/bond

Power User Advocacy Reference

Purpose: Identify the 10-20% of users driving disproportionate engagement and revenue, build an advocacy ladder (active → advocate → referrer → community leader), and activate them through community, referral mechanics, and early-access programs.

Scope Boundary

• bond power-user: Power-user identification and advocacy activation (this document).
• bond loyalty (elsewhere): Points / tier / reward programs. Power-user is earn-through-behavior; loyalty is earn-through-spend.
• Voice (elsewhere): NPS survey and promoter signals. Power-user consumes Voice's promoter data.
• Growth (elsewhere): Referral mechanics and viral loops. Power-user feeds high-intent candidates into Growth's referral system.
• Pulse (elsewhere): L21+ MAU bucket metrics and overlap analysis.
• Prose (elsewhere): Advocacy program copy.

Identification Rubric

Combine behavioral + sentiment signals:

Power User = (Behavioral signal) ∩ (Sentiment signal) ∩ (Tenure signal)

Behavioral signal (pick any top-quartile)

Sentiment signal

Tenure signal

Power User identification: user meets ≥ 1 behavioral + ≥ 1 sentiment + tenure ≥ 90d.

Advocacy Ladder

        Active
          │  sustained engagement
          ▼
       Advocate           (talks about product, replies to reviews, testimonial opt-in)
          │  visible advocacy
          ▼
       Referrer           (actively refers new users, shares signup link)
          │  measurable invite conversions
          ▼
  Community Leader        (runs meetup, writes content, answers questions in community)

Not every Active becomes a Leader. Design the ladder with increasing effort + reward per step and clear next-action per tier.

Per-Tier Activation Triggers

Each step is earned by observed behavior, not claimed. Avoid self-nomination — actions > intent.

Activation Program Elements

Referral Mechanics

For the Referrer tier:

• Share link with unique attribution token.
• Reward both sides (friend + referrer) — the dual-side incentive drives much higher conversion than one-side.
• Reward shape: account credit, extended subscription, premium feature unlock (not cash — cash attracts fraud).
• Reward trigger: referee reaches activation threshold (not just signup) — prevents gaming.
• Fraud guard: rate-limit referrals per user, verify payment method uniqueness, block known fraud networks.
• Leaderboard (optional): top referrers public if opted-in; provides social status.

Benchmark referral rates (Viral K-factor):

• K < 0.5 → referral is supplemental, not driving growth
• K 0.5-1.0 → meaningful contribution
• K ≥ 1.0 → viral growth engine

Metrics

Segmentation for Power Users

Don't treat all power users the same:

• B2B admin vs end-user: admin is the decision-maker; end-user is the champion. Different activation.
• Industry / vertical: healthcare power users act differently from SaaS dev tool power users.
• Plan tier: enterprise power users demand different handling than free-tier.
• Region: community events and swag logistics differ by region.

Output Template

## Power User Advocacy Plan

### Identification
- **Behavioral signal**: [chosen metric + threshold]
- **Sentiment signal**: [NPS / opt-in / review]
- **Tenure signal**: ≥ 90 days active
- **Current identified power users**: [count, % of MAU]

### Advocacy Ladder
| Tier | Count | Criteria | Next-step trigger |
|------|-------|----------|-------------------|
| Active | [N] | rubric met | ... |
| Advocate | [N] | testimonial opt-in + helping others | ... |
| Referrer | [N] | shared link, ≥1 activated referee | ... |
| Leader | [N] | community work | ... |

### Activation Programs
- [ ] Private community (tier: Advocate+)
- [ ] Beta early-access (tier: Advocate+)
- [ ] Quarterly PM feedback call (tier: Advocate+)
- [ ] Referral program with dual-side reward (tier: Referrer)
- [ ] Community Leader stipend (tier: Leader)
- [ ] Swag ladder (per tier)

### Referral Program (if Referrer tier activated)
- **Reward shape**: [credits / service months / feature unlock]
- **Reward trigger**: referee reaches activation, not just signup
- **Fraud guards**: [rate limits, unique payment, fraud detection]
- **Attribution**: unique link, UTM, in-product share

### Metrics
- **Primary**: Referral K-factor
- **Secondary**: Advocate-to-churn ratio (vs baseline), referred-LTV uplift
- **Guardrail**: referral fraud rate < 1%, power-user burnout rate < 5%

### Handoffs
- Voice: NPS promoter signal
- Growth: referral-loop mechanics and viral-growth measurement
- Pulse: L21+ bucket + identification event
- Prose: advocacy-invite and referral copy
- Experiment: test activation thresholds and rewards
- Scribe: community code of conduct

Anti-Patterns

Deliverable Contract

When power-user completes, emit:

• Identification rubric (behavioral × sentiment × tenure).
• Advocacy ladder with counts per tier and next-step triggers.
• Per-tier activation programs.
• Referral mechanics (if Referrer tier active) with reward shape, trigger, fraud guards.
• Metrics plan (K-factor, advocate churn, referred LTV, guardrails).
• Handoffs: Voice, Growth, Pulse, Prose, Experiment, Scribe.

References

• a16z — "Power User Curve"
• Sarah Tavel — "Enduring vs Non-Enduring" (power-law engagement)
• Reforge — Community-Led Growth course
• Sangeet Paul Choudary — Platform Scale (two-sided power users)
• Brian Balfour — Growth Loops and referral K-factor
• AppsFlyer / Branch — Referral fraud detection patterns
• Dropbox, Airbnb, PayPal — classic dual-side referral case studies