Integrate ChartMogul with Mention
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.
Mention monitors conversations about a brand by tracking any time that the brand is mentioned on a range of online platforms, including social media, blogs, or news outlets. Mention can then analyze the sentiment of those conversations and send that information to users in the form of alerts. This data also allows Mention to gauge overall public sentiment and reputation of a brand. If those metrics seem particularly unusual - i.e. if there is a spike in negative public sentiment - they can send notifications immediately so that changes can be made.
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 Mention data to Amazon Redshift
Load your Mention data to Google BigQuery
ETL all your Mention data to Snowflake
Move your Mention data to MySQL
Integrate ChartMogul With Mention 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.
Mention's End Points
Create or modify a Mention user account, including the user’s contact info, how often they receive alerts and what kind of access they have to the data on Mention. This allows you to ensure that users can operate as efficiently as possible and interact with Mention in a way that creates the best workflow for them.
Retrieve a list of mentions that have been tracked by your alerts, which can be filtered by a number of parameters including source, date range and tone. This query then returns details - like description, source and author’s influence score - about the relevant mentions, allowing you to gauge if the mention warrants a response.
Define the parameters of an alert, such as the alert’s name, query terms and tracked sources. Then, retrieve data about the mentions that have triggered the alert, including how many mentions there are and how important it is to respond to them.
Design tags, which can be used to filter responses generated by your alerts. Once a tag is created, you can either fetch all the Mentions with that tag in them or use the tag as one of many parameters to filter queries about the mentions in an alert.