Importing data from a spreadsheet (CSV) file
The spreadsheet (CSV) file data source allows you import your customer/people and organization data from a CSV file to your Ortto account’s customer data platform (CDP).
CSV file prerequisites
This process assumes that you have a valid CSV format file whose first row of columns match* field names for people and organizations defined in your Ortto account’s CDP. Each "column" represents a set of vertical values down each line of the CSV file, delimited by the same number of commas from the start of each line.
Your CSV file does not need to contain every field defined in your CDP. Only a subset of fields is required for people data only as well as organizations and people.
If you are working with a spreadsheet file, then use your spreadsheet application to export each of the spreadsheet file’s relevant pages into individual CSV files, and upload each one of these CSV files separately to Ortto.
NOTE: The field names defined in the header row of your CSV file do not need to match those defined in your CDP. Ortto will automatically attempt to match these as part of the data import process. However, it is assumed that each column of data in your CSV file is valid for each field defined in the first row.
People only
A CSV file with People data only must meet the following criteria:
- At least one field matches the People unique identifier set under Settings > Customer data > Unique identifiers > People.
- The format of your date data must match the format set in your General settings.
If you are setting the Language field value for a person, the value must be an ISO code. For example, to set a person's language as English, use en
, or Spanish, use es
. You can also specify region-specific language values, e.g. en-gb
for British English. See the List of languages for a full list of the supported ISO language codes.
Organizations only
A CSV file with Organization data only must meet the following criteria:
- At least one field matches the Organization unique identifier set under Settings > Customer data > Unique identifiers > Organizations.
- The format of your date data must match the format set in your General settings.
Organizations and people
Importing data associated with People and Organizations must be accompanied by people who will be linked to these organizations.
A CSV file with People and Organization data must meet the following criteria:
- At least one field matches the People unique identifier set under Settings > Customer data > Unique identifiers > People.
- At least one field matches the Organization unique identifier set under Settings > Customer data > Unique identifiers > Organizations.
- To link multiple People to a single Organization in your CSV file, specify the same Organization's unique identifier value for each linked person.
EX: If the Organization's unique identifier is Name, we can format the CSV as follows:
Name, Email My Company, chris@example.com My Company, alex@example.com
Since the unique identifier for the Organization matches on both contacts, they will both be linked to the same Organization (My Company).
Upload your spreadsheet (CSV) file
Assuming you initially followed the Configuring a new data source procedure, use this procedure to complete importing and integrating your CSV file’s data into your Ortto account’s CDP.
After having clicked through Popular / CRM Spreadsheet import Get started (from the New data source page), on the Upload spreadsheet page, drag and drop your CSV file into the dashed rectangular area of this page. Alternatively, click the or browse for the file on your computer link in the center of the page to browse for your CSV file to upload to Ortto. Click Next to open the Map the columns to a field page. On this page, Ortto attempts to match the columns defined in the header of your CSV file to field names defined in your CDP. If matches are found, then Ortto automatically applies the appropriate fields defined in your CDP to the field names defined in your CSV file’s header, indicated in the Spreadsheet columns section of the page.3. If any of these field name matches are incorrect, then drag the appropriate field defined in your Ortto account from the CDP fields section of the page over the field name defined in your CSV file’s head in the Spreadsheet columns section. The existing mismatched CDP field is replaced with your new choice, and the old CDP field moves back to the CDP fields section.TIP: If the list of CDP fields is too long, you can search and filter this list. At this point, you can also add a new CDP field, if any of the existing CDP fields are not suitable.
Click Next. On the Tag page, click Add tag to begin adding a new tag (by typing its text and clicking Create to create the new tag) or selecting one from the existing list of tags. Similar to searching existing CDP fields in the previous step, if the list of existing tags is extensive, you can filter this list itself by typing one or more consecutive letters into the Type to search box.TIP: Tags are useful for filtering and grouping people and organizations (each being a record) within your CDP. For example, you can utilize tags to help move your CDP records from one playbook to another, control which CDP records enter a playbook, group CDP records created or updated from different CSV file imports, and so on. Note that an existing tag consisting of the name of your CSV file, as well as the date and time of import is automatically applied to all people and organizations data imported into your Ortto account through this CSV file.
Click Next. On the Select a merge option page, choose the appropriate merge option and merge key strategy to determine how Ortto behaves when integrating any existing people or organization data in your CSV file into Ortto. Learn more about the merge options. Click Done to start the import. Once the import process starts and your CSV data is initially uploaded, then synced, and completed when Import complete is shown, click Done again (or X at the top) to return to the Data sources page.NOTE: If your CSV file is large and the syncing process takes a while, you can click Done again (or X at the top) from when the syncing process beings to return to the Data sources page. Syncing will complete in the background and Ortto notifies you of when the import is completed.
Merge options
Import and merge new data only (recommended)
When a record exists only new data will be added. If the record doesn't already exist, it will be created.
EX: Consider an existing contact with the following fields:
First Name: John Last Name: Perez Country: MexicoIf you map any columns from your CSV file to these fields, the existing values will remain unchanged. For instance, if your CSV includes:
First Name: (new value) Last Name: (new value) Country: (new value)Ortto will not update John's first name or last name, and the country will remain as Mexico. By selecting this option, you can only populate fields that are currently empty. This allows you to update your contact data without risking the loss of existing information.
Import and merge new data for existing records only
This option allows you to add new data only to existing records. If a record is found, only new data will be merged based on the mappings provided (see the example above for details on how data is updated).
The key distinction between this option and the previous one is that it does not create new records. If a record cannot be matched using your unique identifiers, it will be ignored during the import process.
Import and overwrite any data that exists
When a record exists all mapped fields will be overwritten. If the record doesn't already exist, it will be created.
WARNING: Exercise caution when using this option, as all mapped fields will overwrite existing data. If you're unsure whether this is the best option for your needs, we recommend exporting all your contact data before proceeding with this import option. This way, you'll have a backup of your data in case you need to restore it. Learn more about how to export records.
EX: With this option, all mapped fields will overwrite any existing data in your records. For example, consider an existing contact with the following fields:
First Name: Sarah Last Name: Johnson Country: CanadaIf you map any columns from your CSV file to these fields during the import process, the existing values will be replaced.
Any fields that you map on the mapping page will completely overwrite the existing data in the contact profile.
There are two scenarios where existing values will not be updated during the import process (this applies regardless of the merge option you've selected):
The field in the CSV file is empty: If the corresponding field in your CSV file is empty and you map it to a field that already has a value, the existing value will remain unchanged. In this case, the field will not be overwritten and will not become empty. The field in the CSV file was not mapped: If you choose not to map certain fields from your CSV file, those fields will not be updated in Ortto. Only the fields that you map will be considered during the import.Import and overwrite any data that exists for existing records only
This option allows you to overwrite any data only for existing records. If a record is found, data will be overwritten based on the mappings provided (see the example above for details on how data is updated).
The key distinction between this option and the previous one is that it does not create new records. If a record cannot be matched using your unique identifiers, it will be ignored during the import process.
Import new records only
If a record already exists, it won’t be modified. This option only imports new records.
Searching existing CDP fields
If the list of CDP fields is extensive, you can filter this list itself by typing one or more consecutive letters into the Search box, and any of these fields whose names do not match these letters are dynamically excluded from the list as you type.
You can then select and/or clear the remaining CDP fields on this list.
Clearing the Search box, or clicking X restores all CDP fields to the list.
Adding a new CDP field
If your Ortto account’s existing CDP fields are not suitable for one or more columns of data in the CSV file you are importing, you can create a new CDP field to map to your CSV file column.
To do so:
Click Add a new field. In the New custom field dialog, specify the Field name and Field type for your new CDP field. Click OK and the new CDP field appears at the top of the CDP fields section list. You can now drag this field across to the appropriate CSV file column in the Spreadsheet columns section of the page.Adding contacts into an audience
Contacts enter an audience based on the audience's entry conditions.
If an entire CSV of contacts needs to enter a specific audience, one option for doing so is to use a tag.
To do so:
Update the audience's People enter when: settings to include the "Tag is [Tag-Name]" condition, replacing the placeholder value with the tag that you'd like to use. During your import, apply that tag to the contacts in the Tag step of the import.This will allow all of the contacts in the CSV file to meet the audience's entry condition for the tag once the import has completed.
Troubleshooting CSV file imports
Too many rows without merge keys
If you receive an error saying "Too many rows without merge keys", this means that Ortto cannot find in the CSV file enough data matching your account’s unique identifiers to be able to create or update records in your CDP.
To be able to create meaningful CDP records, Ortto requires the following minimum fields:
- For people: First name, Last name, and Email address.
- For organizations: Name (of the organization), as well as either the Email address or Phone number of the person being linked to this organization.
By default, Ortto uses the following data values as unique identifiers:
- For people: their email address, followed by their phone number (as a fallback), and
- For organizations: its name.
You can modify the default identifiers under Settings > Customer data > Unique identifiers.
As such, the likely issue causing the error is that your CSV file is missing identifier data, e.g. people’s email addresses. When you’ve updated your CSV file to include the missing data, this should resolve the issue and allow you to complete the import.