New: AI-Powered Job Title Normalization in Smart Agents

We've added AI-powered job title normalization to Smart Agents. Now you can automatically standardize messy job titles across your entire database - no manual cleanup required.

The Problem

Job titles in CRM data are notoriously inconsistent. The same role might appear as:

• VP Sales
• VP of Sales
• Vice President Sales
• Vice President of Sales
• Vice President, Sales
• VP - Sales
• V.P. Sales

Multiply this across thousands of contacts, and you have a segmentation nightmare. Your "VP-level" segment misses half the VPs because their titles don't match your filters.

Lead scoring breaks. Routing rules fail. Campaign targeting gets messy.

The Solution

Smart Agents now uses AI to understand job titles semantically, not just match strings.

How it works

1. Upload or connect your data
2. Select the job title column
3. Choose "Normalize Job Titles"
4. AI analyzes each title's meaning
5. Output: Standardized titles in your preferred format

What the AI understands

The model recognizes:

Seniority levels:

• C-Suite (CEO, CTO, CFO, etc.)
• VP/Vice President
• Director
• Manager
• Individual Contributor

Departments:

• Sales
• Marketing
• Engineering
• Finance
• Operations
• Human Resources
• Product

Role variations:

• "Head of Growth" → VP Marketing
• "Revenue Leader" → VP Sales
• "Full-Stack Dev" → Software Engineer
• "People Operations" → HR Manager

Customizable output

Choose your normalization format:

Option 1: Title Case Standard

• Input: "vp sales"
• Output: "Vice President of Sales"

Option 2: Abbreviated

• Input: "Vice President of Sales"
• Output: "VP Sales"

Option 3: With Department Extraction

• Input: "vp sales"
• Output: Title: "Vice President", Department: "Sales"

Option 4: Seniority Extraction

• Input: "Senior Director of Marketing"
• Output: Title: "Senior Director of Marketing", Seniority: "Director"

Use Cases

Better lead scoring

Before: Your scoring model gives +10 points for "VP" in title. "Vice President of Sales" gets 0 points because the string "VP" isn't present.

After: All VP-equivalent titles normalize to a standard format. Scoring works consistently.

Accurate segmentation

Before: Campaign targeting "Directors and above" requires listing every possible title variation.

After: Normalized seniority field lets you filter simply: Seniority = Director OR Seniority = VP OR Seniority = C-Suite.

Clean reporting

Before: "Contacts by Title" report shows 500 unique titles, most being variations of the same role.

After: Normalized titles consolidate variations. Report shows 30 meaningful role categories.

ICP matching

Use normalized titles with ICP Scoring:

• Target: "Director or VP of Sales/Marketing"
• Match: Any title that normalizes to those criteria

How to Use It

In the Cleanlist dashboard

1. Go to Smart Agents
2. Select your dataset
3. Click Add Transformation
4. Choose Normalize Job Titles
5. Select your output format
6. Run transformation

Via API

POST /api/v1/transform
{
  "data": [
    {"title": "vp sales"},
    {"title": "Vice President, Marketing"},
    {"title": "head of growth"}
  ],
  "transformations": [
    {
      "type": "normalize_job_title",
      "input_field": "title",
      "output_field": "normalized_title",
      "extract_seniority": true,
      "extract_department": true
    }
  ]
}

Response:

{
  "data": [
    {
      "title": "vp sales",
      "normalized_title": "Vice President of Sales",
      "seniority": "VP",
      "department": "Sales"
    },
    {
      "title": "Vice President, Marketing",
      "normalized_title": "Vice President of Marketing",
      "seniority": "VP",
      "department": "Marketing"
    },
    {
      "title": "head of growth",
      "normalized_title": "Vice President of Marketing",
      "seniority": "VP",
      "department": "Marketing"
    }
  ]
}

In CRM workflows

Set up automatic normalization:

1. Connect Cleanlist to HubSpot/Salesforce
2. Create workflow: "When new contact created"
3. Action: Normalize job title via Cleanlist
4. Update: Write normalized title to custom field

New contacts get normalized titles automatically.

What's Included

Job title normalization is included with Smart Agents - no additional cost.

Smart Agents features:

• Job title normalization (new)
• Name parsing (first/last)
• Phone number formatting
• Industry categorization
• Company name cleanup
• Custom AI transformations

All available on any Cleanlist plan.

Coming Soon

We're expanding Smart Agents with:

• Industry normalization: Map free-text industries to standard categories
• Location standardization: Normalize country, state, city formats
• Company name matching: Identify company variations (Acme Corp = Acme Corporation)
• Custom AI prompts: "Categorize these titles by seniority using our custom framework"

Get Started

Try job title normalization now:

1. Log into Cleanlist
2. Upload a sample file with job titles
3. Run the normalization transformation
4. See standardized output

Questions? Reach out to support@cleanlist.ai.

Messy job titles shouldn't break your targeting and scoring. Let AI handle the normalization while you focus on selling. Try Smart Agents today.