Best Practices

Before you begin preparing your data, it's important to become familiar with a few general Best Practices when it comes to preparing your file for import. These Best Practices guide you in learning basic data treatment along with the steps necessary to verify and validate your import. This section includes valuable information for:


Best Practices


  • Headers are the first row in a .csv file is called the header with each column listing the field names for the object that you are processing. Each subsequent row corresponds to a separate contact record in Clockwork. If a column header is included in a source file that does not conform to the import process standards, that column is ignored.  You can either leave or delete columns you will not use. Blank columns will be skipped.
  • Unknown Column Headers are skipped. If a column header is not recognized by the import process, it is skipped and the data within that column will not be loaded.


  • The Name field is the only field that is required to process an import file into Clockwork. The First Name, Middle Name, Last Name fields are concatenated (condensed) together into a single name string during the import process.  
  • Column Order does not matter, as long as there is a First Name/Last Name field, the rest of the columns can be in any order.
  • Blank Values are skipped. If you include a column header and no data within the column, the data will be skipped.
  • Notes and Tags can be imported for more advanced imports. Consider splitting this information into a separate data load, which would include the contact name, email, and the note or tags, as this type of information is generally responsible for most of the import errors that are experienced.
  • Special Characters to Avoid: It's important that you search/replace double quotes (") with single quotes (').


  • Duplicate Data should be avoided. Clockwork automatically merges data based on LinkedIn URL or email address only. This means that if your import data does not have an email address or LinkedIn URL, a new contact record will be created and will NOT auto-merge if that person already exists in your database. You may reference this article for Removing Duplicate Data to help ensure you avoid this problem.
  • Junk Data should be cleaned up before importing. This is advice more than a rule, but keep in mind that there is little benefit to having 10,000 (or any large number) people in your contact database with little contact information (we refer to these as “sparse” contact records).  In the long run, it will be much better for you and your firm if you load smaller groups of well-formed (dense) contact records that you can leverage.
  • Double-check your data to make sure you will import correct and well-formed contact records only. There is no backing out data that is loaded. be very careful what you import, as deleting malformed contacts can be difficult (there is no bulk delete option).
  • Test your file before importing. Do do this, take a small sample file (i.e. < 5 rows worth of data) and test the import using this sample data first.  This will allow you to identify any structural problems with the full dataset.  It is much easier to delete a few contacts at the outset than to manage thousands of contacts that are entered incorrectly.
  • Multiple files are better than one single file. Consider breaking up your source dataset into discrete groups of contacts (based on some relevant criteria).  You can always access the list of people that were imported from a specific file at a later date – this gives you an additional way of slicing/dicing the data in the future (and adding tags!).


Next Steps

Now that you have reviewed our Best Practices, choose an Import Guide from the list below depending on the complexity of your dataset. 

  • Basic Import - This simple import guide is great for preparing basic contact information that has been exported from Gmail, Outlook, and the like. Use this guide for a straightforward import of information such as name, a single email address, a single phone number and a single position (title and company).
  • Advanced Import - This more advanced import guide is great for preparing more in-depth contact information. If you are more confident with data import and are working with files that include data beyond basic contact information, you will want to use this guide. It will help you prepare more complex and in-depth information such as :  multiple positions, education, tags, and notes.
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