Integrate Atlassian with Shopify
Millions of users globally rely on Atlassian products every day for improving software development, project management, collaboration, and code quality. Atlassian products include: JIRA Software, JIRA Service Desk, JIRA Core, StatusPage, Confluence, HipChat, Bitbucket, SourceTree, Bamboo, Cover, FishEye, Crucible.
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.
Popular Use Cases
Bring all your Atlassian data to Amazon Redshift
Load your Atlassian data to Google BigQuery
ETL all your Atlassian data to Snowflake
Move your Atlassian data to MySQL
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
Integrate Atlassian With Shopify Today
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Atlassian's End Points
Request information about your service desk instance, including its version number, how long the instance has been running and what build it is. Accessing this data will, among other things, allow you to more successfully integrate your service desk with other relevant data sources.
Create a customer entity in JIRA Service Desk by providing Atlassian with the customer’s name, email and display name. Then, use this data in other endpoints to track service requests for a specific customer or integrate it with customer service data from other sources to provide a more comprehensive view of a customer’s journey.
Retrieve data on organizations that are engaging with your service desk, including the organizations’ names, IDs, properties and associated users. Then, access this endpoint to track those organizations, their users and their service requests so that you can have a better understanding of your service interactions with them.
Track any and all customer service requests and get relevant data, such as the customer’s contact info, the reason for the request, and the status of the request (what step it is on in your customer service process). Use this data to evaluate how well your company is responding to these requests and/or monitor customer service trends.
Shopify's End Points
Shopify Abandoned Checkout
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.