A robust data science team is essential for building business wealth. But what turns your analytics from data into ROI?
Let’s dive in!
Like many marketing professionals, Brian followed a less than straightforward path on the way to his ultimate career. For one, his background is actually in engineering.
He found his way into a marketing role while working a second job at a warehouse. The business needed help with their website, and the opportunity allowed Brain to gain valuable experience in SEO and analytics. He decided to make a full career switch and began diligently studying the practice.
Entirely self-taught and with a gift for numbers, Brian began interviewing for entry-level SEO positions at marketing agencies.
“The strength of my interview landed me several levels up,” he told our hosts. “I knew I had a knack for it, and that’s how I got started. It was wild … I went in there just hoping I would get the job.”
He continued to grow as an expert in his field until the fateful day he and then-coworker Jenny Du decided to break off from the pack, stating: “We wanted to create the place that we wanted to work at.”
And thus, BrainDo was born!
Ten years later, Brain is now surrounded and supported by a robust team of like-minded, data-driven, digital marketers. And he’s right there with his team, formulating analytics strategies for clients across the globe.
A business could look at countless amounts of data to track its performance. Understanding what data is most relevant, however, can be challenging.
As Brian points out, “There’s a lot of vanity metrics out there.” These are numbers that look good, but don’t deliver as much value. He continues:
“There are so many easy ways to waste energy, to waste time, to waste money.”
And as podcast co-host Tatiana Knies-Smith notes, there’s no way to retroactively collect past data. This is why proper foundational analytics work is so important.
Foundational work can include examining a user’s flows and deciding exactly how you’d like said user to behave. After this step, you can begin researching the different analytics platforms out there — one of which has a lot of significant changes happening right now!
Over the years, traffic on the internet has increased dramatically — and will continue to do so. Google and its Universal Analytics platform have been an industry favorite for years, but there’s change on the horizon.
Recently, Google replaced the beloved Universal Analytics tool with a new product: GA4, or Google Analytics 4.
Brian states that GA4 is, “a certain evolution of a product that came much later, and I would say in some ways it is more primitive than the prior version of Google Analytics.”
His sentiment reflects the fact that the previous version had invested so much in feature expansion. Universal Analytics was completely flushed out. But it’s also built upon an old and, dare we say it, obsolete iteration of what the internet once was.
Despite not having the same depth of functionality (yet), GA4 is built on and for the modern internet, and the platform captures a far more advanced array of technological touchpoints. The new platform understands that, eventually, we will need to be able to track data in everything. From VR spaces to apps nested within other apps and beyond.
So, let’s say you’ve completed the foundational analytics work and are gung-ho for GA4. How can you convert this data into a strong return on investment (ROI)?
The question every good business owner has asked since the beginning of time: What’s the ROI?
For a quantifiable answer to this inquiry, look to your analytics program. The team working with the data should produce insights and informed recommendations that allow the company to optimize for better performance.
Brian shrewdly observed that “the data itself is useless unless it’s being applied to actually change the business and improve the program.”
Data can show a company where its opportunities lie, unearthing possibilities that may have gone unnoticed. This is just one way that your data analytics program can produce an ROI. However, there are other ways to mine further returns from your data.
But you’ll have to watch the full episode to find out!
In our conversation with Brian, we dive into creating actionable insights, A/B testing, and much more. This is just the preamble to our deeper discussion of data analytics. Listen to the full episode to extract as much value as possible for your company!