Seize the data; why charities need to capitalise on the information they collect

Seize the data; why charities need to capitalise on the information they collect

“You can have data without information, but you cannot have information without data.” (Daniel Keys Moran)

The latest trend in sales and marketing talk is “big data”. It’s a simple enough proposition - the idea that the vast amount of consumer behavioural data now available to companies can revolutionise the process of targeting and selling goods. It’s easy to see how this can be attractive, both for companies and charities. So how should charities go about getting the best out of the data they've collected?

The classic advertising dictum is that “half the money I spend on advertising is wasted; the trouble is I don't know which half.” Well, according to recent research by Rex Briggs, that’s close enough - around 40% of marketing spend by companies is being wasted, up from 37% five years ago as consumer behaviour is shifting faster than marketers can keep up with. Data-based consumer intelligence promises to cut wasteful spending by replacing gut instinct with evidence-based actions. Any fundraising manager would be delighted to be told a way to cut 40% of her spend while keeping the same returns!

Big corporates have been leading the way when it comes to turning big data into big profits. Supermarkets regularly use their vast amounts of transactional data (thanks to club cards and similar programs) to target offers and discounts to consumers. Famously in one American case, Target’s database had worked out that a teenage girl was pregnant from her purchases. Her father was yet to find out and was outraged when she started receiving offers on pregnancy and maternity related products!

Online retailers have taken big data marketing to another level. Amazon have access to a wealth of data that most shop owners could only dream about – imagine a real world book shop being able to access data on which books caught people’s eye, how long they spent looking at the blurb on the back and how long they spent in the shop. Amazon’s sophisticated data analysis allows them to generate recommendations on the fly and even offer personalised prices based on your average spend and how much you shop around.

Of course, it is much easier to collect data than it is to use it. Think of the data that your charity collects every day. Supporter information, donation values, donation types, website visits, email click-throughs, social media interactions and countless more. You have much more information on the behaviour of your supporters and their engagement with your charity’s communications and fundraising efforts than would have been conceivable twenty years ago. But how much of this is just collected for its own sake? And how much of it is just sitting on a server or occasionally passed around without context, analysis or explanation to an uninterested team?

The problem is that having this data in itself isn’t much use – it’s like sitting on top of unused oil reserves. The oil is no use to you unless it’s extracted, refined and put to use. Piles of data are no use to your charity unless they are analysed, interpreted and converted into meaningful insights. While some charities are masters of database marketing, I suspect that a lot of charities are better at generating and accumulating data on their supporters than they are at actually putting it to good use.

There are good reasons for this of course – as always in our sector, money is a limiting factor. Investing in the right systems and people who can make sense of the data you have is not cheap and it might not be popular among conservative boards and donors suspicious of any overheads. Walmart generates data on over a million transactions an hour and has a database of 2.5 petabytes (2.5 million GB!). Naturally, this doesn’t come cheap and neither does a vast team of data scientists and analysts to interpret the data and turn it into actionable results.

So what can you do if Amazon-style database interrogation is beyond your means for now?

The first step is to simplify. Decide which metrics are most important to you, track them and integrate them into your systems. Build a plan for how to use your data – and make sure that it matches your capability to implement it. Biting off more than you can chew is a real risk, so start with “small data”!

Finally, remember that as powerful a tool as big data is, it has its limitations. Endlessly working your database can tell you a huge amount of information about a comparatively small number of people who are already engaged with your organisation. To get a broader picture, you need to combine data analysis with other techniques. Market research can help you broaden your base and spot opportunities you would never have seen from your database alone.

At nfpSynergy, we know that the most useful projects we can run are those that can map insight from the wider world back to our clients’ databases. It combines the best of both worlds.

 

Did this contribute to your data-day life? Or is this disinformation? Leave us a comment below.

Submitted by Adrian Salmon (not verified) on 14 Jun 2013

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You know, I'd love to think that we in the charity sector were assiduously collecting and storing all this data, but I suspect the opposite is the case. Tons of valuable data discarded each day because no-one's thought through the value of keeping it, or the charities just aren't resourced to handle it. Letters sent in with gifts not stored on the database because they're just 'white mail', web visitor stats not stored on the database because the website doesn't link to the fundraising database - I could go on and on..
Many charities don't even know the ages of their supporters and have to guess. Dates of address changes not stored - although someone who's recently told you they've moved is 11 times or so more likely to give than someone who hasn't. Would you agree?

Submitted by Anonymous (not verified) on 17 Jun 2013

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I'm sure that it is true of some organisations, though it's difficult to know how widespread it is. In some ways I wonder if it's actually worse though to go half way and waste time and money on accumulating data without using it?

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