Baby Steps: How to Cut The Confusion and Start Using Data to Improve Your Cause Marketing
Data is everywhere.
We live in a world where almost everything we do generates some sort of data that can then be used in some sort of way.
So it comes as no surprise that marketers are using data to improve what they do and how they engage customers and constituents. Seventy-eight percent of marketers say that using data is an embedded or strategic part of their job.
Data-driven marketing can unlock huge opportunities for nonprofits in areas like email marketing and donor retention. In these areas, using data to generate modest improvements in performance—say a 7% increase in donations—can add up to thousands (or millions) of dollars over the course of a campaign.
But data can also be confusing.
For many, marketing is something inherently unscientific. It’s an art, based on intuition and insight, not something to be driven by numbers in a spreadsheet. Many nonprofits don't use data in their marketing because they struggle to cut through the confusing information and implement a straightforward and simple data-driven marketing plan.
Let’s discuss how your organization can get past confusion about data and start using it as a tool to generate continuous improvement in your marketing.
Start with the data you have (and aren’t scared to use)
Data is everywhere, but as a nonprofit you may not have the tools or resources to capture as much data as you’d like. That’s okay. In fact, it’s probably preferred.
Many nonprofits—and for-profits, for that matter—are scared to jump into data-driven marketing because the amount of available data (and ways to use it) is simply overwhelming.
In this case, though, it doesn’t have to be exhaustive. You just have to start somewhere—anywhere. Find some available data that you can use to inform some aspect of your marketing. Test it out. Get better at using it. Then find more data and more ways to use it. Baby steps are okay.
The first place to look for data is probably in two key areas: CRM and email.
Both of these systems likely have huge troves of data. And if you’re like most organizations, you just barely scratch the surface of using what’s available. For instance, if you use a service like MailChimp or Constant Contact, you probably look at the top-level data like open rates, click-through rates, and unsubscribes.
These are baseline metrics—and they can be useful. You can test different subject lines to see if it improves the open rate on messages you send. Or you can see how your click-through rate changes based on the number of links you have or the placement of those links.
But have you dug deeper? What about retention rate? Engagement rate over time? Testing different layouts, calls to action, send times, and more?
There is a ton of data to be collected—most of which is provided by your email service provider if you know where to look.
The point is that your data doesn’t have to be incredibly sophisticated to start. You can use the data you have to begin to make progress. Then as you see results—and as your organization grows more comfortable in analyzing and using data in their marketing—you can expand your efforts.
But, for now, it’s okay to start small and simple.
Find insights, not just numbers
We’ve written previously on the perils of blindly following data. And that applies equally across all kinds of marketing.
Whether you’re looking at email metrics or analytics data, the real value in those numbers is not on the surface. It’s what the data—and the associated actions—tell you about the people you are trying to understand.
Hidden within the numbers are insights—things that don’t just tell you how people act, but why they act that way.
The key to uncovering insights is to look beyond the number and see the context and the meaning behind that number. It’s to ask why, to form theories, and to test those theories.
One way to turn data into insights is through qualitative research. Take the quantitative figures you have and hold discussions, panels, or focus groups with members of your primary audience. This gives you a way to probe deeper and provide context and meaning to observed behaviors.
Understandably, this is out of reach for many nonprofits. But that doesn’t mean you’re dead in the water.
Another way to begin turning data into insights is to develop and implement a series of tests—experiments—that will help you understand not just how people behave but why they behave that way.
This involves forming a hypothesis and then attempting to validate it through testing. So, for example, if you think that your constituents might be willing to donate at the end of the month because they have extra money left and have paid their bills, then you would design a series of experiments that would help validate that idea.
You might try:
Sending emails at the end of the month versus the beginning
Including messages in your email that directly allude to that little bit of extra money in their bank account
This is not a perfect system. But it allows you to extract data and then use that data as the basis for ideas—and possibly insights—that will move efforts forward.
Track and test
Taking this process a step further, your organization should commit to tracking and testing as much as possible. Rather than assuming or guessing about what will work best, you should test and validate different approaches to learn what works.
It’s through a workflow like this—where things are constantly tested, analyzed, and re-tested—that you achieve measurable improvement over time. Making small adjustments to the way that you communicate with constituents may only change the results by 1 or 2%. But, with 5 or 6 improvements of that magnitude, your organization can see a 10% improvement or more.
And all it takes is one small step to get started.