s tools are designed to help users with a variety of tasks related to running those businesses, including: issuing refunds, processing orders, and managing different subscriptions.
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.
Popular Use Cases
Bring all your Stripe data to Amazon Redshift
Load your Stripe data to Google BigQuery
ETL all your Stripe data to Snowflake
Move your Stripe 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
Integrate Stripe With Mode Today
Free 14-day trial. Easy setup. Cancel any time.
Stripe's End Points
Retrieve data from all your customer transactions, which provides basic details about the customer, such as their name, address, and email, in addition to data about the charge itself, such as if it was accepted, disputed, refunded, etc.
View or create data about new and existing customers, which allows you to track recurring charges, subscriptions, and multiple purchases. This can, in turn, help you to monitor a customer’s transaction history throughout their lifecycle with your company.
Retrieve any automatically recorded event that occurs on your account, whether it’s a charge, subscription, failed invoice payment, or anything else of note. This allows you to have current, up-to-date data about what is happening on your account at any given moment.
Monitor an invoice, which is created as part of a recurring payment on Stripe. This returns data on the charged amount, whether the invoice was successful, how many attempts the invoice has made to collect the money, and which subscriptions are linked to that invoice, if applicable.
Collect data on different subscription plans that you have, which includes the cost of the plan, how and when it is billed, and the plan’s trial period. You can then integrate the plan data with your subscription or customer data to get a deeper view of the sales performance of various plans.
Track which clients are subscribed to which plans, as well as when they subscribed, when they canceled, and how many users they are subscribed with. This field also allows you to track charges associated with those subscriptions so that you can monitor the revenue they generate.
Mode's End Points
Mode White-Label Embeds and Visualizations
Mode SQL Editor
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.
Mode Helix Data Engine
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.
Mode Dashboard Features
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 Native Python and R Notebooks
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.