Case Study: ActionAid Australia boosts tax appeal fundraising with Dataro machine learning propensity scoring

ActionAid Australia lifts campaign revenue with Dataro as 73% comes from top propensity scores

ActionAid Australia partnered with Dataro to test if machine learning could improve their important mid-year tax appeal. The challenge was to identify supporters with a high propensity to give, which would allow them to reduce mail volumes and save on campaign overheads while also finding new potential donors outside their usual criteria.

Dataro used machine learning algorithms to analyze donor data and generate propensity scores for each supporter. The results showed a strong correlation between high scores and actual giving, with the vast majority of campaign revenue coming from donors with the highest scores. Dataro's solution was so successful that ActionAid Australia is now working to integrate the propensity scoring directly into their CRM.

ActionAid Australia