Integrate ChartMogul with Fullstory
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.
Fullstory helps companies record and analyze their customer communications by recording user sessions, providing detailed step-by-step logs of everything customers did during their sessions and storing that information for later retrieval and analysis. Fullstory can then be searched for specific events, including link usage, rage clicks or dead clicks. In addition to data on individual sessions, Fullstory can also retrieve analytics on aggregate customer behavior, showing the most clicked items, the most rage clicked areas, the most navigated to sites, etc.
Popular Use Cases
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 Fullstory data to Amazon Redshift
Load your Fullstory data to Google BigQuery
ETL all your Fullstory data to Snowflake
Move your Fullstory data to MySQL
Integrate ChartMogul With Fullstory Today
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ChartMogul's End Points
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 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.
Fullstory's End Points
Provide a user ID and/or email address to get a list of every session associated with a specific user up to the defined limit. Entries in that list include the user ID and email address, the time the session occurred, and the Fullstory session URL, all of which can be used to access the data from that session if desired.
Retrieve a list of 20 available data bundles from a specific timestamp onward. Then, export the most valuable data bundles from that list so that they can be integrated with other relevant data sources to give you a deeper overall view of your customer’s experience.