NYCF_BioKind

Quick exploratory analysis for BioKind's donor/marketing support work with NYCF (New York Cancer Foundation).

Data Used

• Source workbook: data/NYCFBiokindData.xlsx
• Converted CSV: data/NYCFBiokindData_Sheet1.csv
• Analysis script: analysis/analyze_nycf_data.py

Quick Findings (Current Snapshot)

• Total records: 4,462
• Columns: 10
• Organization field: all rows are New York Cancer Foundation
• Status split:
  • Active: 4,197
  • DoNotContact: 265
• Donation distribution:
  • Parsed donation values for all 4,462 rows
  • Total donations: $10,658,637.30
  • Mean: $2,388.76
  • Median: $0.00
  • Max: $325,000.00
  • Rows with $0 donation: 2,494

Donor Value Segments

• 0: 2,494
• 1-25: 234
• 26-100: 509
• 101-500: 450
• 501-2.5k: 420
• 2.5k-10k: 186
• 10k+: 169

Data Quality Notes

• Missing values are high in location fields:
  • city: 56.4% missing
  • state: 56.7% missing
  • zip code: 56.6% missing
• extension is 100% missing
• phone type is almost entirely Unknown

What We Can Do Next for NYCF

1. Donor segmentation: build target groups (non-donor, small, mid, major).
2. Major donor strategy: prioritize the 10k+ cohort and identify upgrade candidates in 501-2.5k.
3. Reactivation campaign: target $0 segment with tailored outreach.
4. Data cleanup/enrichment: improve city/state/zip and contact fields before deeper campaign attribution analysis.