Integrate Intercom with Mixpanel
Intercom is a powerful set of tools for better managing your company’s customer support system. It includes a help center with a feedback system, which you can use to focus future articles on the growing needs of your customers, and it also provides a robust conversation system that allows you to assign support teams to customers based on specific criteria (about the customer or discussion topic), rather than just based on availability. Intercom is designed to create a more effective customer support network by specifically tracking and targeting your customers’ needs.
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 Intercom data to Amazon Redshift
Load your Intercom data to Google BigQuery
ETL all your Intercom data to Snowflake
Move your Intercom 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 Intercom With Mixpanel Today
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Intercom's End Points
Track the content of conversations and who is involved in them. This can be used to generate data about which topics customers are most concerned with so that you can further focus your support efforts accordingly.
Sort specific groups of users and companies that you are communicating with by creating an easily searchable tag that permeates all of your intercom databases, and you can use that tag to integrate other data about those groups throughout intercom.
Collect valuable customer data for your CRM, including basic contact info such as name, email address, and phone number but also more specific data, such as when they signed up, last signed in, and the tags associated with them.
Track the progress of your business relationship with companies (including a list of their users). Use that data to monitor how well your support network is meeting a company’s needs and how much of your overall revenue comes from each of the companies that are interacting with your business via intercom.
Automatically categorize users based on set criteria. Then Intercom can assign support teams based on that criteria, which allows you to more easily match customers with the support team members that can best assist them.
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.