Find where your former customers went

<context>
Every contact who leaves a customer account takes their experience of our
product with them. I want to find them, see where they landed, and work
the ones whose new company isn't already a customer.
 
My inputs:
- Closed-won account domains: [PASTE DOMAINS, one per line]
- Current customer domains (to exclude): [PASTE DOMAINS — usually the same list]
- Function I sell into: [SALES / REVOPS / IT / FINANCE / OTHER]
- How far back to look: [12 MONTHS unless stated otherwise]
</context>
 
<task>
1. Use Lusha to find contacts whose previous employer is one of my
   closed-won domains, filtered to:
   - Job changed within the stated window
   - VP and C-suite seniority
   - My target function, if one is specified
 
2. Exclude anyone whose CURRENT company is still on my customer list.
   These are internal moves, not departures.
 
3. For each person who left, return a preview row:
   Name | Former customer account | New company | New title | Months in new role
 
4. Flag which new companies are NOT already customers. Those are the
   new-logo opportunities.
 
5. Group by new company. If several people from my customer base landed
   at the same place, say so — that account has multiple people who
   already know the product.
 
6. Wait for my shortlist, then reveal verified email for those contacts only.
</task>
 
<constraints>
- Preview only until I confirm the shortlist. Reveal email only, not phone.
- Exclude internal moves. If current company equals former company, drop the row.
- Someone 0-3 months into a new role is the highest-value timing window.
  Sort by recency of move.
- Don't infer that a former employee was a champion. Flag them as a
  warm contact to qualify, not a guaranteed advocate.
</constraints>

The situation: a CS-led outbound push. The team pulled three closed-won account domains as a test before running the full customer list.

Output: 138 senior contacts who previously worked at those three accounts and changed roles in the last twelve months. A slice of the result:

Five of 138 returned, individually masked. Live result via Lusha connector, August 15, 2026.

What it cost: 1 credit. Contact search bills at 1 credit per batch of up to 25 records, so the first 25 rows of a 138-person result cost 1. Revealing email on a shortlist costs 1 credit per contact. Skip phone reveals here — this is a warm-intro play, not a cold-calling one, and phone costs 5x email.

Three accounts produced 138 senior alumni. Scale that against a full closed-won list and the arithmetic gets interesting quickly. This is the play that turns customer churn into pipeline rather than loss.

The trap this prompt is built to avoid

The previous-employer filter matches a contact’s employment history, not their departure. Someone promoted internally still has that company in their history, so a naive version of this search returns people who never left at all — two of the first ten results in our test run were still at the origin company.

That is why the prompt carries an explicit exclusion: if the current company is still on your customer list, drop the row. Without it you would email a live customer’s champion as though they were a prospect, which is worse than not running the play.

If the list comes back thin

Widen the window before assuming coverage. Twelve months at roughly 1% per month is a modest slice of any customer base; a twenty-four month window roughly doubles it. Also check that you have passed domains rather than company names — a misspelled or abbreviated company name can match a different organisation entirely.