How to Decide Which Salesforce Fields Should Be Required

If you work in RevOps, SalesOps, or an operations role, one of the most important decisions you make in Salesforce is this:

Which fields should be required… and which should be optional?

Get this wrong and everything starts to break:

• Leadership stops trusting dashboards
• Reps see Salesforce as busy work
• Automation fails
• Forecasting becomes unreliable

But when it’s done correctly, Salesforce becomes a reliable decision engine for the business.

This guide walks through the simple framework we use with tech companies scaling from $3M to $100M ARR to audit and clean up Salesforce fields.

You can run this exercise yourself in a few hours.

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Why Required Fields Matter

Salesforce data only works if the right information is consistently collected.

Without that, you can’t:

• Qualify your ideal customers
• Forecast pipeline accurately
• Automate workflows
• Build trustworthy reports

Instead, you get the classic signs of a messy system:

Leadership problem

Executives look at a dashboard and immediately say:

“I don’t think those numbers are right.”

Rep problem

Sales and marketing teams start viewing Salesforce as administrative busy work.

They stop filling out fields.

Team alignment problem

Different departments define the same process differently.

Marketing thinks a lead is qualified.
Sales disagrees.
Support tracks something else entirely.

This is where required fields bring structure.

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Step 1: Audit Your Salesforce Fields With Data

The first mistake operators make is asking people what they use.

Sales reps will often say they fill out fields even when they don’t.

Instead, start with data.

Use tools that show you how often fields are actually populated.

Two ways to do this

Option 1 — Salesforce Field Usage

Salesforce includes a built-in feature that shows:

• All fields on an object
• The percentage of records where the field is filled

Option 2 — Field Trip

Field Trip is a popular tool that provides the same analysis with easier visualization.

You’ll quickly see:

• Fields filled out 90–100% of the time
• Fields filled out 1–5% of the time
• Fields nobody ever uses

Those numbers tell you where to start cleaning.

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Step 2: Decide What Should Be Required

Not every field should be mandatory.

A good rule:

If a field doesn’t drive a decision, workflow, or metric, it probably shouldn’t be required.

Fields should be required if they help:

1. Qualify opportunities

Example:

• Industry
• Company size
• ARR

These help determine if a prospect fits your ICP (ideal customer profile).

2. Execute a process

Example:

• Sales stage progression
• Lead routing
• Proposal creation

Required fields make sure processes run correctly.

3. Support critical metrics

These fields power leadership dashboards like:

• ARR
• CAC
• Churn
• Lifetime value
• Pipeline forecasting

If leadership relies on the metric, the field must be reliable.

4. Legal or compliance needs

Sometimes data must be collected for:

• Finance
• Contracts
• Regulatory compliance

These should always be enforced.

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What Should Stay Optional?

Optional fields usually fall into these categories:

• Nice-to-have context
• Rare edge cases
• Fields not tied to reporting or workflows

For example:

• Additional notes
• Non-critical enrichment data
• Internal comments

Making too many fields required is one of the fastest ways to destroy Salesforce adoption.

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Step 3: Enforce Fields the Right Way

There are two main ways to enforce required fields.

Option 1: Required Fields on Page Layouts

This forces a field to be completed any time a record is created or edited.

Example:

A contact must always include a first name.

This method works best for fields that are always known immediately.

Option 2: Validation Rules

Validation rules enforce fields at specific stages in a process.

Example:

You might require:

• ARR
• Industry
• Deal value

before an opportunity can move to Proposal stage.

Or require compliance data before marking a deal Closed Won.

This approach prevents frustrating reps by asking for data too early.

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Step 4: Fix Duplicate Fields

As you audit Salesforce, you’ll likely find duplicates like:

• ARR
• Annual Recurring Revenue

This happens when multiple people have permission to create fields.

Duplicates cause major problems:

• Broken reports
• Confusing dashboards
• Data stored in multiple places

How to fix duplicates

1. Choose one field as the official version
2. Migrate data from the duplicate
3. Update reports and automations
4. Delete the duplicate

Also consider limiting who can create new fields.

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Step 5: Make Sure Deleting Fields Won’t Break Anything

Before removing a field, check whether it’s used in:

• Reports
• Dashboards
• Page layouts
• Validation rules
• Flows and automations
• Integrations (HubSpot, Marketo, etc.)

Salesforce’s “Where Is This Used?” feature helps with this.

Some teams also use tools like Salto to visualize dependencies across the system.

This prevents accidentally breaking automations.

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Step 6: Run This Process Object by Object

Don’t try to clean everything at once.

Start with the areas that affect revenue most.

Typically:

1. Leads
2. Contacts
3. Accounts
4. Opportunities
5. Cases

Pull the field usage data, identify unused fields, and clean each object step by step.

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Step 7: Align the Right Teams

When finalizing changes, include stakeholders from:

• Sales
• Marketing
• Operations
• Leadership

But keep meetings small.

A good structure is:

• One rep using the system daily
• One manager
• One decision-maker

Present your recommendations instead of asking open-ended questions.

This avoids long debates.

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What Success Looks Like

When Salesforce fields are cleaned up correctly:

Reps

• Spend less time filling out forms
• See Salesforce as useful, not busy work

Operators

• Trust the data in reports
• Can identify pipeline bottlenecks

Leadership

• Finally trusts dashboards
• Makes faster decisions

Instead of arguing about numbers, teams can focus on improving the business.

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Final Thought

Cleaning up Salesforce fields might sound simple.

But it’s one of the highest leverage exercises an operator can run.

Fewer fields.
Higher completion rates.
Better data.

And most importantly:

Reliable insights that help the company grow.

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2 Ways We Can Help:

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