Blog Archives

Training a new data monkey – what would you recommend?

After a 4 month search, I have finally acquired myself a trainee data monkey. Now comes the critical question – how to train the monkey?

I’ve started by piling a number of articles and books on his desk! Here are a few that I consider ‘foundation’ pieces. I’d be most interesting in hearing from other fundraisers as to books, articles, blogs etc that you regard as essential!

Fundraising books

These would be my top 3 books for getting a good grounding in fundraising. What is your top 3?

The Fundraiser’s Guide to Irresistible Communications by Jeff Brooks.

Since hearing Jeff Brooks speak at the Fundraising and Philanthropy forum in Sydney two years ago, I’ve been a fan.

I love Jeff’s simplicity, his wit and most of all his dislike of brand gurus! I mentioned to a colleague that I had ordered a copy of Jeff’s new book and in response, they said to me that they expected it to be just a summary of what he writes on his Future Fundraising Now blog.

Only half way through the book, I can certainly say there are many familiar themes, yet I’m thoroughly enjoying it and I think it will be a fantastic book for my trainee data monkey.

Building Donor Loyalty: The Fundraiser’s Guide to Increasing Lifetime Value by Adrian Sargeant and Elaine Jay.

I first read this book about 6 or 7 years ago and its impact has never left me. My experience of fundraising texts to that point had been of rather vague prose banging on about how to make donors feel important.

This book combined definitive data about why donor loyalty matters with concrete strategies for improving it.

It remains a favourite to this day.

Relationship Fundraising: A Donor-based approach to the Business of Raising Money by Ken Burnett.

Many people recommend the work of Ken Burnett. He talks about donors as friends. When I first read this I thought it sounded nice but it didn’t actually click with me until I became a donor myself.

I support the Cat Protection Society at Enmore ever since I adopted my two tortoise shells from them in 2009. I subscribe to their facebook page and actually look forward to their facebook status updates telling my who has been adopted. I was asked to write an article for their recent book, Feline Friends, about my girls’ fascination with walking through my paintings while they are still wet. To my delight, it didn’t end up on the editor’s cutting room floor. When I approached them for an advance copy for my grandmother’s 90th birthday, they happily obliged.

I am a donor yet I feel like a friend.

Fundraising Articles

Of all the areas of fundraising, I find major gifts one of the hardest to find quality reference material. I’ve directed my new colleague to a most entertaining and informative series of blog posts by Jeff Schreifels from Passionate Giving.

If you haven’t seen 10 Reasons Why Most Major Gift Programs SuckI strongly recommend it.

Last but not least, is an interesting 2 part blog post on what makes a great database manager by Ivan Wainewright. I have to admit to reading this post with some trepidation as I am a database manager with no formal training in the area. I like the article because personally it pointed out some strengths I’d overlooked and highlighted areas where I can improve my skills.

I’d be really interested to hear from you – what books or articles would you add to this list?

A proud profession

A couple of years ago I was at the Fundraising and Philanthropy Forum and I heard John Jeffries of CBM give a presentation on the state of the fundraising profession. During this talk, he said something like:

No one leaves school and says, ‘yes, I’m going to have a career as a fundraiser!’

It would seem that being a fundraiser is not a sexy profession. At times the way people talk about fundraisers, I’m wondering whether the phrase should be ‘never discuss sex, religion, politics or fundraising.’

Recently personal experiences have shown me that far needing to whisper ‘I’m a fundraiser’, people should be shouting it from the roof-tops with pride.

I’ve always known that fundraising changes lives. There have been times when I’ve seen it’s impact.  Yet it’s only recently that I’ve really understood what ‘life-changing fundraising’ really is.

It took for a person dear to me to be in dire need of vehicle modifications in order to maintain his independence for me to really see how powerful fundraising can be.

Less than 2 months ago, I was sitting have a conversation with Andrew about his increasing difficulty lifting his wheelchair into his car. His struggle to get in and out of the car was getting too much. ‘I’ll just have to quit TAFE’ he said. ‘And organise some other way to get my groceries.’

With a price tag of anything from $8,500 up to $20,000, depending on the option he chose, it did seem hopeless.

I went away and thought about it. I wasn’t ready to give up. I came back and said, ‘you’re right, we mightn’t be able to raise the money, but I know I’ll always regret it if we didn’t try.’

—-

Little did I know that within 2 months, we would have already raised close to $3,000. We may only be a third of the way there – and what an emotional rollercoaster it has been – yet hope has returned.

When your profession changes people’s lives like this, then there’s plenty of reasons to be proud.

—-

Why disability databases are like fur seals

Need a fundraising database? No problem. There are plenty on the market to choose from. Ring around a few mates and you’re likely to find the same names popping up again and again. From the time you start thinking about a new fundraising database, to having it installed with all your data converted you could have given birth to a sheep or a goat. In less time that it takes for a human baby to grow you can have your fundraising database safely settled into it’s new nursey.

Yet there are two sides to most not for profit Organisations. The funds and the services. If a database for your fundraising team is as quick as having a goat, how long does it take to get one for your client services department? In my experience, 9 months can come and go and there’s still no database. That’s right. If you’re planning on birthing a client services database, then start making friends with fur seals, giraffes and elephant mothers-to-be as these will be in your mother’s group. I hope for your sake that it isn’t as long as the elephant (22 months).

Part of the problem here is that there are no usual suspects. Ring around other Not for profit Organisations and you will probably hang up empty handed.

Of course, I’ve made a huge assumption here. I’m thinking that fellow charities must be using a database to track their service provision. In your quick ring around and you may find out that the ‘database’ is the paper file. The ‘database’ is a few excel spreadsheets. Or my personal favourite, the ‘database’ is something that Jane’s husband made up in two days in Access because Jane’s husband is ‘good with computers.’ Does anyone know how to change it? Yes – Jane’s husband does. Oh great. Let’s hope Jane and her husband never get a divorce.

A year in the making

So where’s the good news? I thought I had it. I thought (stupidly) that because it took twice as long to implement a client services database that it meant it would all go twice as smoothly. Twice as long means twice as good, right? Wrong!

The issues of data quality that exist with most fundraising database transfers weren’t going to plague me. After all, we had hardly any data as it was all in those paper files.

The data quality curse

Yet it seems the data quality curse knows no limits. The same curse which causes your fundraising team to put Mr & Mrs Jones on one client record, infects the clinical department as well. I’m hoping that I have the power to stop it before it gets too bad but the signs are all there.

Take this simple example. The humble look-up list. When you open your fundraising database and pull down the ‘Title’ field, if it’s been through multiple data conversions without a data tyrant at work, you’ll have an abundance of choice. In addition to the usual Mr, Mrs, Miss and Ms, it’s likely you have Rev and Reverend, Sister and Sisters, Mr&Mrs, Mr/s, Householders and my favourite Mr 7 Mrs (where someone forgot to press Shift for the ampersand).

In the case of Title, there are standards. It’s easy for a data monkey to come up and fix them all up, however what does one do for diagnosis? Or disability?

Other. It’s the answer to everything. When you just can’t decide, go with Other. If I had money for every time someone had asked, why can’t we just have Other and then write what it is, I’d be buying a house with a pool big enough to house a fur seal.

To be fair, some of these things aren’t easy. While there is an Australian standard for language and country of birth and ethnicity and god knows what else, there is not one of recognised ‘disabilities’. Or at least not one I can find. (For anyone looking the best I can find is a list from the Department of Family and Community Services of conditions recognised as eligibility for the carer’s pension. And if anyone has found one on the Australian Bureau of Statistics, or elsewhere, please send me a link!)

Another little trick the data quality curse has up it’s sleeve, is the multi-talented data field. This is a little like a bunyip, a yowie or a yeti. It must exist as people talk about it but I’ve yet to see one! It’s that field that magically transforms itself as the user’s will. When people don’t feel like typing a date, it undergoes a metamorphosis and becomes a text field. Just the other day we were having a discussion about when we should enter a date and someone came up with an ‘exception to the rule’. As it was a date field, their usual request of Other was null and void. Instead they called in the multi-talented data field and suggested they just put an asterisk after the date. Never mind that a date field doesn’t allow such deviation… the multi-talented data field lives on and intuitively changes itself to allow such a thing. Pity it doesn’t also create a data dictionary definition which explains what the asterisk actually means.

But there is one more trick the data quality curse has up its sleeve. Worse that ‘Other’ in look-up lists and data fields which can magically transform themselves from date to text is the third weapon in the arsenal. The shoehorn.

This has to be one of the most used and most spectacular methods of creating a big data quality issue. It’s when you don’t have a home for something in your database, so you find another field you aren’t using and you shoehorn the data into it. This is common when Jane’s husband built the thing and now he has run off with the massage therapist to outer Mongolia and no one knows how to change anything. This is how you end up putting the mobile phone number in the medical record number box. Or the word deceased in the title field as he forgot that us humans are mortal. And if you’re looking for the name of the next of kin, try location. Obvious really.

Loving your inner database: a small rant

Someone asked me the other day ‘how are you finding your fundraising software… because I was talking to [so and so] and she hates it.’

I went away and thought about this. What I was left with was the question: when was the last time someone told me they loved their fundraising database? Then I re-phrased the question to: when was the last time someone told me they loved any database?

People are the most in love with their database when they don’t have it yet. Yes, that’s right. When they don’t have the database, they love it. The ‘new’ database has so much promise. We dream of it curing all the problems the present one has. We peg our hopes and aspirations onto that new database and hope that we don’t end up comparing our situation to pin the tail on the donkey later.

Fundraising databases are particularly dangerous.  I say this because money is involved. I refer not to the purchase price but to the funds the database will generate. I hope someone did a double-take there and re-read that sentence. If you didn’t, let me rewind: ‘the funds the database will generate’. Poor quality fundraising databases can be very costly indeed. They frequently lead to missed opportunities, over-mailing or under-mailing and good old fashioned time delays. However the thought that a database generates money doesn’t sit easy with me. Fundraisers generate money; databases support you to do so. This may seem like quibbling; a pedantic nature, call it what you will. This nitpicking comes from seeing fundraisers promise a new database will turn a ship around when, in reality, it’s going to be a new ship with the same old people doing the same old thing.

Let’s imagine for a moment that there were 3 levels of fundraising software out there. I’ll be really scientific: let’s call them the ‘good’, the ‘average’ and the ‘bloody frustrating.’ The Free the Flamingo Foundation has a ‘good’ database and the Quidditch Mission has an ‘average’ database. In this case, it’s a fair assumption to think the Free the Flamingo Foundation would be faring better. That could well be so, however, we should not forget that an ‘average’ or even ‘bloody frustrating’ database managed well, could easily beat a ‘good database’ managed poorly.  I’m not suggesting that a charity should settle for an average database on the premise that if it’s managed well, all is fine. What I am trying to draw attention to is the role people play in making fundraising databases a success. These ‘things’ that we spend our days using, cursing, ignoring or embracing are a lot like the human brain: we generally only use a very small percentage of them.

So next time someone asks me how in love – or in disgust – I am with my fundraising database because they ‘hate’ theirs, I’m wondering how I can – without offending them – ask whether the database is really the problem? When the database IS the problem, there is nothing for it but the axe. When it isn’t, it’s just sad to watch all the energy of fundraisers funneled in to hating their software, rather than loving their jobs.

 

 

 

A premium cynic

Cynicism is a good quality for a data analyst to sport. Lately, I’m sporting it in spades.

The focus of my current cynicism is an article in the Feb/Mar edition of Fundraising and Philanthropy magazine by Sean Triner of Pareto. It claims that the difference in renewal rates between premium acquired and non-premium acquired donors is minimal.

To my mind this seemed contrary to what I would expect and what I’ve read on the subject. Take this snippet from an article on the Agitator by Tom Belford:

Now, I’m not a fan of premiums, period. Yes, I know they can lift response (not always), but they’re prone to generating low value, low loyalty tippers. So analysis of lifetime value usually indicates a rather poor return compared to non-premium responders.

The stock standard response to complaints about poor conversion appears to be to continue to incorporate premium / freemium elements in the follow-up packs.

This is certainly the view of David Hazeltine who says: ‘so what?’ Send them another premium if that’s what it requires.’ Similarly, a convio study shows some increased renewal figures when a link back to the premium acquisition pack was included. That said, the convio slidedeck also features some data which supports the view that premium acquired donors are harder to renew and retain, with a smaller window of opportunity to boot! (You can see the convio slidedeck at: A New Donor is Like a Blind Date).

My experience to date (with more than one charity) is that the difference in renewal rates is anything but minimal. However, perhaps what the Pareto article is suggesting is that when it is all said and done, the difference in renewal rates is not sufficient to dismiss the use of the premium acquisition packs. If response rates are sufficiently higher, even with a low renewal, the ROI may come out markedly better. My only question is for how long?

Lastly, I have to throw in this one. Not because it has anything to do with premium acquired donors. It’s because it proves cats rule. Or at least, cat owners rule when it comes to donations. If I ever work for an animal charity, that knowledge may come in handy. Until then, I can just smile knowing feline owners are superior.

The nuclear fundraiser: 3 figures every data analyst should know

Next week I’ll be attending one day of the Fundraising Institute of Australia’s conference. After some recent interactions with fellow fundraisers, I’m walking into this conference trying to prepare myself for anything. I wouldn’t be surprised if the next fundraiser I met was a nuclear physicist in a former role, a funeral parlour director or a pole dancer.

It seems John Jeffries, the CEO of CBM is right. To paraphrase what I heard him say once: no one leaves school and says ‘I want to be a fundraiser.’ I certainly didn’t! (This is, of course, presuming that as a database manager / data analyst, I am a fundraiser. But that’s a whole different debate).

Given people don’t seem to ‘decide’ to become a fundraiser, people certainly don’t go to ‘fundraising college.’ When I think back to when I first started working with fundraising data, I could have benefitted from a few ideas of where to start. In that vain, I’m offering up the 3 figures every data analyst should know.

Figure 1: How many active donors do you have?

I know, this seems so basic but you’d be surprised how many people have trouble answering this question. The trouble comes not from inadequate databases (although this can be a factor and certainly a good excuse!). It usually comes from a lack of clarity about what an active donor is. Whether you decide an active donor is anyone who has donated in the last 6 months, 12 months or 24 is not nearly as important as picking a definition and sticking to it. Once a charity does this, it can know over time whether it’s going up, down or to planet Jupiter. The latter could be interesting but I’m sure your board of directors would prefer you were going ‘up.’

Figure 2: What ‘types’ of donors do you have?

When I say donor type, I’m not referring to whether they are companies or individuals. I’m also not referring to whether your donors are the ‘glass half full’ or ‘glass half empty’ types. Quite simply: it is what methods do your donors respond to or support? (There’s probably a far better word than ‘type’ for this; however it eludes me at this time. Perhaps I should have substituted that word for any random word… like ketchup maybe?)

Typical ‘ketchups’ include: Regular Givers/Pledgers, Community Fundraising Sponsors (e.g. city to surf; host a morning tea; the office staff come dressed as an antelope day… that kind of stuff…), Eventers (dinners, lunches, balls, high tea… you know the kind), Direct Mail/Marketing responsive donors), Bequests etc.

Why do you care about ‘ketchups’?

It can make an enormous difference to your results. At the very least, I think every analyst should know how many donors they have who have DM responsive, regular givers and then, if you like, the rest. If they can tell you more than that, woohoo! Chain them to a desk and don’t let them leave – they’re a keeper. (For the record, I’ve only managed to get clear in my head DM, RG and the rest, so I’m certainly not chained to any desk… yet).

Figure 3: How ‘matured’ are your donors?

I hear the word matured and I think of a fine cheese, or a red wine. With the utmost respect, I’d like to say that donors are similar. Let’s presume that we have two charities. For the first, I’ll use my fictitious charity – the flamingo protection foundation; the second, I’ll call the Quidditch Mission.

Each has 5,000 active DM responsive donors (defined as anyone who donated in the last 12 months to a DM campaign). For the sake of argument, let’s presume each charity deploys the same fundraising strategy and activities for 12 months. Let’s even presume that the donors give exactly the same average donation over the next 12 months and I’ll make that an even $100.

At the end of the 12 months, the Flamingo Protection Foundation has raised $350,000 from the donors who were active at the start of the year and the Quidditch Mission has raised $200,000.

They started with the same number of donors, did the same thing and got the same average donation (in my hypothetical world). So why are they so different? Quite simple: the Flamingo Protection Foundation donors were more ‘matured’ than those from the Quidditch Mission. Translated into numbers, those who save Flamingoes from the evil clutches of the red queen for croquet enslavement ‘renew’ at a rate of 75%. These are donors who were not ‘new donors’ in the previous year. In fact, it’s unlikely they were even ‘new’ the year before that. These people have been around for some time just like Alice herself. The Quidditch Mission donors on the otherhand are relatively ‘fresh’; a more recent invention. These guys only renew at a rate of 40% in the first 12 months and therein lies the difference. (To be more realistic, the flamingo supporters would probably also give a higher value of donation than the broomstick soccer nuts but let’s just glance over that).

So, that’s figure 3. Go quiz your data analyst and see whether they can tell you (in raw numbers or in percentages of active donors) how ‘mature’ your donors are. If they don’t know; ask for the retention rate. That alone may give you an indication. If they can’t give you either of those numbers, then I think we’ve located someone who was a scuba diving trainer in their former career and has yet to adjust to fundraising data analytics.

Data Segmentation, Profiling and Analysis

Data Segmentation, Profiling and Analysis. That’s the title someone has given a presentation that I will be giving next week. Gulp.

I have 25 minutes to discuss segmentation, profiling and analysis in fundraising. Double Gulp.

People can spend days, even a week discussing this. What pearl of wisdom am I going to deliver in 25 minutes? Don’t get me wrong. I’m not saying that if I had longer, I’d offer up any better shiny object. I am questioning what I am going to offer up at all.

Those who know me, will be more than aware that I’m not short of a word on the subject. Those who know me are also aware that I can be reasonably quirky. I try as much as possible to make presentations about data slightly more interesting than cutting your own toenails. By way of example, my last presentation on data involved a toddler sized purple bunny being hurled across the room. At the very least, anyone who was asleep had the very real chance of being hit in the head with presentation collateral.

As I’ve been invited to present as a guest, perhaps this isn’t the best idea. I’m not sure the hosts will look favourably on flying bunnies. Might be an occupational health and safety issue. Unless I get very small and soft rabbits.

My only idea at the moment is to make the ‘presentation’ a little more of an interrogation: where I get to do the interrogating of course! ‘Describe your segmentation of your Christmas appeal’ may yield some interesting responses. Or not as the case may be. Such an approach means a lot of thinking on my feet. This could get me into hot water as thinking on my feet sometimes leads to them being in my mouth. Yet I’m fast realising that the risk of me looking like a goose may be worth it if it results in something more engaging than another data geek with a powerpoint presentation, or prezi, which I think of as powerpoint for those who don’t get motion sickness.

My other fall back options won’t work. Plan a is to pay out marketers. This may be a big mistake in a room likely to be sporting the odd marketing refugee. Then again if I deploy some of that analytical technique I’m supposed to be sporting, I can ‘segment’ the room and assess how many fundraisers we have versus other marketers… like the dreaded brand manager. They’re probably fair game if we have a strong weighting towards fundraisers. I’m racking my brains to try to think of a scenario where the brand manager and the fundraiser were friends. (I’m lucky. We have no brand manager at work. Ergo we have no conflict).

Plan b is to adopt my usual sarcasm about text fairies, murderous databases and colleagues who stuff people in freezers. Actually, this could work. They’ll pronounce me insane within 5 minutes and we’ll spend the next 20 waiting for the little men in white coats to take me away. All that without even packing the flying bunny rabbit.

So I’m back where I started: Data Segmentation, Profiling and Analysis.  Gulp.

Data Mining for Fundraisers

I know, I know… it sounds like you’re in for a boring post. ‘Feeding your brand manager to the lions’… now that would be a good title for a post! But alas, ‘data mining for fundraisers’ it is. Why? It’s the name of a book I just finished reading. Well, actually it’s the short name. The full title is: Data Mining for Fund Raisers: How to Use Simple Statistics to Find Gold in Your Donor Database-Even if You Hate Statistics‘ written by Peter B. Wylie.

It is a fantastic book and here’s why.

  1. It’s short. Who wants to read a tome on data mining in the hope that it will enhance your Organisation’s fundraising. This book is under 100 pages and in my opinion, teaches far more than many books do which are four times the size.
  2. There’s not an RFM, LTV, LYBUNT in sight. Well, there may be the occasional reference to such things… but for the most part this book is about data mining. This book is about finding donors in your database who will end up with a brilliant RFM score long before they have one.
  3. It’s practical. This isn’t a text book. It’s more like a tutorial. The chapters are even called ‘step 2, step 3…’. It is a book designed to be put into practice.
  4. The author is a pragmatist. When you get to the part of ‘significance’, he tells you that you can run a chi-square test, or run the ‘wow, look at that difference style test’. I cannot tell you how wonderful it was to read a book written by someone with over 35 years of statistical experience telling me that it was ok to skip the significance testing and go with the ‘gasp, isn’t that a brilliant difference’ style approach.
  5. There’s nothing new here. This may sound like a strange ‘plus’. Let me try to explain. This book is consistent with so much of what I have read and done over the years in my roles which was very comforting. I didn’t go to ‘data monkey training school’. Sometimes I think I should have more of a background in statistics or IT to do the work that I do. Yet the idea of either bores me to death and I have clung to experiences where I’ve come across someone with those qualifications who, at the end of the day, was quite ineffective. Reading this book assured me that a qualification in stats is not essential. This showed me I’ve been on the right track, filled in a few of the missing pieces and gave me a structure for building a predictive model.

So I say to Mr Peter B Wylie – thank you! A handy little book that I will revisit time and time again.

Miss Milly sells spats to snakes

I have a colleague who could sell spats to snakes. I once had a boss who was similar. A mate said of her ‘she could say you had two months to live and somehow you’d think that was good news’. Indeed when I think of former boss and current colleague – who I’ll call Miss Milly – they both had a similar way of smiling at the very moment you wanted to scream at them. They repeatedly have that ‘surely that can’t be too hard’ expression?

It’s Miss Milly who convinced me that it was ok to implement a new fundraising database (aka big bird) AND within a few weeks kick off an acquisition campaign, a supporter survey, a few random eDMs and a step up in the community fundraising activity. I have no idea how she managed to hoodwink me into this one but as I say, Miss Milly could convince you to put a screen door on a submarine.

To be fair, Big Bird is weathering the storm quite well. He’s only 3 weeks old and we are certainly making him run. I can tell I’m in for a chaotic couple of weeks. I already am telling myself ‘when I get through these few weeks I’ll have time to sit-down and learn how to use our new database better.’ I am of course delusional because when I get to the end of these few weeks, there will be Miss Milly and her smile and two words… Christmas Campaign.

Costing Big Bird

Today I have a question. How do you cost how much a database is worth to you?

When people build business cases for boards they often quote how much more efficient their new database will be. In my most recent circumstance, Barry was so bad that there was no argument he needed replacing. However I find myself thinking, now that I have big bird, how will I measure the ‘savings’ he brings to the business.

If there are any data monkeys out there who have database return on investment down pat, I’d love to hear from you!

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