Integrate Mention with Shopify
Mention monitors conversations about a brand by tracking any time that the brand is mentioned on a range of online platforms, including social media, blogs, or news outlets. Mention can then analyze the sentiment of those conversations and send that information to users in the form of alerts. This data also allows Mention to gauge overall public sentiment and reputation of a brand. If those metrics seem particularly unusual - i.e. if there is a spike in negative public sentiment - they can send notifications immediately so that changes can be made.
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 Mention data to Amazon Redshift
Load your Mention data to Google BigQuery
ETL all your Mention data to Snowflake
Move your Mention 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 Mention With Shopify Today
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Mention's End Points
Create or modify a Mention user account, including the user’s contact info, how often they receive alerts and what kind of access they have to the data on Mention. This allows you to ensure that users can operate as efficiently as possible and interact with Mention in a way that creates the best workflow for them.
Retrieve a list of mentions that have been tracked by your alerts, which can be filtered by a number of parameters including source, date range and tone. This query then returns details - like description, source and author’s influence score - about the relevant mentions, allowing you to gauge if the mention warrants a response.
Define the parameters of an alert, such as the alert’s name, query terms and tracked sources. Then, retrieve data about the mentions that have triggered the alert, including how many mentions there are and how important it is to respond to them.
Design tags, which can be used to filter responses generated by your alerts. Once a tag is created, you can either fetch all the Mentions with that tag in them or use the tag as one of many parameters to filter queries about the mentions in an alert.
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.