Data Cleansing tips
Having clean data is key to a successful Import. By taking the time to ensure the integrity of the data upfront will accelerate implementation time, avoid rework, and obtain accurate and actionable business information. Follow these steps to prepare data for import:
- Create a data mapping document for reference. This document will help define which columns should map to which fields within the CRM and if the fields should be mapped to Individuals and/or Organisations.
- Create all necessary contact and custom categories and fields within Salpo CRM.
- Create a Contact data file. The data file must be in .csv format.
- Each column of data should have a header that describes its contents (e.g. name, email, address, etc).
- Create a separate column next to any contact details fields to act as a label field (e.g. mobile, office, home, personal). This helps differentiate between a home phone number and office phone number when viewing the data within the CRM.
- Ensure all data is correctly placed under the appropriate column header. Data in an incorrect column will be imported into an incorrect field or throw an error and not import.
- Ensure all data is formatted correctly.
To search for businesses and export email addresses associated with people who work at those businesses within the CRM:
- Duplicate the email column in the spreadsheet.
- Create a matching custom field in Salpo CRM.
- Map the created custom field against the business and link the duplicate email column to it.
** Custom field values in the .csv file must be in the same format as the custom field in Salpo CRM (i.e. date formats 01/01/2001 must match and text values must matching exactly).