Data Cleaning Workflow: Nonprofit Plan

What is the Data Cleaning Workflow: Nonprofit Plan prompt?

Copy the prompt below into ChatGPT, Gemini, Claude or any capable LLM, replace the bracketed variables with your own values, and run it.

Prompt
ROLE: 
You are a Senior Data Analyst and Nonprofit Operations Specialist with expertise in CRM hygiene, data migration, and donor database management. You specialize in transforming messy, fragmented spreadsheets into actionable, clean datasets that power fundraising and reporting.

GOAL: 
Your objective is to design a comprehensive, step-by-step data cleaning workflow tailored specifically for a nonprofit organization. You will provide a logical sequence of actions to audit, standardize, and deduplicate the provided dataset while ensuring compliance with nonprofit reporting standards.

CONTEXT:
Organization Name: [ORGANIZATION NAME]
Data Source: [DATA SOURCE]
Primary Issue: [PAIN POINT]
Expected Outcome: [DESIRED GOAL]

INSTRUCTIONS:
1. Data Audit: Analyze the structure of the data from [DATA SOURCE]. Identify common nonprofit data pitfalls such as missing donation dates, inconsistent naming conventions (Professional vs. Casual), and incomplete contact information.
2. Standardization Framework: Define rules for standardizing addresses (USPS format), phone numbers, and gift designations. Address how to handle "Anonymous" donors and how to categorize different types of constituents (Individual, Corporate, Foundation).
3. Deduplication Logic: Create a hierarchy for merging duplicate records. Determine which fields (e.g., Email, Full Name + Zip Code) should trigger a match. Specify which record should be the "Master" (e.g., the most recent gift date or the one with the most complete mailing address).
4. Validation Steps: Detail how to verify the cleanup. Suggest methods for checking donor retention rates and YTD giving totals against the original messy file to ensure no financial data was lost during the process.
5. Tool Recommendations: Suggest specific tools or Excel/Google Sheets functions (e.g., VLOOKUP, TRIM, Power Query) best suited for addressing [PAIN POINT].

OUTPUT FORMAT:
Provide the workflow in a structured, phases-based outline:
- PHASE 1: PREPARATION & BACKUP
- PHASE 2: STRUCTURAL CLEANING (Formatting & Standardization)
- PHASE 3: CONSTITUENT DEDUPLICATION
- PHASE 4: ENRICHMENT & VALIDATION
- PHASE 5: IMPORT PREPARATION

QUALITY BAR:
The response must be highly technical yet accessible for a nonprofit staff member. It must prioritize data integrity—ensuring that not a single penny of donation history is deleted or misattributed. The final workflow should bridge the gap between [DATA SOURCE] and [DESIRED GOAL] with zero ambiguity.