With ever more pressure on charities to self police in their recruitment activity and growing backlash from the public, most charities have put on hold or severely curtailed their direct cold recruitment activity. Reciprocals (where charities swap their names)have died overnight and many charities are pulling their data from the cold marketplace.
In talks with the ICO, data compliance companies and the DMA, Marketing Metrix concluded that it is not ‘if’ positive opt ins will be mandatory, but when. This could be in the form of simply asking new donors to give positive consent for their data to be passed onto another charity, or even more restrictively to actually list the individual named charities that their consent is being given for marketing. Furthermore, this would almost not be permission in perpetuity, but for a set period of time, 3 years say, after which permission will need sorting again.
We think there is going to be pretty much a standstill in cold recruitment for the next couple of years so it will be even more important to maximise the potential of existing donors from charities donor bases.
So, how does a charity know if it is maximising the potential of its donor base?
This is where the Gini Coefficient comes in. The Gini coefficient was first published in 1912 by the Italian statistician Corrado Gini, the eponymous code is a simple way of ascertaining the income inequality of a nation. Scores range from 0 to 1, the higher the score, the more unequal a society and vice versa. For example, South Africa has the highest Gini coefficient at 0.7, making it the world’s most unequal society, and at the other extreme, Norway has a score of under 0 .5.
Having worked with a large number of charities Marketing Metrix recognised that some are much more efficient at raising money than others. In a similar way of distinguishing between inequalities between countries, Marketing Metrix hypothesised this could be used to measure the relative efficacy of donor files. This investigation revealed the Charity G Effect: In terms of income generation from their donor bases, the most successful charities were those with the highest Gini coefficients, whilst those with lower coefficients were less efficient. We applied this to manycharities who took part in the test and to our astonishment results were consistent.
One charity stood out with an extremely high Charity G Effect at 0.86, the International Committee of the Red Cross. The mainreason for this is that charities that have developed an effective donor strategy will eventually be able to identify a seam of high value donors and in doing so produce a higher coefficient.
So how can the Charity G Effect be used?
The measure can be used as a way of determining how much more can be raised from a charities donor base, this would give an indication of how the cold recruitment shortfall can be plugged in the short term. It is a quick and easy sense check for Marketing Metrix to assess how a charity is doing at the beginning of a working contract,and it can be recalculated to see how the effect changes over time. If the score is increasing then good news, if it’s decreasing then it could be that the marketing strategy has gone awry, or the donor base is full of one-time-givers.