Are you tracking these 3 essential types of digital fundraising data?

As a fundraising organisation, your website acts as a net in which you can collect donations. And, just like any net, there are gaps.

The good thing about a digital net is that it’s relatively easy to close those gaps, allowing you to retain more donation revenue. There are a variety of different ways to close such gaps.

One is to be conscious of the natural cognitive biases that impede good data collection and analysis. One of those biases is known as the streetlight effect. It’s a phenomenon in which we severely limit our searches, only looking where it’s easy and convenient, and often adversely affecting the outcome of our exploration.

Sometimes that streetlight effect is a way of reducing mental or emotional effort. But in other cases, it’s completely unconscious – we restrict our own search (in this case, our search for data) because we simply don’t realise it can be more thorough.

In this article, we want to concentrate on that latter situation. We’ll take a closer look at some of the often-overlooked fundraising data that will immediately improve your data picture. We’ll also talk about some of the techniques for making them a central part of your reporting.

Why good analytics is important.

Before we get on to three common absences from good fundraising data reporting, let’s quickly talk about why data analytics is important for organisations reliant on public donations.

When you’re working with a good analytics configuration, you can more easily understand how your fundraising results are distributed across audiences and tactics (for example, Facebook Ads or email campaigns). With these insights, you’re well-placed to optimise and prioritise your marketing efforts. You can invest more budget in the tactics or audiences that are producing bang-for-buck, and you can tweak and optimise in the areas where results are wanting.

Put another way: if you aren’t carefully tracking the various aspects of your digital marketing, the odds are you’re wasting money and limiting overall performance. You’re leaving gaps in your metaphorical net that are far larger than they need to be.

As we’ve said, though, there are quite a few common blind spots that you can easily address through good tracking practices.

Three common blind spots.

So, what are the kinds of meaningful digital fundraising data that many organisations don’t track? We’ve come up with a list of three, each of which lends itself to a different tracking implementation method:

• Donation types. For example, a one-off versus a recurring donation. Or a standard donation, as opposed to one connected to a particular mechanism, like a gifted donation.
• Target audiences. This is the audience as defined within marketing platforms. Examples include audiences you may define in Meta Ad Manager, or a custom audience list you upload for the purposes of remarketing.
• CRM segments. Here, we’re talking about which segments a donor falls into within a CRM. This could be a tag that differentiates new and repeat donors, or information about the different supporter tier in which the donor sits.

That’s an overview of the types of data. Let’s talk a bit more about how to collect and analyse each one.

Tracking different types of donations.

This first type of data is best collected through a method called a ‘data layer push event’. Simply put, the data layer is a JavaScript object that contains information about a user’s interaction with a website.

In the case of different types of donations, it comes down to either collecting information dynamically based on the information visitors input into a donation form, or by pulling meta information from the form itself (i.e. which variant of the donation form the visitor is using). In the case of form abandonment tracking, it can even be used to tell you which field the visitor last interacted with. That’s a vitally useful data point when determining potential causes for drop-off.

This method is quite reliable (it’s unlikely to break or cause errors in your data), and you’ll find it useful in covering most tracking requirements for all kinds of forms (including donation forms). However, it does require some developer support to add the necessary code to the form.

Tracking different campaign audiences.

Part A: a little bit about URL parameters.

Sometimes the data you’re attempting to track doesn’t come directly from the site or the visitors’ interactions, but instead from the digital marketing and advertising platforms you’re using (for example, eDMs, Google Ads, and Meta Ads).

In these cases, a good approach to capturing visit and conversion data on the audiences you’re targeting is through the combined use of ‘URL parameters’ and ‘custom dimensions’ in your analytics setup.

A ‘URL parameter’, also known as a query string parameter, is a piece of data that’s added to the end of a URL in order to help information pass between pages and sites. It’s commonly used in tracking and analytics for the purposes of marketing optimisation and attribution.

The most commonly used of these is the Urchin Tracking Module (more often referred to as “UTM parameters”). This is a standardised approach that helps people tag the links used across various marketing channels by the source and content. Here’s an example landing page link, with and without UTM parameters:

Untagged link: https://www.yoursite.com/landing-page/

Tagged link: https://www.yoursite.com/landing-page/?utm_source=facebook&utm_medium=paid-social&utm_campaign=spring_appeal&utm_content=video_ad

The parameters shown here (for example, “utm_campaign” and “utm_content) are an established convention accepted by Google Analytics and many other web analytics tools.

Part B: setting up your own custom URL parameters.

But you aren’t limited to what we’ve mentioned above. You can add your own custom parameters with a little extra setup.

A common need in the area of digital fundraising is the ability to collect the names of the various audience groups being targeted. The easy part is establishing a consistent parameter name that you use when tagging links – there’s no special trick to this part, and it can be as simple as “audience”. This would look something like:

www.yoursite.com/?audience=campaign_audience_01

To achieve this, the parameter needs to be defined as a dimension within your analytics account. How you do that will depend on the type of analytics implementation your site is running.

Once you’ve added this custom dimension to your analytics configuration, you now have a new dimension you can use to segment data within your analytics reports.

Tracking donation behaviour of different CRM segments.

The final type of donor data you should consider using in your reporting is segment data from your organisation’s CRM. This additional layer of information can help in you understand the different behaviour and touchpoints of your various donor groups. For example, you might look at distinctions between first-time and repeat donors, or low-value versus high-value givers.

This relies on both the “client-side” tracking (i.e. what’s happening in the browser) and what is captured and, subsequently, sent back from your CRM.

In simple terms, when a donation form is successfully submitted it will trigger a request to the backend of the website. This request will then be processed and sent across to the CRM. The CRM can, in turn, be configured to return a package of data to the frontend of the website that then gets folded back into the donation analytics tag.

Unlike the other methods shared in this article, this requires support from backend and CRM developers.

That said, there is huge value in being able to overlay CRM segment data with your web analytics, and the only real limits to this are the secure management of personal or sensitive data.

Improving your fundraising ‘net’.

The data you collect helps you put together a picture of how the people who visit your website behave. That includes how they get there, what they do when they visit, and, if they become a donor, how their journey from awareness of your organisation to donation progresses.

The more accurate the data, the clearer that picture is. And the clearer the picture is, the easier it is to close (or decrease the size of) the holes in your fundraising net.

There are so many different ways to obtain more accurate data. As Animals Australia demonstrates, the switch to a server-side analytics configuration can make a considerable difference.

If you’re seeking to make smaller adjustments, or looking for improvements in addition to those brought about by larger changes, what we’ve talked about in this article is an excellent place to start.

Carefully tracking donation types, audiences, and CRM segments doesn’t require a huge amount of work. But each seemingly modest adjustment will lead to more and more clarity.

Ultimately, that leads to more donations towards your organisation’s cause.

If you’d like to talk more about tracking or data analysis, get in touch. We’re always happy to chat.