DECISIVE SYSTEM's monthly donor scoring turned out to be almost twice as effective to identify potential monthly donors
than the ad hoc targeting rules we've developed internally over the years.
Utilizing Artificial Intelligence (AI) and Machine Learning (ML) has significantly streamlined the process for non-profits to identify potential monthly donors within their databases. These technologies efficiently analyze extensive donor data, focusing on past giving patterns, donation frequency, demographics, and engagement levels to pinpoint individuals likely to commit to regular, recurring donations.
AI’s capability to uncover hidden trends in donor behavior is a game-changer. It can, for instance, identify one-time donors who are prime candidates for transitioning to monthly giving. This insight is crucial as it leverages but also extends beyond basic demographic data, offering a more nuanced understanding of donor habits and preferences.
Our monthly donor scoring models enable non-profits to personalize their outreach. By understanding the unique characteristics of potential monthly donors, organizations can craft more resonant and effective appeals, increasing the likelihood of converting one-time donors into regular supporters.
In the chart above, each donor has been assigned a monthly-donor score from 1 (worst) to 20 (best), based on their demographics, past behaviors, and key behavioral indicators. The chart plots the conversion rates after a six-month period and an all-out conversion campaign. Less than 3% of the database, as identified by our exclusive predictive model, accounted for more than 40% of the donors who were effectively transformed into monthly donors, hence allowing the organization to effectively focus their efforts on the most promising donors, hence minimizing costs while maximizing impact.
