Integrate Shopify with Mixpanel
Shopify is an eCommerce platform that provides tools for both online and physical sales. On Shopify, users can set up an online store with pre-made themes. They can also accept payments from a variety of sources and use the analytics to look at their business’s sales trends. This can help them understand where they need to better focus their sales and marketing efforts.
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 Shopify data to Amazon Redshift
Load your Shopify data to Google BigQuery
ETL all your Shopify data to Snowflake
Move your Shopify 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 Shopify With Mixpanel Today
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Shopify's End Points
Track checkouts that were added to a customer’s cart but not completed as sales. This field includes data about the customer, the product and the reason for cancellation. It can help determine which products are most commonly abandoned at checkout and why, allowing you to run better predictive analyses about your future products and customers.
Retrieve basic customer information - such as ID, email, mailing address, and name - as well as data about customer behavior, such as the last order a customer made, their total amount spent or how many orders they have made with your company. You can then use this data to focus your marketing efforts towards specific customers or demographics.
Retrieve important data about an order request, such as customer contact information, the product ordered or the status of the order itself. Then, use this field to track important sales data like what products are being ordered the most or sales trends based on region or product price.
Create any number of product groupings and view data ranging from the product name and product ID to how much the product weighs, when it was created and how much it costs. Then, use that data to track trends and understand what types of products have been successful and why.
Track any exchange of money that occurs on Shopify, including completed sales, refunds and voided orders. This data can also track the actual revenue generated from your orders via their order ID’s, which will provide you with a sales-focused view of how well your business is performing.
Capture data from any transaction where the money has been refunded to the customer or any transaction where an item has been returned after being ordered. You can then view details about how much was refunded, what products were returned and whether or not those products have been restocked. This information can ultimately help you understand which products are successful, which are not and why.
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.