Integrate Freshdesk with Mixpanel
Freshdesk is a customer support ticketing system that includes a range of ticketing tools such as ticket prioritization, service level agreements, native internal communication between collaborating agents, automated suggestions for ticket solutions and in-depth customer support analytics.
Mixpanel gathers product usage data, including metrics like what features are being used most frequently, the number of active users, and when user engagement rises or drops. It also automatically collects data on all user actions and uses that data to provide a variety of useful insights, such as automatic suggestions for how to improve customer retention and lead acquisition. Since usage data is collected from the start, Mixpanel can also track newly defined metrics using historical data.
Popular Use Cases
Bring all your Freshdesk data to Amazon Redshift
Load your Freshdesk data to Google BigQuery
ETL all your Freshdesk data to Snowflake
Move your Freshdesk data to MySQL
Bring all your Mixpanel data to Amazon Redshift
Load your Mixpanel data to Google BigQuery
ETL all your Mixpanel data to Snowflake
Move your Mixpanel data to MySQL
Integrate Freshdesk With Mixpanel Today
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Freshdesk's End Points
Create, view, and/or modify information associated with one of your support agents, including their contact information (name, email, phone number), their permission level and which customer support group they belong to. You can also see if the agent is currently available to take a ticket and how long they have been available for so that you can assign tickets to appropriately.
Retrieve and update information about replies and notes associated with tickets, including the full text of the reply and the IDs of the agents, customer and support ticket associated with the conversation. This will not only allow you to integrate the full content of a support interaction into your customer support analytics but also allow Freshdesk to provide deeper analytics with regards to support agent performance.
See an array of information about a support ticket, including the customer that submitted the ticket, the source they submitted it from, the assigned agent, the content of the support request and the priority that Freshdesk has assigned that ticket. This, along with data about the type of support issue that the ticket is addressing, will allow you to more effectively assign the right members of your support team to the right tickets.
View data about a contact that has created a support ticket. This includes both basic contact information - like their name, email address, and social media ID - and information that will help you to more effectively assign the right agents to meet that contact’s needs, such as their preferred language, their associated tags and what other tickets they have submitted.
Mixpanel's End Points
Get any or all raw event data that has been collected by Mixpanel, including what events have occurred, when they happened, and any relevant properties about those events. Then, integrate this raw data with other data sources to get new or deeper usage analytics.
Retrieve data about a customer’s journeys through your funnel. This data contains the customer’s timeline from start to finish - including how many steps in the funnel the customer completed during that time - which can be used to identify which steps during a funnel most commonly include specific events, such as losing a customer.
Gather event data that is filtered into segments by an array of properties, such as date range, country, and specific search terms. Then, use that filtered data to get deeper, more detailed analytics into your product performance.
Track customer engagement data, including a customer’s name and email address, as well as the date and time they last accessed your product. This allows you to run predictive analytics, which can show when engagement will likely drop or increase based on historical engagement data.
Get retention data for a specific cohort of customers by tracking signups and other relevant events during a specified date range. Then, you can feed that data into your analytics to provide a more comprehensive view of your retention trends over time.