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Job Title Normalizer

Paste a list of raw job titles and get back normalised, standardised versions — perfect for segmenting lists or building ICP filters.

Clean messy titles for better targeting

If you've ever tried to segment a list of 5,000 prospects by seniority, you know the pain. "Sr. Account Executive – EMEA", "Senior AE", "Account Executive (Senior)", and "AE III" should all be the same segment — but they're not, until you normalise them.

The problem with raw title data

Job title data from LinkedIn, ZoomInfo, Apollo, or your CRM is always messy. Companies invent their own title conventions, add regional qualifiers, seniority levels, and team names that make segmentation nearly impossible without normalisation.

How normalisation works

Paste your raw titles into the tool and we map each one to a standardised format: function (Sales, Engineering, Marketing), seniority tier (IC, Manager, Director, VP, C-Suite), and department. The output is a clean two-column table you can paste straight into your CRM.

ICP filtering that actually works

Once your titles are normalised, you can build precise ICP filters: "all Director+ in Sales at companies 100–500 employees." Without normalisation, you'd miss half your market or include too much noise.

Automated inside WaffleIQ

WaffleIQ normalises job titles automatically as contacts enter your pipeline. No manual clean-up, no missed segments. Your targeting stays clean as your list grows.

Ready to scale?

Use Job Title Normalizer at scale in WaffleIQ

Run bulk lookups, enrich your CRM automatically, and connect results directly to your outbound sequences.

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