How can I use this data for email targeting?
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Job titles are the most actionable B2B signal you have. They tell you what someone cares about, what budget they control, and what language to use. But raw titles are messy, so treat the field like data, not poetry.
Group titles by authority, not by string match.
A CEO, a VP, and an individual contributor read the same email three different ways. The C-suite cares about strategy, revenue, and risk. Directors and VPs care about whether your thing makes their team look good. Individual contributors care about whether it solves the problem on their desk today. Same product, three different opening lines.
Build three or four authority buckets:
- C-level / founder
- VP / Director
- Manager / Lead
- Individual contributor
Anything more granular fragments your list without adding insight.
Group titles by function too.
Marketing, sales, IT, finance, and ops live in different worlds. A finance person wants a business case with numbers. An IT person wants the technical architecture and security posture. A marketing person wants to know if it will make the next campaign better. Sending the same body copy to all five wastes the segmentation work you just did.
This is what behavioral vs demographic vs psychographic signals actually buy you. Function is demographic. Behavior is what they do with your emails. You need both.
Normalize before you segment.
"Head of Growth", "VP of Growth", "Growth Lead", and "Director, Growth Marketing" probably all do similar jobs. A "Director" at a 12-person startup has the scope of a "Manager" at IBM. If you segment by exact string match you get 400 segments of one person each.
Pick a normalization scheme and stick to it. A simple regex pass that maps titles to (function, seniority) tuples covers about 80% of B2B lists. Tools like Clearbit, ZoomInfo, and Apollo do this for you, but you can write the dictionary yourself in an afternoon if your list is under 50K rows.
Do not segment on title alone.
Title tells you their role. It does not tell you whether they opened your last six emails, whether they hit the pricing page yesterday, or whether their company just raised a Series B. Layer title with behavior, recency, and account-level signals. That is where CRM fields earn their keep.
A "VP Marketing who clicked the pricing page in the last 7 days" is a segment of two people that converts. A "VP Marketing in your database" is a segment of 4,000 that does not.
Be careful with the "I know who you are" opening.
"As a CMO, you know..." can land or backfire. If they self-identified as CMO on your form, fine. If you enriched it from a third-party source they never consented to, it reads as surveillance.
M3AAWG's Sender Best Common Practices is direct on this: enriched data should not be used to address recipients in ways that imply a relationship they never agreed to. Mailbox providers read that pattern as a deception signal and it will show up in your complaint rate before it shows up in your conversion rate.
A working playbook:
- Normalize titles into (function, seniority) buckets on ingest.
- Pick 6 to 8 working segments that combine function and authority. Not 60.
- Layer behavior (opens, clicks, recency) on top before any send.
- Personalize the angle, not the salutation. "Here is how Marketing teams measure this" beats "As a marketer, you know this".
- Re-normalize quarterly. Titles drift, people get promoted, companies restructure.
If your list is mostly self-reported B2C data, title segmentation is the wrong tool. Look at engagement-based segmentation instead.
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Every name links to their profile. Every company links to their site. Real people, real accountability.
