Do you feel tiny droplets of sweat begin to form when somebody says, “Let’s see what the analytics dashboard says about this marketing campaign.”? Technology rewards us with massive amounts of data about how content on our digital presence is being consumed and the resulting actions. For some, it’s an overwhelming amount of information.
The sheer amount of data generated by your website, digital communications such as email, and social media activity is complex and overwhelming in its raw form. It’s probably why so many of us shy away from diving into what analytics can tell us.
But like the scary monster in the closet that turned out to be just a shadow made from a winter coat, most of our challenges with marketing analytics are perceived. So, let’s do some myth-busting.
But before we get started, let’s make sure we’re all on the same page about what marketing analytics are.
It’s the practice of measuring, managing, and analyzing marketing performance. We do this to maximize the effectiveness of our efforts and optimize our return on investment (ROI).
When we understand what’s working because we’ve measured the results, we become more efficient at attracting prospects, converting leads, acquiring customers, and growing the brand. Analytics help us do this by showing us the best way to optimize resources and marketing dollars.
You may think you know what’s working, but you won’t truly know for sure unless you measure and monitor your campaigns.
What does measuring analytics really do?
The challenge with analytics is that, depending on our role, we are either valued for our analytical thinking or our creativity.
If you spend more of your time creating content or crafting explainer videos, you might not have much exposure to the data side of things. What you might know of it is like the mythical monster in the closet. You might even believe some of these myths.
What do the numbers say? Get a FREE site assessment.
Fear not! If you tried but failed to remain conscious during algebra, and you’re still wondering when you’ll ever employ a quadratic formula in real life, there are programs that do the heavy lifting and number crunching for you.
It’s more important to understand – in general terms – the “why,” rather than the “what” or the “how.” For that, turn to resources like Google’s Analytics Academy or sign up for HubSpot’s Inbound Certification classes.
It’s true, there’s a crazy amount of data to look at. However, not all of it requires your constant attention.
Knowing what to look at to generate the metrics you want to measure is what you’ll initially focus on. It becomes a regular routine. Like a habit, you’ll do it without thinking through each step.
Not all data needs to be analyzed with the same frequency. You may decide to analyze visits and leads daily, while data offering insight on email campaigns and CTA click-throughs might be relegated to a weekly check.
Likewise, your SEO rankings and social media metrics require cumulative data that make more sense to check monthly.
Tell that to the folks who launched the New Coke in 1985. They’d already conducted taste tests with nearly 200,000 people, who told them they liked it better than Coca-Cola’s original formula.
Based on their assumptions, and their decision not to challenge those assumptions, the beverage company found themselves at the center of, in their own words, the story on one of the most memorable marketing blunders ever.
Not every channel may perform as you think it should. Look closely at the data to see if you can discover why. Numbers are logical, but consumers are not. Humans are known for their unpredictable and irrational behavior.
If it looks like a duck, walks like a duck, and quacks like a duck, it’s a duck.
Perhaps so, but don’t apply duck test reasoning to marketing analytics. Definitions and semantics come into play, meaning that data is still measured in numbers, but different platforms will define what’s being measured.
Here’s an example. If you use HubSpot for marketing analysis, it will measure your website’s visits. A visit is any time someone comes to the site from a referring source, regardless of the time frame.
Meanwhile, Google Analytics determines visit data over a 30-minute period. It means you’ll have a slight variance when you compare the same data metric across different platforms.
There is a lot of data, and you don’t want to chase it down rabbit holes. There’s no perfect KPI, and the purpose of the data isn’t to create a report. It’s to provide deeper insights into targeting and persuasion. So analytics on visits and leads is not enough – at least the cumulative numbers.
For the purpose of targeting and persuasion, you need to analyze the percentage coming from different marketing channels.
Is paid search doing better than organic?
Are you email campaigns pulling in more visits and converting better than social media?
Then you’ve got to slice and dice again. Are your blog posts doing an effective job awareness at the top of the sales funnel? What about conversion, or even sales?
Not all visits have the same value when measured against a specific behavior. It’s why other metrics join the analysis.
Actions speak louder than words. You know things are going right when lead generation increases, there’s a rise in conversions, and revenue grows.
But what part of that sophisticated virtual marketing engine is doing it? The “why” is right there in the data, and interpreting that data isn’t as mind-boggling as you think.
Learn more about what marketing analytics tell you about the effectiveness of your content.