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Customers

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The Customers Submodule in the Master Data Module enables users to manage all customer records in a centralized and structured manner. It provides capabilities to view, search, add, edit, delete, and filter customers based on various attributes.


1.4.1⠀Overview #

The Customers page displays a tabular list of all registered customers with key details such as:

  • Customer Code
  • Customer Name
  • Mobile Number
  • Email
  • Address
  • Created Date & Time


Key Features #

  • Global search (by name)
  • Advanced filtering (by country, state, address)
  • Add new customers
  • Edit existing records
  • Delete customer records
  • Pagination for large datasets


1.4.2⠀Search & Filter Customers #


Purpose #

To search and filter out customers with proper details


Search Customers #

  1. Navigate to Master Data → Customers
  2. Use the Search bar (Search by name) at the top
  3. Enter the customer name
  4. Matching records will be displayed instantly
  5. You can also filter out the customers according to their addresses by clicking the filter button


1.4.3⠀Add a New Customer #


Purpose #

To create new customer records


Steps to Add Customer #

  1. Go to Master Data → Customers
  2. Click “Add Customer” (top-right corner)
  3. Fill in the required details like Basic Information, Identity Details, Location etc.
  4. Click “Save Changes”
  5. Customer will be added successfully to the list


1.4.4Edit Customer #

  1. Locate the customer from the list
  2. Click the three-dot menu (⋮) on the right
  3. Select Edit
  4. Update required fields
  5. Click Save Changes


1.4.5.Delete Customer #

  1. Locate the customer in the list
  2. Click the three-dot menu (⋮)
  3. Select Delete
  4. Confirm the deletion

⚠️ Note: Deleted records cannot be recovered.


1.4.6Production Notes #

  • Mandatory Fields: Name & Phone must be filled
  • Avoid Duplicates: Do not create multiple entries for the same customer
  • Deletion: Permanent action, cannot be undone
  • Data Accuracy: Ensure correct GST and contact details
  • Performance: Use filters for faster access in large datasets
  • Consistency: Maintain uniform naming and address formats

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