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Salesforce ‘s Data Import Wizard doesn’t clearly distinguish between required and optional contact fields until import failure occurs, making it difficult to create efficient templates.
Here’s how to identify true field requirements upfront and design templates that match your actual data availability.
Identify true field requirements with upfront visibility using Coefficient
Coefficient provides upfront visibility into field requirements, letting you see which contact fields are truly required versus organizationally preferred before designing your import templates.
How to make it work
Step 1. Browse complete Contact object schema with field property details.
Connect to Salesforce through Coefficient and examine the Contact object properties. You’ll see that LastName is the only universally required field for standard Contact objects.
Step 2. Identify organization-specific required fields set through validation rules.
Look beyond standard requirements to understand fields that your organization has made required through validation rules or business processes. These might include Email, Phone, or custom fields specific to your business.
Step 3. Understand conditional requirements based on record types or processes.
Some fields become required based on record type or business process triggers. Use Coefficient’s field browser to understand these conditional requirements for your specific use case.
Step 4. Design templates around actual vs perceived requirements.
Create different template versions: minimal templates for incomplete data sources (LastName only), recommended templates (LastName, FirstName, Email, Phone), and comprehensive templates when full data is available.
Step 5. Test different field combinations through preview functionality.
Use Coefficient’s preview feature to validate that your template design works with your actual data completeness. This prevents over-engineering templates with unnecessary fields.
Step 6. Build conditional logic to handle varying field availability.
Create formulas that adapt to different data completeness scenarios. For example, use fallback values for organizationally-required fields when source data is incomplete.
Build templates that match your data reality
This approach prevents over-engineering contact import templates with unnecessary fields while ensuring all truly required fields are properly addressed for successful imports. Start building efficient contact import templates.
