For nonprofits looking to improve their fundraising results, overly simplistic metrics like average gift amount and overall retention rate are not enough. According to fundraising analytics expert Kirk Smith, nonprofits should focus on analyzing retention rates, gift amounts and donor subgroups to gain actionable insights.
Retention rates vary widely based on factors like donor acquisition channel and years of giving. New donors acquired through peer-to-peer fundraising often have lower retention rates of 15-20% compared to 70-80% for long-time donors. Nonprofits need to calculate retention rates for key donor subgroups to understand the factors driving donor loyalty and predict future retention.
Similarly, average gift amount can mask meaningful differences in key donor segments. The top and bottom 5% of gift amounts can skew the average, obscuring the most common gift amounts that form the bulk of revenue. Nonprofits should analyze the distribution of gift amounts to see the most common values for key donor groups. This can help optimize fundraising appeals and suggested gift amounts.
Focusing on simplistic metrics like overall retention rate and average gift amount provides an incomplete picture and risks misallocating resources. By analyzing retention rates, gift amounts and other key metrics for specific donor subgroups, nonprofits can gain actionable insights to strengthen their fundraising programs.
For small nonprofits with limited resources, identifying a few key donor segments to analyze can provide significant value.
Retention rates and gift amounts for newly acquired donors, repeat donors of 2-3 years and higher-level donors are examples of subgroups that could yield impactful insights.
While advanced analytics and AI tools can help with this type of analysis, they may be out of reach for small nonprofits. But by starting with their CRM and spreadsheet tools and focusing on analyzing key metrics for a few donor subgroups, small nonprofits can strengthen their fundraising results and build the case for further investment in analytics. The key is moving from overly simplistic metrics to targeted, data-driven analysis.
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