It's so interesting that only 5% of companies are actually using their data analytics to drive action. Earlier this year, there was a trending article from Forbes published by Brent Dykes. He shared his experience with organizations on how they work with their data.
Surprisingly, a very small number of companies take action based on their data analytics. To get there, Brent broke the process down to 6 milestones.
How about we take a look at it through a paid social perspective?
Digital marketing is no different.
Whether your job is to create and optimize campaigns, make reports, monitor, or you're doing all of the above. It will always include data to some degree. And knowing how to work with your data will help you in times when you're not really sure what to do to increase your performance.
This week, we talked to a social media marketer from one of the companies we advised. She called for guidance while she was preparing her social media strategy for 2022.
"What should I do to demonstrate increased performance?" she asked.
This is a question that, at some point, all marketers have asked themselves throughout their careers. And most likely not only once.
So let's unpack the data analytics framework step-by-step.
Data collection in paid social usually starts with you deciding the primary objective for your campaigns. Social media platforms collect a variety of raw data automatically. However, some of the data will require more effort to capture correctly.
To reach your goals and objectives, you'll need to figure out whether it's possible to collect them or not.
You most likely already heard of tracking preventions like iOS14 and Cookie Consent. These measures heavily impacted your paid social tracking, targeting, and ad delivery. For example, you might have noticed that your ads take longer to exit the learning phase.
Since more and more people are declining to be tracked, the target groups got smaller, making it difficult to collect some data. Especially when you want to collect data lower in the funnel. For now, it's about 50 conversions that your ad needs to collect as a minimum to leave the learning phase.
You should ask yourself:
Is the data you need affected by tracking preventions? If yes, how can you get this data? Or, is there a way around them?
We described it in detail in this article →
To gain valuable insights from your data, you need to prepare them. You'd be surprised, but many marketers choose to measure a lot of metrics to view.
And let's be honest.
There are hundreds of metrics that your ads can collect. And then multiply that number by the number of ads you're running. 😱
It comes as no surprise that it's very easy to get distracted by data that is not important.
To get valuable insights, it's critical that you choose only a few. To make it structured, we would suggest applying these 2 categories:
Most marketers end on this step - visualizing data in reports. But you'd be only halfway done. And it's far from making data-based actions. Even though only 70% of companies do this, reporting has to be done. It helps you to monitor your campaigns' performance.
And when you share your visualized report or dashboard with your managers and stakeholders, they'll be able to observe the performance as well. Not to mention that making a proper data analysis would be much harder without data visualization.
You need to explore your data to gain valuable insights.
Usually, you'd want to start your campaign analysis by figuring out if your primary metric reached its goal. If your campaign didn't perform the way you wanted, you need to dive deeper. Breaking down your secondary metrics can show you the potential low-hanging fruits.
You can also group a huge amount of data to discover hidden patterns/trends.
Many marketers don't analyze grouped data. This is mainly because native platforms don't allow you to group your data the way you need.
Imagine having a year long campaign with, e.g., 4 different target groups or ad sets. Within each target group, you are testing 3 different creatives - a short video, a longer video, and an image. Let's spice it with 2 different CTA buttons as well. This gives you 4*3*2 = 24 ads. In native platforms, you can easily find which ad gave you the most conversions. But it won't tell you which one of your creatives performed better.
Was it the short video, longer video, or an image?
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Just as a side note, you can do this in deepdivr by using filters. It's a feature our clients say is a gamechanger. But don't take just our word for it. Check the reviews →
All the data that you analyzed may hold a tremendous value. But your company won't get even a grain of that value.
Not until all the insights are translated into actions and outcomes. Or in other words, you need to get your message across so that people can understand what needs to be done.
For example, you might've noticed the difference between who you most often reach and those who really engage in your campaign. That can spark an idea to improve your targeting and budget split for your next campaign. Now you just need to translate it to your team and stakeholders to show the opportunities that are based on your data.
So to make sure your decisions are driven by your key insights, you need to communicate them effectively.
We're finally catching up to the top 5%. In the last, most crucial step, you need to decide which key insights you need to pursue. Once you've decided, it comes to the planning and execution. After all, a plan is just a wish without execution.
Which key insight has the best potential to drive the results you set out to achieve? To optimize your performance, do you need to adjust your targeting strategy? Or do you need to change your messaging?
It's always a great idea to test your findings before making big changes. Either way, you need to analyze your results after each change to learn from them.
Knowing how to work with your data is crucial for demonstrating increased performance. This is true for both business in general and in digital marketing. You take the same 6 milestones from Brent’s article and apply them to your paid social.
Some milestones can be more difficult than others. Unfortunately skipping one or few will make your job probably harder. Or based on guesses instead of hard data. If you’re in doubt on any of the milestones we wrote about, feel free to drop us a message.
If you’re a paid social specialist that is interested in campaign optimization you can check out our optimization guide. You’ll find there 6 steps that you can apply as a framework to your campaign optimization process.
If you'd like to know more about this topic, feel free to reach out to anine@deepdivr.io.