Shopify Public App Development
API Integration
UI/UX
AWS Server
TypeScript
AdobeXD
Shopify
Node.js
When it comes to automating order processing and fulfillment, order tagging is a crucial step. A fantastic concept came from TagRobot, the client, who came up with a Shopify app that makes it easy to set up criteria for automatic tagging. As an outcome, the tags applied to customers and orders can categorize and filter.
Customer and order tags were added to both past and current orders by the client, who sought to improve the existing app for this purpose. In addition, there are other features like adding a new rule, checking the list of rules, enabling and deactivating rules, refreshing the list of rules, as well as editing, deleting, and applying rules.
Every online business owner aspires to be successful and build a well-known brand. As a result, the more prominent a brand is, the more likely it will be targeted by online fraudsters. One needs to take these concerns seriously and devise measures to counteract and mitigate the effect of fraud on online stores. A person's personal and credit card data may be used to perform online fraud, and the card does not need to be present for the transaction. Fraud committed by criminals is more severe than friendly fraud, in which the client makes an unintentional chargeback to get free products and avoid payment. The client requested functionality that automatically generates and applies tags depending on the threat level.
The client asked that all orders, customers, and items be automatically tagged. Using tags to apply a specific set of criteria to a large number of things might make it easier to filter. However, despite the app's ease of use and its ability to modify tag modifications and apply them to a specific set of items, the client needed this app to operate not only for current and future orders but also for previous ones. They also wanted it to work with custom tags and rules.
When a consumer does not provide permission for a transaction, it is considered fraudulent. A chargeback might result in the loss of money for the shop owner if the transaction is fraudulent. It is usually a good idea for merchants to review their orders for fraud before they are automatically sent to fulfillment. It allows business owners to put any suspicious orders on hold while the rest of the purchases are automatically fulfilled. A lot depends on how they intend to manage high-risk transactions and the current order procedure. We used the Order Risk API to create appropriate tags, such as medium, low, and high, to address this issue.
WebDesk Solution has created a highly customizable TagRobot Shopify application that assists merchants in forming tags for orders and customers. TagRobot is also available inside the merchant's store notification templates (including Order Printer), allowing them to personalize notifications based on the tags they deem appropriate for their store and customers. The store will analyze each new order for each tagging rule once a merchant has created a set of tagging rules using TagRobot. If any of the rule criteria are met, the order will be marked according to the rule; they can apply their standards to previous orders in addition to automatically marking new ones. TagRobot allows them to arrange their consumers efficiently using tags. For example, a store owner wishes to compile a list of all consumers who have placed an order for a specific item. They have to define the rule, apply it to previous orders, and identify and tag customers with that criteria.
Merchants can use an Order Tag to classify or categorize orders. It can prove vital to getting insights into the orders placed, such as orders with discount codes, orders from a specified region, etc. The Order Tag can get order information before applying the auto tag to orders that meet the rule parameters. TagRobot allows merchants to set rules for order segmentation and grouping for various purposes, including marketing, product sales analysis, and more.
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