Delighted is a service that employs single question surveys to provide businesses with real-time customer feedback. Each survey question can have a rating scale for customers to select from as well as a section where customers have the option to leave a free-form comment. This provides both a numerical score - that can be collected to create a Net Promoter Score (NPS) - and useful customer feedback that Delighted can filter and search to retrieve the most useful responses for a given purpose.
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.
Bring all your Delighted data to Amazon Redshift
Load your Delighted data to Google BigQuery
ETL all your Delighted data to Snowflake
Move your Delighted data to MySQL
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
Create a survey recipient, including their customer ID, email address and phone number. Then, you can customize your survey delays based on your customers’ needs and preferences, specifying how you want the surveys sent - via SMS or email - and how frequently you want them sent.
Retrieve data from customer responses, including the score they selected, any comments they left in response to the survey and the person ID for the customer (which allows you to continue to track their responses). Additionally, use this data to create and update your Net Promoter Score, which can help provide customer analytics both within Delighted and in other data sources via integration.
View important metrics for your account like your NPS and the percentage of your respondents that identified as promoters, passives, or detractors. This provides a broader view of your survey performance that can help you determine your overall business performance.
When someone unsubscribes, you can maintain their previous survey response data and view their old emails. When integrated with other user data, this information can provide key business insights. It can also be used to run an array of business analyses, including predictive analytics.
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.