Client Data Preparation Guide

Purpose
Providing clean, complete, and well-structured data is one of the most important factors in a successful CRM implementation. This guide explains what is expected when preparing data for a migration into HubSpot, why it matters, and how your project team can help throughout the process.

Client Responsibilities
Your team is responsible for:

• Determining what data is in scope for migration
• Reviewing and cleansing data before submission
• Providing data in the agreed format and by the agreed dates
• Confirming the accuracy and completeness of the supplied data
• Reviewing and approving migrated data during User Acceptance Testing (UAT)

Data Submission
To help keep your data secure, we'll provide a dedicated Google Drive folder for uploading your migration data. This folder is separate from the main project workspace to ensure access is limited to only the project team members who require it. Once your files have been uploaded, simply let your Project Manager know.

File Formatting
How to structure and format your data files:

• CSV (.csv) or Excel (.xlsx) files preferred
• One file per data type (e.g. Contacts, Companies, Deals, Tickets)
• One field per column
• Clear column headers
• Provide ALL data where possible, not a subset
• Note: we can remove records easily when imported into HubSpot, but it makes validation hard when a subset is provided
• Do not merge cells, use filters, or apply formatting that alters the data structure

Best Practice Checklist
Before submitting your data, we recommend reviewing the following:

• Include a unique identifier (UID) for each row to support matching and validation during migration
• Identify relationships between records by including the UIDs of related records
• Remove duplicate records where possible. In HubSpot, contacts with the same email address are considered duplicates and should be reviewed before migration
• Validate email addresses and remove invalid or test accounts
• Split fields into separate columns where possible (e.g. Name into First Name and Last Name, Address into Street Address, Suburb, State/Region, Postcode, and Country, etc.)
• Standardise picklist values (e.g. Industry, Country, State, Lifecycle Stage, Role, Company Type, etc.)
• Format phone numbers consistently (recommended: E.164 format)
• Standardise date fields are provided in a consistent format throughout the file:
  • Date only: DD/MM/YYYY or YYYY-MM-DD
  • Date & Time: DD/MM/YYYY HH:MM:SS or YYYY-MM-DD HH:MM:SS
• Provide the Create Date and Last Modified Date for each record, if available from your source system
• Record owners have been assigned
• Data has been reviewed and approved by the business