How Data-Driven Decisions Set You Up for Growth
Many marketers and business leaders think they know what their audiences want. But without the data to prove it, you’ll never know for sure.
Data-driven decisions take the guesswork out of your choices and truly improve your organizational metrics. Here’s a look at the importance of testing your hypotheses and how a data-driven culture can positively impact your bottom line.
Question Assumptions and Habits
Surprisingly enough, business leaders often make assumptions about what drives user behavior. Whether you rely solely on general industry benchmarks in a vacuum, or still lean on processes that made sense in the past, a lack of ongoing data-based decisions can actually damage your results and cause you to misjudge your audience altogether.
At Classy, we recently experienced an eye-opening moment around user behavior with our weekly blog newsletter, the Classy Roundup. At one point, we considered whether adding images to each item in the newsletter would improve click-through rates. Up to that point, none of the sections in the email included images. Given what we knew about the power of visual content in engaging and attracting readers, we quickly assumed adding images would improve our numbers.
But despite our conviction, we set up an A/B test to test the effectiveness of adding images to the roundup. We set up version A as our control (what we’d been currently using):
And we incorporated images in the roundup for version B:
We ran these tests simultaneously, splitting the traffic so that subscribers all saw either variation A or B at the same time. After we ran the the tests for several weeks, we were shocked to find that variation A—the newsletter layout without multiple images—outperformed variation B. Our initial assumptions were proven totally wrong. If we hadn’t stopped to test our own opinions, we would’ve implemented a change that hurt our results rather than helped them.
The same can be said about procedures and decisions that are based on habits and tradition, rather than data. When you continue a process just because it has been “the way we do things around here,” you risk losing touch with your supporters and preventing growth.
For example, if your organization has historically focused on direct mailings, advertisements, and cold calling, it’s worth considering that inbound strategies (using valuable content to attract users) drive 54 percent more leads than traditional outbound marketing. Or if you continue to post Facebook updates at 11am and 5pm on weekdays because that’s what proved optimal in the past, you could miss the majority of people who now check Facebook mainly at noon or midday.
Not only is it important to keep a pulse on current industry statistics, it’s critical that you take these insights and test them where they matter—among your unique audience. This allows you to confidently know what works and doesn’t work in order to make smart, data-based decisions.
How Testing Can Improve Your Bottom Line
Beyond just testing singular questions or hypotheses—like whether adding visual imagery will improve an email’s click-through rate, or changing up your calls to action on your blog posts—consistent testing can have tremendous impact on your organization.
When you test thoughtful, careful changes to improve a distinct metric, you can continue to improve the overall user experience over time. The results of testing different variables in isolation will help you to determine which changes impact your supporters’ behavior. Armed with this information, you can then craft marketing materials and campaigns that drive better holistic results than your previous ones.
For instance, a nonprofit might aim to improve its overall donor conversions off of its homepage. To do that, it might A/B test:
- The location of a donate button
- The color of a donate button
- The addition and placement of a monthly giving CTA
- Visual content
- The use of pass-through parameters
The organization can then look to its subsequent donation page and test:
These experiments can show them which changes convert interested prospects into donors.
With the results of each separate experiment on these different variables, the organization can optimize the entire experience to drive higher conversion rates and improve their bottom line.
Tips to Encourage Data-Driven Decisions and Testing
So how do you support a data-driven mindset among your team? Here are a few tips:
Get your team members together and encourage everyone to throw ideas out there on how to improve processes or the overall business, no matter how unconventional they may seem. This can help you take a hard look at your traditional way of doing things.
Create a schedule of A/B tests.
A/B testing is a specific way to support data-driven decisions. Whether it’s for your emails, website, social media strategy, or landing pages, create a list of things you want to test and a schedule for each experiment. How many times or weeks will you be running the test? How will you circulate the findings to your team, who could benefit from your takeaways and apply them to their own tasks?
As you continue to brainstorm and make decisions, reassess your team’s choices and ask why that route was chosen. This applies to both habits as well as suggestions and assumptions while looking at data. An assumption based off immediate data might be that visual content has been shown to increase retweets on Twitter, but that doesn’t necessarily mean you should include images in all your tweets. In fact, with some testing you might find that images could increase retweets but actually decrease clicks on links. It’s a matter of asking why and ensuring your decision aligns with your actual business goals.
The importance of testing cannot be understated. When you take the steps to “know” rather than “assume,” you pinpoint the strategies that will impact user behavior and power your growth. Have any other thoughts or tips on how to support data-driven decisions at your organization? Let us know in the comments below.