“What do you do for a living?”

I get asked this question frequently, and I sometimes find it a daunting task to explain. If I had been an astronaut, I could simply say, “I am an astronaut.” Everyone knows what astronauts do (although often in a very generalized and simplified way). But as a digital analyst, I find I need to prepare a more detailed response for the question, should it arise over dinner or at a party.

My canned response begins with: “I measure visitor behavior online so organizations can improve their online presence and marketing efforts.” It usually helps to provide some examples of what I measure. Common metrics that a digital analyst measures are:

  • The most popular pages on a website
  • How landing pages are performing for a particular digital marketing campaign
  • Which campaigns are driving visitors to a site and resulting in purchases
  • How long visitors stay on a site and site bounce rates
  • Which social media posts are gaining the most traction
  • Website conversion rates
  • Engagement with blog posts

What is Digital Marketing Analytics?

Digital marketing analytics involves collecting and analyzing data from the digital space to inform marketing strategy, which begs the next question, “what is the digital space?” This is mainly the world of websites, which has its own subset of digital analytics called web analytics. But a comprehensive digital analytics strategy can also extend to mobile apps, interactive mall displays, social media, email marketing and point of sale (POS) systems. Essentially, anything that can be connected to the internet at some point can be tracked with digital analytics. The collection and analysis components can then be further expanded for a greater understanding of the business.

Data Collection – Building a strategy to understand user behavior

Collecting this information is the first phase of digital analytics. Before collection can begin, a collection strategy needs to be agreed upon. This usually involves interviewing stakeholders and designing a plan that explains what will be collected to understand user behavior. It is important to document this well for future reference. It’s easier to examine data when you know how it was collected, and it’s vital that information is collected the same way every time for comparison.

The collection of the data starts with gathering information about interactions on the device where the interaction is taking place, sometimes referred to as the client. A singular interaction is referred to as a hit. This hit information is then sent to the processing platform (such as Adobe Analytics or Google Analytics) where it is then fed into a database for holding until it is later extracted for reporting.

Quality Assurance – Ensuring data is collected properly

One important step in data collection is quality assurance, or QA. This is the process of ensuring that the data is being collected properly and reflecting an accurate record of interactions. If you ask a consultancy about their QA process and you get a blank stare, it’s time to run! QA involves watching the data being collected at the point of interaction as well as viewing the data in reports to ensure the processing is set up correctly.

Analysis and Visualization – Using analytics tools for marketing insights

The actual analysis step is where both analytical thinking and creativity come into play. This involves building reports, creating dashboards, discovering insights and presenting findings and recommendations. There are numerous ways to view data, referred as visualizations. You can use standard out-of-the-box reports or custom reporting options provided by your vendor. Additionally, there are third-party vendors that provide analytics or customer data platform tools, bringing multiple data sources into one view to create customized reports and visualizations in real time, including Tableau and Domo.

Each of these pieces – reporting strategy, data collection, QA, analysis, visualization and presentation, make up the field of digital analytics. It is an exciting, data-driven, multi-disciplinary field, but not one that readies itself for canned responses. This may be why astronauts are so popular at parties, but astronauts are not readily able to help evaluate your business model and set you up for success.