Enrich event registrant list before pre-event outreach

<context>
I have a registrant list from an upcoming event or webinar. Before pre-event emails go out, I want to enrich every registrant with verified contact data and firmographics — so the emails are segmented and personalized based on actual job titles and company profiles, not what people typed into a form field. I also want to flag any registrant who has departed their company or whose contact details don't match what was submitted.

My registrant list:
- Event name: [EVENT NAME]
- Registrant list: [PASTE NAME, EMAIL, COMPANY, TITLE (if submitted) — one per line]
- What we sell: [PRODUCT / SOLUTION]
- ICP criteria: [COMPANY SIZE / INDUSTRY / FUNCTION]
- Pre-event email send date: [DATE OR "TBD"]
- Segmentation needed: [e.g. "by seniority" / "by company size" / "by industry" / "suggest segments"]
</context>

<task>
1. For each registrant, use Lusha to enrich and validate:
   - Confirm current verified title — does it match what was submitted on the form?
   - Still at the company? Flag if contact has departed.
   - Company: headcount, industry, HQ location, funding stage
   - ICP fit: does the company and role match stated criteria?
   - Flag title mismatches between form submission and Lusha

2. Score each registrant for ICP fit:
   - Strong fit: decision-maker or senior influencer at an ICP-matching company
   - Good fit: ICP-matching company, below ideal seniority
   - Weak fit: partial ICP match
   - Outside ICP: doesn't match — include in event communications but don't prioritise for sales follow-up

3. Segment the enriched registrant list for pre-event email personalisation:
   - Based on stated segmentation criteria
   - If "suggest segments": analyse the enriched data and recommend 3–4 natural segments
   - For each segment: shared profile and a one-line subject line angle

4. Flag any data quality issues:
   - Departed contacts — don't send to a dead address
   - Title mismatches — personalisation tokens will be wrong if not corrected
   - Duplicate registrations

5. Return:
   - Enriched registrant table with verified title, company firmographics, ICP score, and segment
   - Segment breakdown with subject line angle per segment
   - Data quality flags: departed, mismatched, duplicate
   - Summary: X enriched, X strong fit, X good fit, X outside ICP, X flagged
</task>

<constraints>
- Departed contacts must be flagged prominently — sending to a dead address hurts deliverability.
- Title mismatch flag must show both the submitted title and the Lusha-verified title.
- Subject line angle per segment must be specific enough to brief a copywriter.
- Outside ICP registrants still receive event communications — flag, don't remove.
</constraints>

The situation: A field marketing manager has 7 registrants for an upcoming RevOps webinar. Selling to mid-market B2B SaaS, VP and above. Pre-event email goes out in 3 days.

Enriched registrant table

Data quality flags

🔴 DEPARTED — remove from send D.R. — submitted company email is no longer active per Lusha. Remove before send or deliverability score drops.

⚠ TITLE MISMATCHES — fix personalisation tokens R.V. submitted “VP Operations” — Lusha verified title: VP Revenue Operations. Update {{title}} before send. M.L. submitted “Operations Manager” — Lusha verified title: Head of Sales Operations. Update {{title}} before send.

⚠ OUTSIDE ICP — flag for marketing nurture, not sales follow-up J. Smith, Waverly Digital — Marketing Manager at a 180-person company. Below size floor. Include in event comms, exclude from post-event sales routing.

Suggested segments and subject line angles

Segment A — Senior RevOps (3 registrants) R.V. · M.L. · C.N. Profile: RevOps or Sales Ops function, Director and above, 300–620 employees Subject line angle: “Before the webinar: the data quality problem every RevOps leader walks in with”

Segment B — Sales Leadership (2 registrants) T.K. · P.O. Profile: VP of Sales, quota-carrying, 290–580 employees Subject line angle: “Before the webinar: why your SDR ramp time is a data problem, not a training problem”

Summary: 7 registrants · 3 strong ICP fit · 2 good fit · 1 outside ICP · 1 departed · 2 title mismatches fixed

Illustrative example — fictional company names used. Run with your own registrant list to see live results.