How to Standardize Job Titles in Salesforce

January 2026 · 8 min read

You want to see all VP-level contacts at your target accounts. You run a report filtering for "VP" in the title field. You get some results, but you're missing half of them.

Why? Because your database has "VP Sales", "Vice President of Sales", "VP, Sales", "Vice President - Sales", "Sales VP", and "V.P. Sales". They're all the same seniority level, but your filter only catches the ones with "VP" at the beginning.

This is the job title standardization problem. It breaks lead scoring, routing, reporting, and segmentation. Here's how to fix it.

Why Job Titles Are So Messy

Job title chaos comes from multiple sources:

No standard exists. Unlike countries (ISO codes) or currencies (USD, EUR), there's no universal list of job titles. Every company makes them up as they go.

Titles mean different things at different companies. A "Director" at a startup might be an individual contributor. A "Director" at a Fortune 500 company manages 50 people. Same title, completely different seniority.

People write their own titles. Web forms, business cards, LinkedIn profiles all have self-reported titles with inconsistent formatting.

Creative titles are trendy. "Growth Hacker", "Chief Happiness Officer", "Evangelist", "Ninja". These tell you nothing about function or seniority without translation.

International variations. "Geschäftsführer" (German), "Directeur Général" (French), "Gerente" (Spanish) all need to map to something in your system.

The Goal: Structured Title Data

You don't need to fix the raw title field. Keep that intact for reference. Instead, create structured fields that can be used in automations:

Field	Purpose	Example Values
Title (original)	What they call themselves	"VP of Revenue Operations"
Standardized_Title__c	Normalized version	"Vice President, Revenue Operations"
Seniority_Level__c	For scoring and routing	"VP"
Department__c	For segmentation	"Operations"
Function__c	Specific role type	"Revenue Operations"

With this structure, you can:

• Score leads based on seniority level
• Route leads based on department
• Report on contacts by function
• Segment campaigns by decision-maker level

Building Your Seniority Taxonomy

Start by defining your seniority levels. Here's a common framework that works for most B2B sales contexts:

Seniority Level	Title Patterns
C-Level	CEO, CFO, CTO, CRO, CMO, COO, Chief [X] Officer
President	President, SVP, EVP, Executive Vice President
VP	VP, Vice President, Global VP, Regional VP
Director	Director, Senior Director, Associate Director, Head of
Manager	Manager, Senior Manager, Team Lead
Individual Contributor	Analyst, Specialist, Coordinator, Associate
Intern/Entry	Intern, Trainee, Junior, Graduate

Building Your Department Taxonomy

Departments are more stable than seniority. Most B2B companies use some version of:

• Sales (Account Executive, SDR, Sales Manager, VP Sales)
• Marketing (Demand Gen, Content, Product Marketing, CMO)
• Operations (RevOps, Sales Ops, Marketing Ops, BizOps)
• Customer Success (CSM, Account Manager, Implementation)
• Product (Product Manager, Product Owner, CPO)
• Engineering (Developer, Engineer, CTO, Engineering Manager)
• Finance (CFO, Controller, Accounting, FP&A)
• HR/People (Recruiter, HRBP, Chief People Officer)
• Legal (General Counsel, Legal Ops, Compliance)
• IT (IT Manager, Sysadmin, CIO, Security)
• Executive (CEO, Founder, Owner, Partner)

Customize based on what matters for your targeting. If you sell to marketers, you might want sub-departments like "Demand Generation" vs "Brand Marketing".

The Mapping Process

Here's how to actually standardize your existing title data:

Step 1: Export and Analyze

Pull all unique job titles from your Salesforce database:

1. Create a report of all Contacts grouped by Title
2. Export to CSV
3. Sort by frequency (most common titles first)

You'll likely find that 100-200 unique titles cover 80% of your records. The long tail of weird one-off titles can be handled later.

Step 2: Create Mapping Rules

Build a mapping table that transforms raw titles into your structured fields. The logic follows a pattern:

If title CONTAINS "CEO" or "Chief Executive" → Seniority = "C-Level", Department = "Executive"

If title CONTAINS "VP" and title CONTAINS "Sales" → Seniority = "VP", Department = "Sales"

Start with the most specific rules and work toward general ones. Order matters: "VP of Sales Operations" should match "Operations" before it matches "Sales" if that's your intent.

Step 3: Handle Edge Cases

Some titles need manual review:

• Founder: Could be C-Level at a startup or an honorific at a large company
• Partner: C-Level equivalent at consulting/law/VC firms
• Principal: Senior IC at some companies, senior leader at others
• Owner: Could mean CEO or could mean franchise operator
• Consultant: External? Internal? Seniority unclear

For ambiguous titles, you may need additional context (company size, industry) to map correctly.

Step 4: Implement in Salesforce

You have several options for implementation:

Formula fields: Good for simple mappings. Limited by formula character limits and can't handle complex logic.

Flow (Process Builder replacement): Can handle complex IF/THEN logic and updates fields automatically when records are created or edited.

Apex triggers: Most flexible but requires development resources. Good for complex pattern matching.

External processing: Export, process in Python/Excel, reimport. Best for one-time cleanup of existing data.

For most companies, a combination works best: Flow for ongoing automation of new records, and a batch process (external or Apex) for cleaning existing data.

Example Mapping Rules

Here's a starter set of mapping rules you can adapt:

Pattern	Seniority	Department
CEO, Chief Executive	C-Level	Executive
CFO, Chief Financial	C-Level	Finance
CTO, Chief Technology, Chief Technical	C-Level	Engineering
CMO, Chief Marketing	C-Level	Marketing
CRO, Chief Revenue	C-Level	Sales
COO, Chief Operating	C-Level	Operations
VP + Sales	VP	Sales
VP + Marketing	VP	Marketing
VP + Revenue Operations, VP + RevOps	VP	Operations
Director + Sales	Director	Sales
SDR, Sales Development	Individual Contributor	Sales
Account Executive, AE	Individual Contributor	Sales

Expand this based on what you find in your actual data. Your database will have patterns specific to your industry and target market.

Maintaining Title Data Quality

Standardization isn't a one-time project. New records come in constantly, and they'll have the same messy titles.

Point-of-Entry Standardization

Set up automation to standardize titles as records are created:

• Salesforce Flow triggered on Contact/Lead creation
• Apply mapping rules to populate structured fields
• Flag records that can't be mapped for manual review

Quarterly Cleanup

Run a report of records with blank or unmapped structured fields:

• Records imported from external sources
• Records where the title was updated manually
• Records that hit edge cases in your mapping logic

Update your mapping rules as you encounter new patterns.

Monitor for Drift

Track the percentage of records with complete structured fields. If it starts dropping, you have a process gap somewhere (a new import source, a form that bypasses standardization, etc.).

Integration with Lead Scoring

The whole point of standardized titles is to use them in automation. Here's how to connect them to lead scoring:

Seniority-based scoring:

• C-Level: +25 points
• VP: +20 points
• Director: +15 points
• Manager: +10 points
• Individual Contributor: +5 points

Department-based scoring (adjust based on your ICP):

• Target department: +15 points
• Related department: +10 points
• Unrelated department: +0 points

These scores combine with account-level data (company size, industry, technology stack) for a complete picture.

When to Get Help

Job title standardization is tedious work. It's also foundational to everything else in your RevOps stack. Consider getting help if:

• Your database is large: 50,000+ contacts means thousands of unique titles to map
• You're international: Titles in multiple languages add complexity
• You lack Salesforce expertise: Building the automation requires Flow or Apex knowledge
• You need it done quickly: A migration or launch timeline doesn't allow for gradual cleanup

At Verum, job title standardization is part of our broader data cleaning services. We've built mapping tables that cover most B2B titles across industries and can handle the edge cases that simple pattern matching misses.