Not for profit
In the same way that businesses are accountable to their owners, charities are accountable to their donors and Datamine has enabled many iconic NZ charities to ensure any expenditure of their valuable donor contributions has delivered the greatest possible return on investment.
ChildFund had experienced a dramatic increase in new child sponsors year on year - and expected a corresponding lift in donations as a result. However, donor revenue didn’t reflect this. New sponsors were not staying and the number of children in need of a sponsor was growing. ChildFund asked for Datamine’s help to discover why the organisation was experiencing a high rate of donor churn - and why the new donors weren’t contributing as expected.
Datamine took the following approach:
- Quantified churn over time and identified the specific time period when the churn rate at ChildFund increased.
- Investigated revenue changes and correlated that data with ChildFund’s known recruitment channels.
- Considered the effect of the acquisition channel on donor churn.
- Used Census data to provide a profile of donors in good revenue years and compared that with donor profiles during the downturn.
Datamine determined that revenues didn’t match the increase in sponsors for two critical reasons:
- The profile of the new sponsors showed that they were from a lower socio-economic background.
- These sponsors had been acquired through direct recruitment (approached on the street).
In essence, prior to the downturn ChildFund had made a strategic shift in its recruitment strategy and had decided to invest more resource into direct ‘on the street’ sponsor acquisition. The problem was, however, that these sponsors either couldn’t afford the sponsorship or simply couldn’t refuse signing up when approached in a shopping centre or supermarket.
The findings resulted in a total revision of ChildFund’s acquisition strategy with advertising spend being allocated more effectively due to ChildFund’s better understanding of its target audience.
Charities, like businesses in general, have limited resources – and in the same way that businesses are accountable to their owners, charities are accountable to their donors. To this end, the Wellington Cancer Society needed to ensure that it spent donor’s contributions wisely - and approached Datamine for assistance in ensuring its marketing spend delivered a positive return on investment (ROI).
To help the Cancer Society increase its campaign ROI Datamine profiled the Society’s existing donors - establishing what they ‘look liked’ and how they behaved. Using a combination of Cancer Society donor data, census data, Quotable Value NZ data, and the Deprivation Index, Datamine created profiles for five unique donor groups – from very high through to very low.
Using variables such as age, frequency of donations, occupation and property values, Datamine compared each of the five donor groups to the Society’s entire donor base (i.e. the average), and also to the greater NZ population. In addition, maps of the Wellington region showing the penetration and value of donors by geographic location were produced. Equipped with accurate donor profiles the Cancer Society was then able to make strategic shifts in its donor acquisition campaigns – much improving their targeting, relevance and effectiveness.
As a provider of services to people with intellectual disabilities and their families, IHC depends on its Smile Club members to donate a regular amount every month by direct debit or credit card. Administratively the Club is easy for IHC to manage and from an operations perspective, having Club members contributing automatically is the most efficient way to receive donations. With this in mind, IHC and Datamine embarked on a project together to more effectively target the prospects that were most likely to become donors and join the Smile Club.
Datamine constructed a predictive model to identify which meshblock’s (the smallest defined geographic area for which statistical data is collected by Statistics NZ) contained the most residents who were likely to become donors and long term members of the Smile Club. The model correlated IHC donor base data with Statistics NZ census info and ranked prospects based on their propensity to donate.
The Datamine model has enabled IHC to more efficiently target its most likely Smile Club prospects, resulting in more successful donor acquisition campaigns and a reduction of wasted campaign spend in areas with a low to moderate likelihood of conversion.