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Fundraising Analyzer

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travisjneuman
fundraising-analyzer

Nonprofit fundraising performance analysis with donor segmentation, campaign ROI, retention metrics, and trend analysis. Use when evaluating fundraising effectiveness, analyzing donor data, or planning campaigns.

Overview

Publishertravisjneuman
Repository.claude
Skill namefundraising-analyzer
Stars
98
Forks
22
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by travisjneuman on GitHub. Read the source before you install it.

Installation

Install the Fundraising Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/travisjneuman/.claude.git /tmp/.claude
mkdir -p .claude/skills
cp -r /tmp/.claude/skills/fundraising-analyzer .claude/skills/fundraising-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fundraising Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fundraising Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fundraising Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Fundraising Analyzer

Frameworks for analyzing nonprofit fundraising performance, segmenting donors, evaluating campaign effectiveness, and building data-driven fundraising strategies.

Donor Analysis

Donor Segmentation Framework

DONOR SEGMENTATION MATRIX:

BY GIVING LEVEL:
  Tier              | Annual Giving      | % of Donors | % of Revenue
  ------------------|--------------------| ------------|-------------
  Major donors      | $10,000+           | [%]         | [%]
  Mid-level donors  | $1,000 - $9,999    | [%]         | [%]
  Grassroots donors | $100 - $999        | [%]         | [%]
  Small donors      | Under $100         | [%]         | [%]

BY ENGAGEMENT:
  Segment           | Definition                    | Strategy
  ------------------|-------------------------------|------------------
  Champions         | Top 10% by giving + volunteer | Steward, recognize
  Loyal             | 3+ consecutive years giving   | Retain, upgrade
  Growing           | Increased gift this year      | Encourage, cultivate
  Lapsed risk       | Decreased gift or late renewal| Re-engage campaign
  Lapsed            | No gift in 13+ months         | Win-back campaign
  New               | First gift in last 12 months  | Welcome series

BY RECENCY-FREQUENCY-MONETARY (RFM):
  Score each 1-5:
  Recency:   How recently did they give? (5 = this month)
  Frequency: How often do they give?     (5 = monthly)
  Monetary:  How much do they give?      (5 = top tier)

  RFM Score  | Segment    | Priority
  555        | Best       | Highest — personal stewardship
  5XX        | Active     | High — upgrade opportunities
  X5X        | Frequent   | Medium — increase gift size
  XX5        | High value | High — increase frequency
  1XX        | At risk    | High — re-engagement needed
  111        | Lost       | Low — win-back or remove

Donor Lifetime Value

DONOR LIFETIME VALUE (LTV) CALCULATOR:

INPUTS:
  Average annual gift:           $______
  Average giving years:          ______ years
  Donor retention rate:          ______%
  Discount rate:                 ______% (typically 5-8%)

SIMPLE LTV:
  LTV = Average annual gift × Average giving years
  LTV = $______ × ______ = $______

ADJUSTED LTV (with retention):
  LTV = Average gift × (Retention rate / (1 - Retention rate))
  LTV = $______ × (____% / (1 - ____%)) = $______

COST-ADJUSTED LTV:
  Acquisition cost:              $______
  Annual stewardship cost:       $______
  Net LTV = Adjusted LTV - Acquisition cost - (Stewardship × Years)
  Net LTV = $______

BY SEGMENT:
  Segment          | Avg Gift | Retention | LTV     | Acq Cost | Net LTV
  -----------------|----------|-----------|---------|----------|--------
  Major donors     | $______  | ____%     | $______ | $______  | $______
  Mid-level        | $______  | ____%     | $______ | $______  | $______
  Grassroots       | $______  | ____%     | $______ | $______  | $______
  Small            | $______  | ____%     | $______ | $______  | $______

Campaign Analysis

Campaign Performance Dashboard

CAMPAIGN REPORT: [Campaign Name]
Period: [Start Date] — [End Date]
Goal: $______

RESULTS:
  Revenue raised:       $______  (___% of goal)
  Number of gifts:      ______
  Average gift:         $______
  Median gift:          $______
  New donors acquired:  ______
  Returning donors:     ______

COST ANALYSIS:
  Total campaign cost:  $______
  Cost per dollar raised: $______
  Cost per acquisition:   $______
  ROI: (Revenue - Cost) / Cost = ______%

CHANNEL PERFORMANCE:
  Channel          | Revenue  | Gifts | Avg Gift | Cost    | ROI
  -----------------|----------|-------|----------|---------|-----
  Email            | $______  | _____ | $______  | $______ | ___%
  Direct mail      | $______  | _____ | $______  | $______ | ___%
  Social media     | $______  | _____ | $______  | $______ | ___%
  Website          | $______  | _____ | $______  | $______ | ___%
  Events           | $______  | _____ | $______  | $______ | ___%
  Phone/text       | $______  | _____ | $______  | $______ | ___%

YEAR-OVER-YEAR:
  Metric           | Last Year | This Year | Change
  Revenue          | $______   | $______   | ____%
  Donors           | ______    | ______    | ____%
  Avg gift         | $______   | $______   | ____%
  New donors       | ______    | ______    | ____%

Campaign Comparison Matrix

MetricSpring AppealYear-EndGala EventGiving TuesdayPeer-to-Peer
Revenue$______$______$______$______$______
Cost$______$______$______$______$______
ROI____%____%____%____%____%
New donors______________________________
Avg gift$______$______$______$______$______

Key Metrics

Fundraising Health Scorecard

ANNUAL FUNDRAISING SCORECARD:

GROWTH METRICS:
  Total revenue:                  $______ (target: $______)
  Revenue growth (YoY):           ____%   (benchmark: 5-10%)
  Number of donors:               ______  (target: ______)
  Donor growth (YoY):             ____%   (benchmark: 5-8%)

RETENTION METRICS:
  Overall retention rate:         ____%   (benchmark: 45-50%)
  First-year donor retention:     ____%   (benchmark: 25-30%)
  Multi-year donor retention:     ____%   (benchmark: 60-65%)
  Donor upgrade rate:             ____%   (benchmark: 10-15%)
  Donor downgrade rate:           ____%   (target: <10%)

EFFICIENCY METRICS:
  Cost to raise a dollar:         $______ (benchmark: $0.20-0.30)
  Fundraising expense ratio:      ____%   (benchmark: <15%)
  Average gift size:              $______
  Revenue per donor:              $______
  Revenue per staff FTE:          $______

DIVERSITY METRICS:
  # of revenue sources:           ______  (target: 5+)
  Largest source % of total:      ____%   (target: <30%)
  Individual vs institutional:    ___% / ___%

HEALTH INDICATORS:
  ✓ Green:  Retention > 50%, Growth > 5%, Diversity > 5 sources
  △ Yellow: Retention 40-50%, Growth 0-5%, 3-4 sources
  ✗ Red:    Retention < 40%, Decline, < 3 sources

Benchmark Comparison

MetricYour OrgSector AvgTop QuartileStatus
Retention rate____%45%65%+
First-year retention____%27%40%+
Cost per dollar$____$0.25<$0.15
Online giving %____%13%25%+
Major gift %____%60%75%+
Monthly giving %____%15%30%+

Trend Analysis

Multi-Year Trend Template

5-YEAR FUNDRAISING TRENDS:

YEAR          | Y-4      | Y-3      | Y-2      | Y-1      | Current
              |----------|----------|----------|----------|--------
Revenue       | $______  | $______  | $______  | $______  | $______
Donors        | ______   | ______   | ______   | ______   | ______
Avg Gift      | $______  | $______  | $______  | $______  | $______
Retention     | ____%    | ____%    | ____%    | ____%    | ____%
New Donors    | ______   | ______   | ______   | ______   | ______
Lapsed Donors | ______   | ______   | ______   | ______   | ______

TREND ANALYSIS:
  Revenue trend:    [Increasing / Stable / Declining] at ___% annually
  Donor base trend: [Growing / Stable / Shrinking] at ___% annually
  Key concern:      [Identify the most worrying trend]
  Key strength:     [Identify the most positive trend]

PROJECTIONS (next 3 years):
  If current trends continue:
    Revenue Y+1: $______
    Revenue Y+2: $______
    Revenue Y+3: $______

  If retention improves by 5%:
    Revenue Y+1: $______
    Revenue Y+2: $______
    Revenue Y+3: $______

Giving Strategy Templates

Monthly Giving Program Analysis

MONTHLY GIVING PROGRAM:

CURRENT STATE:
  Monthly donors:           ______
  Average monthly gift:     $______
  Annual value per donor:   $______ (monthly × 12)
  Total annual revenue:     $______
  % of total fundraising:   ____%
  Retention rate:           ____%  (benchmark: 80-90%)

GROWTH ANALYSIS:
  New monthly donors (this year):    ______
  Upgraded from one-time:            ______
  Cancelled:                         ______
  Net change:                        ______

UPGRADE OPPORTUNITIES:
  Donors giving < $25/month:         ______ → Upgrade to $35
  Donors giving $25-49/month:        ______ → Upgrade to $50
  Donors giving $50-99/month:        ______ → Upgrade to $100
  Potential revenue increase:        $______/year

ACQUISITION CHANNELS:
  Channel              | Conversions | Avg Gift | Cost/Acquisition
  Website popup        | ______      | $______  | $______
  Email campaign       | ______      | $______  | $______
  Direct mail insert   | ______      | $______  | $______
  Thank-you page upsell| ______      | $______  | $______

Major Gift Pipeline

MAJOR GIFT PIPELINE: FY[Year]

STAGE           | # Prospects | Total Value | Avg Gift  | Probability
----------------|-------------|-------------|-----------|------------
Identification  | ______      | $______     | $______   | 10%
Qualification   | ______      | $______     | $______   | 25%
Cultivation     | ______      | $______     | $______   | 50%
Solicitation    | ______      | $______     | $______   | 75%
Closed          | ______      | $______     | $______   | 100%

WEIGHTED PIPELINE VALUE:
  = Σ (Value at each stage × Probability)
  = $______

PIPELINE METRICS:
  Average cultivation time:    ______ months
  Close rate (solicited):      ____%
  Average solicitation:        $______
  Average closed gift:         $______
  Gifts above ask:             ____%
  Gifts below ask:             ____%

See Also

Frequently asked questions

What does the Fundraising Analyzer AI skill do?

Nonprofit fundraising performance analysis with donor segmentation, campaign ROI, retention metrics, and trend analysis. Use when evaluating fundraising effectiveness, analyzing donor data, or planning campaigns.

Why use Fundraising Analyzer on TypingMind?

Because you install it once and use it with any model. Fundraising Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fundraising Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/travisjneuman/.claude/tree/master/skills/fundraising-analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fundraising Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fundraising Analyzer?

As many as you like. As long as a model supports skills, you can use Fundraising Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fundraising Analyzer AI skill free?

Yes. It is published on GitHub by travisjneuman under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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