Before you get started
Here are some key details to note about switching to Marsello from another marketing platform:
When you connect your POS and/or eCommerce store to Marsello, your customer database will automatically sync into Marsello.
To update your customers' points, you'll need to prepare for a Points Import.
You may need to convert your existing rewarding rule to match your Marsello earning settings.
Convert your current Loyalty Program to match Marsello's earning settings
Before importing your customer points balances, be sure to confirm they matchyour new Marsello settings as you may need to convert/update your customers' current points balances.
Below you will find a few examples of the most common points conversion scenarios merchants face when switching to Marsello.
Example 1
Original loyalty program rewarded customers 1 point for every $1 spent.
In Marsello, merchants update the Making a purchase earn rule to 'Earn 1 point for every $1 spend'.
📝 Note: This is the default Making a purchase setting in Marsello
Example 2
Original loyalty program rewarded customers 1 point for every $5 spent
In Marsello, merchants update the Making a purchase earn rule to 'Earn 1 point for every $5 spend'
Example 3
Merchant decides to create a new loyalty scheme in Marsello from scratch
Original loyalty program rewarded customers 1 point for every $10 spent and wants customers to earn 1 point for every $1 spent in Marsello
Merchant must convert customer's existing loyalty balances to match the new rule for their Marsello program by multiplying customer points balances by 10
Merchant needs to import new customer points balances into Marsello
Create an import file of customer customer points balances to be brought into Marsello
1. Start a blank spreadsheet with two columns:
The First Column should be populated with one of the following identifiers:
- Email
- Vend customer ID
- Shopify customer ID
- ExportId
- Mobile
- VendCustomerCodeThe Second Column is required to be Points
2. Enter the unique identifier (for example, the below screenshot using the Marsello ExportId) of the customers whom you want to tag with your custom tag
If you do not wish to add any points, ensure that the points column has 0 next to each identifier.
3. Copy the two columns to your clipboard
Import your data into Marsello
1. In Marsello, go to Customers > All Customers
2. Click the arrow next to Update customer list and in the drop-down select Import points
3. A pop-up will appear that requires you to select the identifier that you have for each customer and select the unique identifier that you're using to update the tag:
4. Select how you want the points to be added:
Add imported points to customers' points balance
If you have your points column set as 0, no points will be added.
Replace customers' current points balances with the imported points balance
If you have your points column set as 0, all customers will have their points reset to 0.
5. Add your custom tag that you wish to include on the customer's profile and for segment purposes:
💡Quick Tip: Marsello always automatically includes a tag to all imports with the date and time of the import unless you change the text in the box.
6. Click Upload CSV
💡 Quick Tip: It's quicker to manually enter your data than it is to use 'Upload data from file'
7. Drag and drop your CSV file or click Click to upload
8. Select the file from your computer and click open
9. Select your header row and click next.
10. Map your columns and click next
11. The importer tool will not import any lines with errors, and will highlight these columns with red:
📝 Note: You can select to only show the rows with problems to make any necessary amendments. Otherwise, the import tool will ignore any columns with errors.
12. Scroll to the bottom of the pop-up and click Continue.
📝 Note: If your pasted data contains any errors, a message will appear saying that you have unresolved errors. Click "Prev" to make the adjustments to your CSV file.
13. Click Continue to start importing your data.
📝 Note: This import may take up to 4 hours, depending on the size of your database.
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