ChartMogul can turn new and existing business intelligence data into valuable analytics that companies can use to improve their market performance. ChartMogul can take subscriber data - both created within ChartMogul and imported from other data sources - and generate visualized analytics for a variety of metrics that SaaS companies care about.
Google Sheets is an online spreadsheet app that lets users create and format spreadsheets while simultaneously working with other people. Businesses can use Google Sheets to maintain data consistency across departments and to ensure that every member of their team is on the same page.
Bring all your ChartMogul data to Amazon Redshift
Load your ChartMogul data to Google BigQuery
ETL all your ChartMogul data to Snowflake
Move your ChartMogul data to MySQL
Bring all your Google Sheets data to Amazon Redshift
Load your Google Sheets data to Google BigQuery
ETL all your Google Sheets data to Snowflake
Move your Google Sheets data to MySQL
Gather data about your subscription plans - like the subscription IDs, names, billing intervals, and the number of intervals that are charged at once - to evaluate the performance of each plan. This will help you better understand the effectiveness of your plans so that you can determine which ones are more or less successful as a whole.
Create, retrieve, or update data for new or imported customers in ChartMogul. This allows you to see important customer contact details, customer IDs, and valuable performance data including a customer’s MRR, ARR, and industry sector. You can then use that data to better segment your customers, which can provide more accurate and specific information about your business performance.
Import invoice data for customers that you are tracking through ChartMogul, including customer IDs, dates of purchase, transactions, and any relevant line items. Then, use ChartMogul to create subscription data for those customers and use that data to track more specific revenue data, both in ChartMogul and in your other data sources.
Track payments or refunds made on an invoice to see the transaction ID, type of transaction, transaction date, and whether or not the transaction was successful. This can help you get more accurate analytics from your invoice data. It can also indicate when there is an unusually high number of refunds, which could signal a problem worth addressing.
Get a list of subscriptions that ChartMogul has automatically generated from invoice data. This endpoint returns several IDs - including subscription IDs, customer IDs, plan IDs, and data source IDs - that will help you to more easily track and integrate data between any of those parameters to create deeper, more accurate business analytics.
Use tags to track terms that are associated with a customer so that you can segment or monitor them more specifically. For example, you could tag a particular customer as “high priority,” “returning” or anything else that is relevant to your business, and then retrieve a list of customers who have been tagged with those attributes in order to analyze them as a segment.
Update customer data with ChartMogul custom attributes that are more specific to the needs of your company. This can include both tags as well as more complex custom attributes. Then, track those attributes in ChartMogul to get analytics that are focused on your particular business concerns.
Use developer metadata to keep track of a location or an object in a spreadsheet. This can help you maintain data organization and clarity, even as you scale or continue to add new rows of information.
Create new spreadsheets, look up existing spreadsheets via spreadsheet ID, or get data on portions of a spreadsheet using filters. These functions can help you understand and consolidate your data for big-picture business insights.
Maintain full control over the values on your spreadsheet and add, clear, append, or update values as necessary. Use this flexibility to keep your data up-to-date and useful at all times.
Use sheets to copy a single sheet from a spreadsheet to another spreadsheet. This can be especially useful when you’re integrating data from various sources or reorganizing your data structure for analytics.