Everyone knows that if you want Uruguay WhatsApp Number List to be a savvy modern marketer, you need data.
Agencies tout their expertise in data-driven marketing, big brands herald a new age driven by big data trends, and it’s standard practice to have Google Analytics set up on your website.
But let’s get real.
You might have Google Analytics on your site, but how often do you check it? You might know the last email you sent had a 40 percent open rate, but what does that mean for your business?
What do you do with that Uruguay WhatsApp Number List information?
The ability to collect and analyze huge amounts of data has undoubtedly transformed our society. But many marketers simply don’t have huge amounts of data.
The average marketer’s data are small, imperfect, and unpredictable. In our world, the algorithms, statistics, and trends that drive big data discovery just don’t apply.
To get the most out of our small, imperfect data, we need a different kind of tool.
We need intuition.
Data and … intuition?
“Hold up,” you might be thinking. “I thought we were talking about data here. You know, data — science, reason, logic? How is it related to intuition?”
Let me explain.
At my last agency job, one of my responsibilities was to create a monthly report for each client. At first, I simply created the report and sent it off to the client.
But over time, I realized the report wasn’t doing anything. Yes, it demonstrated to the client that we were delivering on our services. But we claimed to be a data-driven agency. How were we using that data to improve our services?
So, I decided to work with our content creators and explain the data to them — show them the trends I saw and hope that would influence how well we did our jobs.
First, I sat down with our social media manager.
Each month, the social media manager was responsible for developing the content calendar for each of our clients. As she was doing this, she had some ideas about which posts might resonate with our audience, and which ones might not.
When I began reviewing the performance of each post with her at the end of each month, I started to notice something interesting.
Sometimes her ideas would be validated: “I knew that one would go well!” she’d exclaim.
But other times, the results were unexpected: “I really thought this one would do better,” she might say. Or, “I’m really surprised to see how well that post did!”
The important part, though, was that after starting this ritual, our social media engagement began to climb.
Every month, the manager would leave our meeting with new ideas and inspiration for the coming month — and most importantly, a slightly improved intuition.
Clear goals + expectations = hypothesis
For a while, I assumed this kind of improvement happened naturally when you exposed a content creator to performance data. Content + data = success. Right?
Well, not necessarily. Since then, I’ve recognized that there were two reasons why reviewing data worked for our social media manager.
- We had a clear goal and KPI for each post. We wanted to boost social media engagement; if one post got more likes than another, it was clearly working.
- The social media manager had expectations for each post.
Before she published, she had her own ideas about what might work and what might fall flat, and those expectations were based on the clear goal of more engagement. Then, later, our data would confirm or rebut her expectations.
In other words, for every post, our social media manager had a hypothesis.