Deconstructing Data Analytics

Tradd Data Analytics1

Data analytics. Sound perplexing to you? A quick Google search explains the term as the science of examining raw data to draw conclusions, but what does this actually mean?

Tradd Salvo, an analytics intern and graduate student at UT Austin, explained data analytics to me as “the base of where everything comes from.” It is essential for the inner workings of an advertising agency and a way to form insights and understand how campaigns are actually performing.

On an average day, Tradd works on dashboard reports and gains insights from metrics. Tradd is responsible for taking raw survey data, putting it into a database, doing statistical analysis, visualizing the data on a deck, and transforming it into something meaningful.

He emphasizes that the analytics team must make things as simple as possible and find the big takeaway from given data.

“At every step, accuracy is most important for analytics,” says Tradd. “If something doesn’t make sense, we figure out why it doesn’t make sense and this may lead to a huge insight and optimization of the campaign.”

After getting a crash course in Data Analytics 101 from Tradd, I spoke to Rory Braithwaite, VP, strategic analytics, and Jo Lu, director of analytics, to dive further into this world.

Visualization is Key

Although many may consider analysts to be strictly “left-brained,” Tradd stresses that analysts utilize both sides of their brain and must be creative in their visualization and delivery.

Rory explains that their analytics team is essentially always trying to prove a point, and that visuals help illustrate the fundamentals. “If there are 10,000 website visits a month, you have to put that into context. Was that good? Did something not work? Did we do something that was successful or not? That, I think, is the big driver of the visual you end up putting out.”

Jo adds, “Digital visualization should not be too complicated—it should be simple and it should be crisp, so that people can grasp the information the moment they look at it.”

Engagement vs. Interaction

What is the difference, and is there a difference? Jo shares that she uses the terms interchangeably.

“If anything, engagement is probably a bigger term. Any kind of experience you have is an engagement,” explains Rory.

The hot term of the decade: “Big Data”

We’ve all heard “Big Data” thrown around in classroom lectures, news headlines, and TEDtalks, but what does big data mean for analysts like Rory and Jo?

Jo shares that she does not emphasize big data because, first and foremost, it is just a large pile of data. She understands that big data is helpful to get comprehensive material from multiple channels, but states, “I care most about the insights coming out of big data. Most of the time people get trapped in the idea that they have all these sources of data, but in the end, we are still trying to solve something with the data.”

To Rory, having a small or large amount of data could mean similar results. He says, “It shouldn’t matter to us how much data there is as long as we figure out what to do with it.” It seems that with a higher volume of data, there is more planning and infrastructure needed, but both analysts agree that turning the data into insights is what is most significant.

Department Interactions

As a department considered a “shared service” like IT, the analytics team must react quickly to projects, but also work to get accurate, quality information.

The analysts also have a wide variety of skill sets from strategic planning to statistical analysis and social media, which is helpful when tackling a diverse array of projects. Additionally, the team interacts with other departments throughout the agency including strategy, creative, account, branding, and research.

Jo shares that ideally they should be collaborating with even more departments. “We would like to be brought in on the early phases of studies because a lot of what we do is exploratory analysis versus just measurement.”

“Strategic” Analytics

It is interesting to note that both Rory’s and Jo’s roles at FCB are under strategic analytics. When asked the meaning of the title, Rory explained that his previous title only encompassed customer insights which felt limiting to a research role. Their current roles suggest integration into strategy to determine a campaign’s first steps.

“[Using the term] strategic analytics is to make it clear that a lot of what we do happens before anything gets launched. That includes doing analyses, capturing data, and conducting research to figure out the right strategic approach and response.”

Rory puts it simply, “Shifting towards the strategy direction is leaning towards insights, instead of just an output of numbers.”

What lies ahead?

What about the future of data or strategic analytics? Rory shares that real-time insight generation is something to watch out for.

“If you think about Amazon, you shop for something, you check out, and it starts haunting you on your database,” Rory states. “Being able to do that, but also being able to generate insights on the fly as data becomes available is something to look out for.” The possibilities are endless as these insights can inform media buys, spending, and what to focus on for optimizing a campaign.

Jo also articulates that analytics is starting to shift towards predictive modeling rather than just pure measurement, replacing “what has been done” with “what could be done.”

Overall, Tradd put it well when he said that today’s data analysts should be considered “decision scientists” because what they do encompasses much more than just numbers and data. Through my interviews with the team, I’ve learned that data analytics is about making sense of raw data, visualizing the data clearly and concisely, and then finding key insights to help change behavior, which all makes perfect sense to me—data analytics debunked!