Our Ask An Expert series features real questions answered by Claire Axelrad, J.D., CFRE, our very own Fundraising Coach, also known as Charity Clairity.
Today’s question comes from a nonprofit employee who wants advice on whether or not it’s worth it to invest in digital analytics tools.
Dear Charity Clairity,
We have some high-tech folks on our board, and some think we’re not doing enough digitally. They want us to invest in digital analytics tools to measure our efforts, but I’m not really sure what this will tell us. Nor am I convinced we’ll have the bandwidth to use the tools or this data.
My boss asked me to explore this further. Do you have any thoughts?
— In the Digital Wilderness
Dear In the Digital Wilderness,
No doubt about it, embracing digital marketing and fundraising strategies is certainly a new frontier for most nonprofits. Your board is right: It’s time to evolve and inhabit the digital landscape.
- The COVID-19 pandemic accelerated digital transformation by, on average, six years.
- 2017 to 2021 saw a 160% increase in customers’ digital interaction with brands.
- 92% of businesses say transforming digital communications is extremely or very critical to address business challenges.
- 79% of businesses say the effects of the pandemic resulted in them having to increase their budget for digital transformation.
A primary driver of digital transformation is customer experience and satisfaction. In fact, a study by Salesforce found the number one most valuable metric of success for service organizations is customer satisfaction. Number two is revenue. That’s a huge harbinger of what the future holds.
As a fundraiser, I’m sure you’re concerned about your donors’ experience; that’s why digital transformation matters. It’s why I wrote about “digital first” being a priority strategy for nonprofits moving forward (here and here.) And, with that, it’s why you need to track data that tells you if your digital efforts are succeeding or if you need to tweak certain strategies.
The road to digital analytics maturity
How can these tools help you track meaningful data? To get a better grasp on this, let’s look at the different types of analytics and what they measure. Below is what Jay Baer of Convince and Convert describes as a five-step “Digital Analytics Maturity Model.”
He’s a master of what it takes to move folks toward the actions you’d like them to take, and I’m hoping this summary will help you talk with your boss and board and figure out how you can use the tools they want you to use to your advantage.
1. Descriptive analytics: What happened?
With descriptive analytics, you’re concerned about what happened with your customer or, in this case, your donor. To figure this out, look at your website analytics, email analytics, conversion rates, social listening, and more.
There are so many things you can measure in Google Analytics, but you’re not going to use all of this information. So, first you need to figure out what data you want to collect. Ask yourself: What are your goals? How are you measuring if you’re meeting or exceeding them? Then disregard the data that isn’t relevant. For example, don’t worry too much about the number of Twitter followers you have if this metric doesn’t lead to an increase in fundraising revenue.
Ultimately, when you’re asking what happened, you’re figuring out if you’re successfully motivating donors to support your mission. That’s a good place to start, no?
2. Diagnostic analytics: Why did this happen?
To figure out why something happened—AKA what the data you collected from descriptive analytics is telling you—consider sending surveys, analyzing reviews, looking at heat maps (showing how the user scrolls through content), holding focus groups and one-on-one interviews, and inviting supporters to take polls to ascertain donor behavior.
Don’t assume you know the answer before you look at the data. You need to understand their expectations and needs in order to meet them and to motivate them to take a desired action. Otherwise you’re just taking a stab in the dark.
3. Predictive analytics: What’s going to happen?
Use machine-learning algorithms to understand and track what is influencing donor satisfaction and performance and to detect specific events in the donor’s journey. The algorithms generate predictive scores for each donor based on journey features, enabling you to look forward not backward. These scores allow you to predict individual satisfaction and value outcomes such as revenue, loyalty, and cost to serve.
There are two principle types of predictive analytics: (1) lead scoring, which many nonprofits use to predict the likelihood of a donor making an annual gift, major gift, or planned gift, and (2) time-series forecasting, which few nonprofits consider.
Per Jay Baer, timing matters. Schedule your marketing communications by looking at the times your donors and supporters are engaging with your communication channels and materials; then use the insights you’ve gained to influence future actions.
4. Prescriptive analytics: What should we do?
Build on what you learned through predictive analytics by looking at hidden factors you’ll find in sophisticated statistical analyses such as variable importance models and Markov chain models. This helps you determine the probability that a page, channel, or topic will result in a desired action.
Because nonprofits’ budgets are usually limited and they can’t do everything at once or in general, it’s important to know where to send visitors to make the most of their time engaging with you. Some pages, channels, and topics convert at much higher rates than others. When you guess, you don’t really know. You can avoid this by focusing on the data and do what is most likely to get you the results you most want.
5. Proactive analytics: Do it for me.
This is where the robots take over! It may sound like science fiction, but it’s possible through machine learning. You need a lot of data, and this requires a lot of money. So although it’s not a viable strategy for most nonprofits, it may be useful for larger and/or global nonprofits.
The length of the digital analytics journey
You can’t rush it. Each stage requires a new skill set, and much of the timing is driven by company culture and comfort level. The full journey may take you somewhere between 12 to 24 months.
As you change stages, you may even have to change organizational structure. Things like staffing, reporting patterns, distribution lists, and how you’re taking action based on this data may need to change.
Finally, keep in mind that it’s not just about collecting data. Just because you measure better doesn’t mean you’ve achieved your goals. You have to make some operational changes because you measured better. Analytics should drive positive change. You’ll know your analytics are working when your organization starts making better decisions that help you achieve and exceed your goals.
I hope this takes you out of the wilderness and gives you some food for thought.
— Charity Clairity
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