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Network membership tier and fee structure evaluator

Evaluates a nonprofit network's membership tiers, dues structure, and benefit bundles across equity, revenue sustainability, and perceived value — then delivers ranked restructuring options including size-based tiering…

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Purpose

Diagnose whether a nonprofit network's membership tiers and dues model are equitable, financially sustainable, and priced to match perceived value — then deliver ranked restructuring options with projected revenue effects. Solves the recurring tension between charging enough to fund the network and keeping membership accessible to smaller or under-resourced members.

When to Use

Invoke this skill when the user asks to:

  • Redesign or rebuild a membership dues or fee structure
  • Add, collapse, or rename membership tiers
  • Evaluate whether a sliding-scale or size-based model would work
  • Respond to member complaints that dues are unfair or too high
  • Unbundle services currently included in flat dues into à la carte options
  • Stress-test whether current dues revenue can sustain the network's budget

Inputs Required

Before starting, collect:

  • Current tier structure: Each tier's name, dues amount, and what it includes
  • Member mix: How many members sit in each tier (counts or percentages)
  • Member size profile: Range of member organizations by budget, staff, or revenue — how homogeneous or varied
  • Network operating budget: Annual budget and the share currently covered by dues vs. grants/other revenue
  • Core benefits offered: The full list of member benefits and services the network provides
  • Known pain points: Complaints, churn patterns, or unpaid dues the network is experiencing
  • Strategic goals: What the network wants from this redesign — more revenue, more equity, larger membership, or retention

If member mix or size profile is missing, ask for it before proceeding — the analysis is unreliable without member distribution data.

Instructions

Step 1: Diagnose the Current Model

Classify the existing structure and expose its weaknesses:

  • Model type: Flat dues / fixed tiers / size-based / sliding scale / hybrid — name it explicitly
  • Revenue concentration: What share of dues revenue comes from the top tier? A model where >50% of revenue depends on <15% of members is fragile
  • Tier compression: Are members bunched into one or two tiers, leaving others empty? Empty tiers signal mispricing
  • Equity gaps: Do the smallest members pay a disproportionate share of budget relative to their capacity? Compute dues as a rough % of member budget where data allows
  • Value-to-price alignment: Do higher tiers actually deliver more, or do they just cost more? Flag any tier that charges more without a benefit differential

Step 2: Assess Financial Sustainability

Test whether dues revenue can carry the network:

  • Dues coverage ratio: Dues revenue ÷ operating budget. Below ~30% signals grant-dependence risk; the redesign should note this
  • Break-even sensitivity: How many members can the network lose before dues revenue drops below its floor?
  • Concentration risk: Model the revenue loss if the single largest member left
  • Payment friction: Note whether unpaid or late dues correlate with a specific tier — often a pricing signal, not a collections problem

Step 3: Assess Equity

Evaluate fairness across member capacity:

  • Ability-to-pay alignment: Do dues scale with member size/budget, or does a large member pay nearly the same as a small one?
  • Access barrier: Is the entry tier priced low enough that the intended smallest members can actually join?
  • Perceived fairness vs. actual fairness: Distinguish between members who feel overcharged and members who objectively are — recommend differently for each

Step 4: Assess Perceived Value

Evaluate whether members feel they get their money's worth:

  • Benefit legibility: Can a member clearly name what they get for their dues? If not, value is invisible regardless of amount
  • Bundle fit: Are members paying for benefits they don't use? This is the primary trigger for unbundling
  • Differentiation clarity: Is the reason to move up a tier obvious and compelling?

Step 5: Generate 3 Ranked Restructuring Options

Produce three distinct restructuring options, ranked by fit to the stated strategic goals. For each option, cover the three primary levers as relevant:

Lever A — Size-Based Tiering Set dues as a function of an objective member metric (annual budget, staff count, or revenue band).

  • Define 3–5 bands with specific dues amounts or a formula (e.g., 0.25% of member budget, capped)
  • Show which current members land in which new band
  • Best when members vary widely in size and equity is the primary concern

Lever B — Sliding Scale Allow members to self-select or negotiate within a defined range tied to capacity.

  • Define the range, the anchoring guidance, and the accountability mechanism (self-attestation vs. documentation)
  • Address free-rider risk directly
  • Best when member size data is hard to standardize or the culture favors trust-based fairness

Lever C — Service Unbundling Separate a lean core membership from à la carte add-ons.

  • Define the base tier (what everyone gets) and 3–5 unbundled services with pricing
  • Model revenue under conservative uptake assumptions
  • Best when members pay for benefits they don't use and perceived value is low

Each of the 3 options must specify: new tier/dues structure, projected annual dues revenue vs. current, equity effect, and the primary risk. Rank them explicitly against the network's stated goals.

Step 6: Recommendation and Transition Plan

  • Name one recommended option with a 2–3 sentence rationale tied to the goals
  • Provide a phased rollout: grandfather existing members, communicate the change, and set a transition timeline
  • Flag the single biggest adoption risk and how to mitigate it

Output Format

  • Structure: Diagnostic sections followed by 3 ranked restructuring options, then recommendation
  • Length: 1,100–1,500 words
  • Format: Structured document — prose diagnosis, tables for tier/revenue comparisons, bulleted options
  • Sections: Current model diagnosis → Sustainability assessment → Equity assessment → Perceived value assessment → 3 ranked options → Recommendation and transition plan
  • Tone: Nonprofit finance director — analytical and candid, sensitive to mission and member relationships, unafraid to name a fragile revenue model

Quality Checklist

Before delivering output, verify:

  • [ ] Current model is classified by type and its revenue concentration is quantified
  • [ ] Dues coverage ratio and break-even/concentration risk are calculated from the inputs provided
  • [ ] Exactly 3 restructuring options are presented, each with projected revenue vs. current
  • [ ] Each option addresses equity effect and its primary risk — not just the numbers
  • [ ] Options are ranked against the network's stated strategic goals, not presented as equal
  • [ ] The recommendation names one option and includes a phased transition with grandfathering

Notes

  • Empty or overcrowded tiers are the clearest evidence of mispricing — read the member distribution before the dues amounts
  • Sliding-scale models fail without an accountability mechanism; never recommend one without addressing free-rider risk
  • Unbundling raises perceived value even when total dues stay flat, because members see exactly what they pay for
  • Grandfathering existing members through a transition is almost always worth the short-term revenue delay — abrupt dues increases drive churn that erases the gain

How to use this skill

This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/SKILL.md — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

Using in Claude.ai, ChatGPT, Gemini, or other AI tools:

  1. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills