Data Sources

The data source page is connected to the settings of data structure and data mapping. Simply, to process any data through our platform (and to send the questionnaires), a strict data structure needs to be set on your side and mapped in the Staffino platform. 



Let’s navigate you through the Data sources page now. Starting from the top, you can see the number of created data sources as the first thing.

The list of all data sources (the main table) consists of the following information: 


• Name: The name usually represents the campaign the data structure is connected to (name of the team, structure entity, product, etc.). If many data sources are created, feel free to use the search bar to find the data source you need based on its name. 

• Type: Based on the data exchange type: Manual/email/SFTP/API. More information about data source types can be found here.
• Mapped Columns: Number of columns (attributes) used in the data source.

• Last edited: Date of the last edit of the data source.
You can sort the list based on any of the parameters above.

You can proceed following changes on this page:*


• Create new Data source(s)
• Adjust existing Data source(s)
• Duplicate existing Data source(s)

• Delete existing Data source(s)

• Restore deleted Data source(s)

*Find out more about specific settings by clicking the section name.

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Choosing a data source

Currently, Staffino allows you to create two types of data sources:

1. Requested feedback: Feedback requests are sent to specific customers through defined channels (end-to-end process managed within Staffino).
2. Imported feedback: Feedback collected outside of Staffino is imported into the platform, without sending any requests (external feedback made visible in the platform).

Regardless of which option you choose, the process for creating, deleting, adjusting, and restoring a data source is the same.

You can access these options by clicking the “+ Create data source” button.

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Creating a data source

The first step, even before creating a new data source in the Staffino platform, is to know the final structure of the data you will import. Once the structure is final, you can start setting up the data source by visiting the “Data sources” in Settings and clicking on the “+ Create data source” button.

A new window pops up, where you select the Data source type. Each data source type requires a different set of information, like log-in credentials for the SFTP option or an API end-point for the API option. More information about data source types can be found here. Once you select the data exchange type, name your data source. The name usually represents the campaign the data structure is connected to (name of the team, structure entity, product, etc.). Press the “Continue” button afterwards.

Another window pops up, where you start mapping the columns of the data you prepare with our platform. The name of the data source is always visible at the top of the box, so you always know which type of data you are mapping at the moment. The first column is already there, and all you need to do is choose the correct information/attribute from the dropdown.

Some of the attributes are predefined, but you can create your own as well. The library of predefined attributes can be found here, and a step-by-step guide on how to create a new attribute is described in Creating an attribute section. Every time you need to add a new column to your data source, the option “+ Add Column” option is here for you.

Once you set all the columns, we highly recommend using the “Upload sample” option. Thanks to this, you can upload an exemplary xls file with some “dummy” testing data that matches the column structure you just built. A header and one or two rows of data are completely enough. This can help you or your other colleagues with data source adjustment in the future. If all of the above is done, use the option “Save” to save your new data source or the option “Cancel” to discard all settings and start all over again.

Now when we successfully created a new data source, let’s get it into use by setting up the Campaign triggers.

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Adjusting data source

When it comes to changes within Data sources, you can change the following:

Name of the data source
This is done by clicking on the “context menu (three dots)” placed at the end of the row of the data source that you want to adjust and choosing the “Rename” option.

Another way is by clicking on the row where the data source is placed and choosing the “Rename” option in the “context menu (three dots)” situated in the top right corner.

In both cases, a new window appears where you can simply rewrite the original name with a new one. Don’t forget to confirm the rewrite via the “Save” button.

Columns adjustments
This is done by clicking on the “context menu (three dots)” placed at the end of the row of the data source that you want to adjust and choosing the “Edit” option.

A new window appears where you can simply:
– delete columns by clicking on the “X” option
– add new columns with new attributes by choosing the “+Add Column” option
– replace the existing attribute with a new one by clicking on the existing attribute and choosing a new one from the dropdown/creating a new attribute

The library of predefined attributes can be found here, and a step-by-step guide on how to create a new attribute is described in Creating an attribute section.

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Duplicating a data source

If you need to create the same Data source as one which is already in use, or you need to create a similar one, feel free to use the “Duplicate” option. This can be done in three different ways:

1. By clicking on the “context menu (three dots)” placed at the end of the row of the data source that you want to duplicate and choose the “Duplicate” option.

2. By checking the check box placed at the beginning of the row of the data source you want to duplicate and choosing the option “Duplicate” from the “Actions” dropdown. This option is better when you’d like to duplicate more than one data source at once.

3. By clicking on the row where the data source is placed and choosing the “Duplicate” option in the “context menu (three dots)” situated in the top right corner.

If you need to adjust the duplicated data source, visit the section Adjusting a data source for more info. And now, when we successfully duplicated (and adjusted) a data source, let’s get it into use by setting up the Campaign triggers.

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Deleting a data source

Deleting a Data source is a simple process that can be done in three different ways:

1. By clicking on the “context menu (three dots)” placed at the end of the row of the data source that you want to delete and choose the “Delete” option.

2. By checking the check box placed at the beginning of the row of the data source you want to delete and choosing the option “Delete” from the “Actions” dropdown. This option is better when you’d like to delete more than one data source at once.

3. By clicking on the row where the data source is placed and choosing the “Delete” option in the “context menu (three dots)” situated in the top right corner.

⚠️ Please note once you delete a data source that was used in the currently running campaign, it is also removed from a Campaign trigger. Therefore, no imports will be processed successfully until a new data source is added to the Campaign trigger.

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Restoring a data source

If you deleted any data source by mistake, you can simply restore it.

First, you need to open the Data Sources part of Settings.

Once there, click on the “Restore” option placed in the top right corner.

You’ll be redirected to a new page where all deleted data sources from your organisation are located with the following information:

• the name of the data source
• the data source type (data exchange type)
• the number of columns mapped
• date of data source creation
• date of data source removal

You can sort the list based on any of the parameters above.

If you want to restore just one specific data source, hover over the row it is placed in and click on the “context menu (three dots)” option. Choose the “Restore” option from the dropdown. Confirm your action in the pop-up window, and your data source will be restored! If you want to restore more data sources at once, use the checkbox to select more rows. Click on the “Action” button afterwards and restore all selected data sources. Once you confirm the action, all data sources will be restored.

Now that we have successfully restored a data source, let’s get it back into use by setting up the Campaign triggers. You can delete restored data sources anytime.

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Data source types

There are 4 types of data sources based on the data exchange type we want to use for a specific campaign.

1. Manual – used for manual importing directly through the Staffino platform via any user. No specific information is needed for this type; you just map the columns based on the data structure created.

2. Email – used for data exchange via email. A unique email address is generated for each new data source, and you can simply copy it via the “Copy address” button. For more secure data processing, check the “only valid senders” checkbox, so only emails sent from required email addresses will be considered valid. A new input field pops up where you put all required email addresses, divided by a comma. Emails with the same data structure but from different email addresses won’t be processed.

3. SFTP – used for files uploaded on the FTP server. Host, Port, Username and Password information will be provided by us during the general/initial setup together with the Protocol. All you need to do is to fill this information into the input fields and start with column mapping.

4. API – used for real-time API connection. The API endpoint is provided for your internal setup. Usually, the API is set during the general/initial setup, so no specific information is needed for this type; you just map the columns based on the data structure created.

⚠️ Please note this section is connected to the data source type explanation more from the set-up and data source adjustments point of view.

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Predefined attributes library

While creating a data source or adjusting the existing one, you can map some predefined attributes or create your own attributes.

Here is the list of all predefined attributes with a brief explanation (of not self-explanatory attributes).

CUSTOMER

• Customer reference
• Customer phone
• Customer email
• Customer salutation (mainly used for templates/flows)
• Customer name
• Customer first name
• Customer last name
• Customer gender (also handy for correct declension in inflected languages)
• Customer language (if templates/flows are prepared in more languages)
• Customer country

⚠️ Please note that the customer gender attribute must follow a predefined format. Accepted values are: M or m for male, F or f for female. With different variations, the data row won’t be processed.
The customer language attribute must be provided in lowercase using the standard two-letter language codes. Examples include: cs for Czech, en for English, etc. With different variations, the data row won’t be processed.

If you are unsure about the correct language codes or if you’d like to double-check that your data meets the attribute format requirements, don’t hesitate to get in touch with our team.

EMPLOYEE

• Employee reference
• Employee first name
• Employee last name
• Employee email

OTHER

• Venue reference
• Interaction source

⚠️ Please note employee or venue reference and customer phone or customer email are mandatory attributes/columns that need to be added to any data source. Without this information, we cannot reach out to a client or assign feedback to any employee or team.

Other than these, you can create up to 30 customer and 30 interaction attributes. Mapped attributes can be used for feedback categorisation, post-data analysis, or as Placeholders in templates and flows.

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Creating a custom attribute

Keep in mind that Staffino offers some predefined attributes when creating or adjusting the data source. You can find the library of predefined attributes here. These predefined attributes can save you some time from not creating duplicates of already existing attributes. If you want to create a new custom attribute through data source directly, please follow these steps:

1. Choose the “+Assign New Attribute” option placed at the end of the column dropdown.

2. Name the new attribute in the window that popped up.

3. Select the attribute type:
Interaction Attribute: connected to the interaction/transaction (call length, order value, products purchased, etc.).
Customer Attribute: all parameters connected to the customer (age, loyalty card owner, etc.).

4. (Optional) Add translations You are always setting up the attribute name in the default language set for your organisation. If you use more languages within the platform (flows, templates, etc.), use the “blocks A” icon to add translations.

5. Use the “Save” button to confirm the custom attribute creation.

⚠️ Please note that a newly created attribute is not automatically added/mapped to a column you created the attribute through. To map the custom attribute to a column, you need to choose it from the specific column dropdown afterwards.

All custom attributes can be found and edited in the Settings category called “Attributes“. You can also use this section to create all new attributes, following steps 1 – 5 mentioned above and adding them to the data source afterwards as already existing attributes.

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Generating an API Key

To use the API for data exchange, you must first generate an API key. Click the “Generate API Key” button located in the top-right corner of the Data Source section within platform Settings.

As the warning message indicates, for security reasons, the API key is displayed only once. If you lose it, you’ll need to generate a new one.

To confirm and save the key, click “Copy”. If you choose “Close”, the key will not be saved, and the action will be cancelled.

For further instructions on how to use the API, please refer to our external API documentation.