Value

What about converting to Regular Giving?

Ranking

Key takeaways

The data

Where’s the value?

So far we’ve focused on the frequency of donations rather than value, as typically response rates are far more elastic than average donations values. However to get the complete picture we now compare a recruit’s financial gross value over time.

The mean average of five year gross income excluding the initial recruitment donation across all supporters is £94.16!

If we look at the chart below we can see how this value differs across market. It shows the average cumulative value per recruit by market, stacked by the average contribution within each year. These values take into account those supporters who didn’t give an additional post recruitment donation – simply the sum raised divided by the count of recruits. The charts exclude the sum of income from the initial donation at the recruitment stage.

It’s worth noting that CHE (Switzerland) shows a very high average 5yr contribution. This market only had three organisations, however the lowest of the three organisations had an average contribution higher than £150.

The chart below shows the range of performances of different organisations, represented by a circle, within each market, allowing us to see the median rather than mean average plus the quartile range. And by hovering over each circle you can see some key metrics for that organisation including give again rates and average age.

Channel & age

We’ve previously seen that recruitment channel and age of the recruits are two of the most important factors that determine a recruits future behaviour, so the following two graphs ‘break out’ the average financial value by channel and frequency of donations, and then look at age band and frequency of donations.

The channel graph shows an inconsistent pattern regarding digital verses non-digital recruits, but we do get an important understanding of how value increases depending upon the frequency of donations.

In contrast we see a very clear pattern when we look at the recruits age band, with a steady increase up to 75 year olds, after which the average value declines slightly.

Combining factors

To bring all of these factors together we have a grid of smaller charts which has age band on the X axis and shows value for combinations of recruitment channel and frequency.

Two insights leap out of the chart above.

Firstly, the consistent picture that in all scenarios average value increases with age up to the last band of 76-100 which drops slightly.

And secondly that recruits acquired through digital type channels have a higher average value than those recruited through non-digital channels – in contrast to the story that emerged from looking at only giving frequency!

To explore this a little more the next graph goes one step further and looks whether this is skewed by a higher proportion of digital recruits being recruited at higher values.

By selecting a different recruitment gift value band in the selection box we can see the relative value contribution between non-digital recruits and digital recruits. While there are slight differences across the recruitment gift value bands, I’d suggest there is no clear reaccuring pattern to suggest recruits acquired through digital type channels have a higher average value than those recruited through non-digital channels.

How value grows overtime

The chart below visualizes how the cumulative value for each market changes during the five year period. You’ll notice that the order of the markets changes indicating that markets do perform at different rates at different stages post recruitment

How do subsequent donation values match recruitment value?

We wanted to see the relationship between the value of a recruits recruitment gift and their subsequent donation. To do this we’ve isolated only those recruits who made one single gift donation post recruitment, so a sub set of the overall dataset.

Interestingly we see a relatively fixed pattern across al of the recruitment gift bands, that among supporters who made one single gift post recruitment, approximately 80% of recruits gave in the same value band OR a lower value band than the value band of their recruitment gift. This leaves 20% to 25% who gave in a higher value band. There is a slight trend that the lower the recruitment value the higher the proportion who gave less for their next donation.

Change by proposition

Within this group we also spotted that there does appear to be a significant difference between those supporters who were recruited via a emergency proposition compared to a non-emergency proposition. Across all value bands those recruited on an emergency proposition had a far higher proportion whose next donation was within the same value band.

Relationships

Gross Income by mean number of donations made

So a crucial question is whether we can evidence that there is a strong relationship between the average number of donations made to an organisations, and the gross income they generate.

The chart plots each organisation and substantiates the relationship between the mean frequency of donations and gross income with a Pearson correlation score of 0.73, indicating a strong relationship, and an R squared value of 0.53. This is what we would have expected.

Gross Income by Give Again ratio

This time we wanted to look at the relationship between gross income generated and the proportion of recruits who made one or more post recruitment single gifts.

Grouping recruits by organisation we substantiate the relationship between the Give Again rate (in any year) and gross income with a Pearson correlation score of 0.71 indicating a strong relationship and an R squared value of 0.51.

When we alter the metric from Give Again in any year, to Give Again in yr1 we see the strength of correlation fall from 0.71 (Strong) to 0.53 (moderate) with a R squared value of 0.28, meaning there still a relationship but its of lesser importance than Give Again in any year.

From Single to ‘Regular Giver’

During the 5 year period from 2018 onwards the proportion of Single Giver recruits that were subsequently converted to a Regular Gift was 4.59%. As we’ll see below this average differs considerable depending upon factors including market, organisation, by the age of the recruit and the number of times they gave a single gift.

Conversion by market

Looking by country the conversion rate ranges from 1.2% in Australia through to 12.8% in Brazil! For this metric looking at the average by market may give a overly simplistic reading however the box plot graph below shows the performance of individual orgs within each market and we can see a wide range of organisational performance within each market.

Given the financial benefit of converting single givers to regular givers, it may raise questions among fundraisers within those markets towards the bottom of the chart – how are markets from different regions achieving twice or more the proportion of conversions? Is it the frequency of conversion campaigns, the performance of those campaigns, or what if it reflects cultural differences in the appetite for regular giving?

Conversion by organisation and market

When we consider the median for each market we can see the majority of markets at around 5% or below.

Conversion by organisation

If we look at the distribution just by organisation we can see the majority (54%) of orgs falling between 2% conversion and 5.99% conversion, and a 70% majority having a conversion rate under 5.99%

Conversion by channel type

During this article we’ve seen important differences in the performance between recruits acquired through digital type channels and non-digital type channels. This is also the case for converting single givers to regular givers. In all markets except Denmark, Spain and Sweden, recruits from digital type channels display a higher conversion rate than those from non-digital channels. And in some markets this difference is highly significant.

It’s worth noting that this may be due to differences in communication strategy for each type of recruit, for instance digital recruits have been asked more frequently to convert to a regular gift.

Conversion by age band

When we look at the comparison of conversion rate by age band we see the same pattern between digital and non digital recruits – that it’s the younger bands who have converted at a higher rate.

However, it’s worth reminding ourselves that this percentage rate reflects the proportion who have been converted and not the conversion rate for a specific or average campaign rate. As we don’t have the communications history we’re unable to assume that supporters across all age bands received the same number of requests to convert, nor that if they were sent a conversion appeal it was through the same channel.

Do emergency recruits convert differently?

We were surprised to see that the conversion rate for those recruited through an emergency appeal was near identical to recruits acquired through a non-emergency proposition (4.4% to 4.6%), so we can say (other thing being equal) that recruitment proposition makes little difference in conversion.

However this is not the case for all markets, as the chart below shows with Spain, Italy, Korea and Sweden have conversion rates for emergency recruits far higher.

The role of SG giving on conversion rate

Below we look at whether the percentage of recruits converted to RG differs by the number of times the recruit gives a single donation post recruitment. And clearly there is a general pattern that frequency of SG has a positive relationship to conversion.

It’s worth mentioning that the number of Single Gifts made was not necessarily prior to conversion – in fact a high proportion of conversions were made either to recruits who failed to make any single gifts after their recruitment, or to recruits who at the time of conversions had yet to make any single gifts but went on to do so after conversion.

Time to conversion

Two surprises here – firstly that the average across all markets was 23 weeks, and secondly that the average number of weeks by market is surprisingly similar with the majority of median values within 5 weeks of each other.

While the mean average is 23 weeks the chart below suggests this may give a false impression of when people get converted. For instance we can see that on average 11% of all converts did so in weeks 0-4.

How much more are RG converts worth?

Guess what – the gross value of a recruit who went on to convert to RG is worth on average approximately 3.9 times the value of those recruits who did not convert! This is comparing only those single givers who made one or more donations post recruitment. So the average gross income of a single giving recruits who does not convert was £248, but this jumps up to £963 if they are converted to an RG gift.

The next chart shows the index for each market of SG value to RG value, with the lowest being 3.2 times non converts value, up to a huge 13.7times in Taiwan.

Below we can see how this differs by market and perhaps the most interesting observation is that in all markets except Spain and the Netherlands the average amount contributed through single giving donations is greater for those who convert to Regular Giving than those who do not convert and remain as Single Giving only. In other words those who converted were the better performing supporters in terms of single gifts.

Income contribution

The fact that converts have a higher value than non converts is no surprise of course – but what did make us sit up was that the value of regular income accounted for 24% of the total income (SG + RG). Given that the average conversion rate was less than 5% it confirms (if confirmation was needed) the huge importance that a successful conversion programme makes to the profitability of individual giving overall.

To consider the importance of RG conversion lets look at the contribution that the RG income makes at the market and organisational level. Grouped by market, for each organisation we’ve calculated the total income (single giving + regular giving) contributed by the recruits in 2018.

The graph shows what proportion of this income that comes from the regular giving contribution. Overall it accounts for 24% of the total income, but for a good number of organisations the RG income exceeds the SG income!

Comparing conversion rates with income contribution

If we plot for each organisation the proportion of recruits that were converted to Regular Givers, and the proportion of their total income from these recruits (Sg + RG) that came from RG income we see a strong correlation of 0.59.

It’s worth mentioning that the average value of each monthly RG payment was £21.9 – with relatively little differences by market, by age group and other factors. The only factor we observed that did show a clear pattern was the recruitment value band . The pattern does differ by market so the chart enables you to specify the market you wish to be shown.

As you’d expect the count of recruits within the higher recruitment bands can be quite low – so by hovering over the column you can see the count at each value band.

Which came first?

Overall among those who were converted to an RG, 65% were converted before they gave an additional SG, while 33% did give an SG before they converted and 2% converted and gave their first SG donation after recruitment in the same week – presumably from the same request and perhaps indicating a coding issue with the cash donation being the start of the RG. This does have operational questions regarding campaign selections. Whether manual or via modeling are your selections for RG conversion based on SG recency and frequency! If so, perhaps you’re missing out!

One of the observations that I thought most surprising was the high proportion of SG recruits who were converted to a regular giver BEFORE they made an any single gift after their recruitment.

I did wonder whether those who converted prior to giving a single gift after recruitment was due to a communications journey with the tactic of using a RG rebound campaign to get conversions very quickly after a new recruits acquisition – however across all markets the median range was between 17 and 23 weeks – so not really any different to the average number of weeks for conversion for any recruit, regardless of whether they had given a single gift or not!

Ranking

Let’s bring it all together and offer some indication of how different markets perform relative to each other.

We selected five metrics which are good indicators of overall performance and then ranked each marked based on its average value for that metric – so the market with the best performance for that metric was awarded the rank 19, and the market with the lowest awarded rank 1 (we ranked in a counter intuitive way as visually it seems to make more sense!)

It worth mentioning of course that by basing the relative performance on a rank it doesn’t reflect the scale of difference in actual performance between markets.

Note – if you wish to directly compare two or three markets switch the chart type to COMBINED and deselect the markets you don’t wish to include using the market code in the legend.

Key Takeaways

Thank you for taking the time to explore our examination of single giving performance across multiple countries – we hope you’ve enjoyed it and gained some useful insights!

We started this project to explore whether we could find evidence that charity brands displayed the giving patterns suggested by Ehrenbergs theory of Double Jeopardy – that big brands are big because they have more supporters AND that those supporters give more frequently than smaller brands. Well we’re the first to admit that we haven’t properly analysed the data in such a way that allows us to conclude one way or another. We can however say that we’ve found some interesting patterns of behaviour and begun to understand which factors do strongly correlate to performance.

When it comes to charity size one interesting question is ‘do larger charities generate more value per recruit than smaller charities.’ And we can answer that the correlation at 0.21 is quite weak and suggests that while size has some influence there are other factors with far stronger effects

We have found that the differences in post recruitment giving frequency across the organisations statistically significant. With some organisations significantly better at driving ongoing single gift donations than others.

Using a Two factor Two-way Anova we identified that the primary key drivers of differences between organisations were the age of the recruit at point of recruitment and whether they were recruited through a digital type of channel or a non-digital channel type. With non-digital recruits making more post recruitment single gifts than digital recruits.

Other factors including the size of the organisation (represented by the single giving income in 2018, and the total individual giving income in 2018), whether the recruit was acquired using an emergency verses non-emergency propositions were not found to have made a significant difference to organisational performance of single giving frequency.

About the data

Source

We’re incredibly grateful to the IFL Forum for supporting this analysis and giving us permission to publish this ‘deep dive’ into the behaviour of Single Giving recruits.

The data has been collated from the INDIGO benchmarking study – globally the largest study of its kind. The INDIGO study is run by Adroit on behalf of the International Fundraising Leadership Forum (IFL Forum), a peer group of international fundraising directors in some of the world’s biggest NGOs and UN agencies raising funds from individuals, companies and foundations in multiple markets or markets.

INDIGO is an IFL Forum study of Individual Giving behaviour across different organisations and markets.   The study is built from anonymized donor and gift records stretching back for the previous 6 calendar years. For the INDIGO study Adroit audit, collate, model, analyse and present the data to draw out key insights. Typically, over 1 billion gift records are processed on 80-90 million individual donors.  This is shared via Power BI reporting as well as webinar insight sessions with members from each market enabling organisations to understand market level trends and make peer comparisons, providing insights into donor acquisition, retention, upgrades, reactivation, life-time value and many more metrics.

For more information about the INDIGO study please click here

Composition

The dataset used for this analysis focussed upon the transactional behavior of Individual Giving supporters recruited in 2018 to the organisations included and were acquired from a single ‘one-off’ donation. Supporters whose recruitment donation or subsequent donations were over $2000 were excluded. Checks were included to identify any obvious miscoding of single gifts and outliers, and these contacts were removed bringing the number of supporters included from the initial 1,000,000 to 997,152.

The data from 75 organisations from 19 countries (markets) were included in this analysis. An important similarity between the organisations is that their main focus is upon humanitarian aid, disaster relief, development issues, human rights and/or the environment.

Analysis and commentary were written in June 2025 by James Long with support from Ella Briggs and Alexis Jones

Notes

Pearson’s correlation scores

Pearson’s correlation score measures the strength and direction of a linear relationship between two variables. It ranges from -1 to +1:

• +1 means a perfect positive linear relationship
• -1 means a perfect negative linear relationship
• 0 means no linear relationship

R squared values

R-squared (R²) is a number between 0 and 1 that shows how well data fits a statistical model. For fundraisers, it tells us how much of the change in say donations, can be explained by a factor you’re analyzing—like marketing spend or age

For example, an R² of 0.8 means 80% of the variation in donations is explained by your model, suggesting a strong relationship. A low R² means other factors are likely influencing results.

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