$ man clay-wiki/alumni-effect
Playsintermediate
Alumni Effect
Target contacts who moved from closed-won accounts to new companies
What This Play Does
The Alumni Effect finds contacts who used to work at your closed-won accounts and have since moved to new companies. These people already know your product. They've used it. They may have championed the original deal. Now they're at a new company — a company that doesn't use your product yet. This is the warmest cold outreach you can do. The contact has built-in trust and product familiarity. You're not selling to a stranger. You're reconnecting with someone who already knows the value.
Why This Works
Most outbound is fully cold. The prospect has never heard of you, never used your product, and has no reason to reply. The Alumni Effect flips that. The prospect has used your product. They may have been a power user, a champion, or even the person who signed the original deal. When they get an email that says "saw you moved from [old company] to [new company] — we worked together when you were at [old company]," the response rate is 3-5x higher than standard cold outbound.
The signal is simple: job change from a closed-won account. But the impact is outsized because trust transfers with the person, not the company.
PATTERN
The Build (Clay + CRM)
Step 1: Pull closed-won contacts from your CRM. In Salesforce, use SOQL to query contacts associated with closed-won opportunities. In HubSpot, filter contacts by deal stage = closed-won.
Step 2: Import those contacts into a Clay table. These are your "alumni seeds."
Step 3: Run LinkedIn enrichment on every contact. Clay checks their current employer against their employer at time of close. If the company changed, flag them.
Step 4: For flagged contacts (job changers), enrich the new company. Does the new company fit ICP? Score it.
Step 5: For qualified new companies, build a mini company card — ICP score, employee count, industry, service fit.
Step 6: Route. If the alumni contact is now at a qualified company, route to outreach. If the new company doesn't fit ICP, flag but don't contact.
This runs weekly. Job changes happen constantly. The table refreshes and catches new alumni every cycle.
PRO TIP
Signal Stacking with Alumni
The Alumni Effect gets even stronger when you stack signals. Alumni alone is good. Alumni + web reveal intent is great. If someone from a closed-won account moved to a new company AND that new company is visiting your website, that's a top-priority lead.
Stack these signals on alumni contacts:
• Web reveal — is the new company showing intent on your site?
• Hiring signals — is the new company hiring for roles that suggest they need your product?
• Tech stack changes — did the new company recently adopt or drop a competing tool?
• Funding — did the new company recently raise a round?
Each signal added to the alumni base increases confidence and reply rates.
PATTERN
The Champion Tracking Layer
Not all alumni are equal. A junior user who left is less valuable than the VP who championed the deal. Add a champion tag to your CRM contacts based on their role in the original deal:
• Champion — actively sold internally, drove the deal forward
• Power user — heavy product user, internal advocate
• Stakeholder — involved in the deal but not the driver
• End user — used the product but had no buying influence
When the Alumni Effect surfaces a job change, check the champion tag. Champions at new companies get high-priority routing. End users at new companies get standard sequencing or skip.
ANTI-PATTERN
Common Mistakes
Treating all alumni the same. A champion who left is not the same as a junior analyst who left. Qualify the person, not just the company.
Running the Alumni Effect without checking if the new company is already in your pipeline. Before reaching out to an alumni contact, check: does the new company already have an active deal? Is another rep already working that account? CRM lookup first. Always.
Another mistake: running this as a one-time play. The Alumni Effect is a recurring workflow. Set it to run weekly. Job changes are continuous. A one-time pull misses 90% of the value.
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