advocate-identifier

name	advocate-identifier
description	Score and rank your user base on advocacy potential (NPS × usage × tenure) and produce a ranked outreach queue with personalized ask messages. Use when the user says "find our advocates", "who should we ask for referrals", "top champions", or is launching a referral / case-study / community play.
status	new

Advocate Identifier (Referral Squad)

Turns your user base into a ranked list of champions ready to be asked — for a case study, a referral, a quote, a panel, or beta feedback.

Triggers

• "who are our advocates"
• "find our champions"
• "build an advocacy list"
• "who should we ask for referrals"
• "NPS × usage scoring"

Inputs required

1. NPS responses with user IDs (most recent per user)
2. Usage data — logins, feature use, tenure
3. Account attributes — plan, company size, public profile (LinkedIn, Twitter)
4. Relationship signals — has a CSM? ever replied to a founder email? posted about us on social?
5. Outreach inventory — what are we actually asking for? (case study, reference call, referral, testimonial, beta)

Process

Step 1 — Compute the advocacy score

For each user:

Advocacy score = 0.4 × NPS_norm + 0.3 × Usage_norm + 0.15 × Tenure_norm
               + 0.1 × Relationship_signals + 0.05 × Public_profile_reach

Normalization: 0–100. Include only users with NPS ≥ 8 AND tenure ≥ 90 days AND active in last 30 days.

Step 2 — Segment advocates by what they're best for

Not every advocate is right for every ask. Bucket them:

• Case study ready — high usage + concrete use case + willing to be public
• Quote-givers — gave a great NPS comment but may not want long engagement
• Referrers — high-NPS prosumer-types with active networks (LinkedIn followers, Twitter reach)
• Beta testers — power users who file good bug reports
• Speakers / panelists — public profile + happy to talk

Tag each advocate with the top 1–2 buckets they fit.

Step 3 — Write the ask

For each advocate × ask type, produce a short, specific, first-name outreach message:

• Reference something they specifically said or did (pull from NPS comment or usage)
• Be concrete about the ask (not "let's chat")
• Be concrete about what they get in return (early access, exposure, a t-shirt, $50 donation, nothing but gratitude)
• Make it one-click to say yes or no

Keep each message under 80 words.

Step 4 — Rate-limit the outreach

Rules:

• Max 1 ask per advocate per 60 days
• Never cold-ask a user with an open support ticket
• Always route through CSM if they have one
• Don't ask enterprise accounts without account team sign-off

Step 5 — Output the queue

CSV with columns:

user_id | name | email | company | score | best_for | suggested_ask | owner | status

Plus a markdown file with the top 20 messages pre-written, ready to paste.

Output artifacts

• advocate-queue.csv
• advocate-outreach-top20.md

Handoff

• Case-study candidates → Case Study Builder
• Referrers → Referral Program Designer (invite to beta program first)
• Quote-givers → Landing Page Optimizer + Competitive Scout
• Performance of outreach → Performance Reporter

Example call

"Build our advocate list. I've attached NPS responses (users.csv), usage (events.csv), and plan/tenure (accounts.csv). We want: 5 case study candidates, 20 referrers, 10 quote-givers for the new homepage."