Upload a Customer Attributes Dataset

This content is only for clients with the one-click DATASETS option in the top navigation bar. If you click DATASETS and see Product Data and Customer Data listed as menu options, then this content doesn't apply to your account. Instead, see Upload a Customer Dataset.

A Customer Attributes dataset contains data you've collected about customers. You can use this type of dataset and its data to better target customers and personalize their experiences on your site.

Before you upload a dataset to Monetate, ensure that it meets the requirements as explained in Customer Dataset Upload Requirements.

Follow these steps to create a Customer Attributes dataset.

  1. Click DATASETS in the top navigation bar, and then click CREATE DATASET.

    Callout of the 'CREATE DATASET' button on the All Datasets list page

  2. Select Customer Attribute and then click NEXT.

    Step 1 of the Create Dataset Schema wizard, with 'Customer Attribute' selected and a callout of the NEXT button

  3. Name the dataset you're creating, and then click NEXT.

    The name must begin with a letter and contain only letters, numbers, and underscores.

    Step 2 of the 'Create Dataset Schema' wizard, with a name for the dataset in the field and a callout of the NEXT button

  4. Drag and drop the file you want to upload into the Create Dataset Schema wizard, and then review the schema generated to ensure all the column headers are present and correct. Select My file looks good, and then click NEXT.

    The file must be in the CSV or TSV format. Schema and field names must begin with a letter and contain only letters, numbers, and underscores. If the file you attempt to upload does not meet these requirements, an error message appears.

    Correct the errors in the file, and then upload it again to the wizard.

    Animated demonstration of a user dragging and dropping a CSV file into the 'Create Dataset Schema' wizard, reviewing the schema generated, clicking the 'My file looks good' checkbox, and then clicking the NEXT button

  5. Confirm that the data type selected for each attribute is correct, then select an attribute to be the dataset's Unique ID, and then click NEXT.

    If an attribute has the wrong data type associated with it, then the data can't be processed correctly when you use the dataset within the platform.

    Animated demonstration of a user ensuring that the data type is correct for each attribute, then selecting an attribute to be the dataset's 'Unique ID,' and then clicking the NEXT button

  6. Select or create an Identifier Name so that you can connect the dataset to one or more ID Collectors, and then click SAVE.

    An Identifier Name can contain only letters, numbers, and underscores.

    Animated demonstration of a user inputting a new 'Identifier Name' into the appropriate field and then clicking SAVE

  7. Click CONFIRM AND CREATE.

    Callout of the 'CONFIRM AND CREATE' button in the 'Create Dataset Schema' wizard

Engine API clients must take additional steps to make use of a Customer Attributes dataset, including sending the Identifier Name as a custom variable in a request. See Identifying Known Customers Included in a Customer Datasets in User Identity Persistence in Requests in the Monetate Developer Hub for more information.

After you click CONFIRM AND CREATE in the wizard, a message appears on the screen informing you that the file is uploading and then updates when the upload is complete.

The 'Upload Complete' message on the 'Upload Data' screen

You can click CLOSE to dismiss this message before the upload is complete. If you choose not to do that or if the upload completes quickly, this message can swiftly be replaced by the details page for the newly created dataset, with the Update History tab showing. The status is PENDING until the platform successfully completes processing the file or encounters an error.

The Update History tab of a Customer Attribute dataset's details page

Refer to Customer Attributes Dataset Details Page for more information about the Update History tab as well as the Attributes tab.

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