Elevating Data Analysis in Marketing

Welcome to a special edition of What Gets Measured, curated specifically for marketing data analysts at agencies. This episode compiles the best clips from our interviews with top industry experts, offering practical tips on data analysis, management, and interpretation. 

Whether you're pulling insights from cross-channel campaigns, tracking conversions, or untangling a web of metrics, this episode is packed with advice to sharpen your skills and transform raw data into actionable business decisions.

The Role of Data Analysts in Marketing

Data analysts sit at the center of today's data-driven marketing landscape. There are millions of data points available for you to mine through, and bubbling up the insights and uncovering the gems from the generic is a full-time, and full-brain commitment. 

The challenge isn’t just mining the numbers, but presenting them in a way that drives decisions—and, let's be honest, not everyone speaks the language of data.  

Improving Analyst Skills with Expert Guidance

In our episode, Improving Your Analyst Skills as a Marketer, with ex-Googler and VP of Marketing at AdQuick, Adam Singer posed a stark and straight forward question about data analysis capabilities.

"Imagine hiring a pilot who couldn’t read the altimeter, speedometer, or understand the fuel levels,” asks Adam. “You wouldn’t do that. So why have marketers or managers who can’t read the dashboards or metrics that are important for your marketing?" Adam humorously likens data proficiency to piloting a plane—without it, you're flying blind.

For aspiring data analysts, he suggests working closely with direct marketers, who are well-versed in using a range of marketing tactics and tying them to outcomes. He advises new analysts to prioritize strategy and cultivate cross-departmental relationships over following the flashing lights of the latest industry buzzwords to guide their interpretation and use of data

The Power of Customer Data

Marketing thought leader Zack Wenthe discussed the importance of controlling and consolidating data to break down silos in his episode, Unlocking the Potential of Customer Data. According to Wenthe, much of the data we need is locked in various platforms, and marketers spend time translating metrics instead of driving strategy.

"A lot of it comes down to control. If you're not in control of your data, you're at the mercy of the platform," he explains. Wenthe underscores that data issues are rarely technical but stem from internal misalignment. Simply buying new tech won’t solve the problem if there’s no cohesive strategy.

Attribution: Who Gets Credit?

One of the biggest challenges in data analysis is attribution—determining who gets credit for conversions. In his awesome episode, Decoding Attribution in Advertising, Jeff Greenfield, CEO of Provalytics, provides a historical perspective on attribution in digital marketing and the transition away from cookie-based models.

"When digital took off, attribution worked pretty well. Today, with cookies going away, we have to start taking advantage of the amazing computing power available to us and start thinking above the bottom of the funnel," says Greenfield. 

He advocates for a broader view of marketing that focuses on marketing mix modeling, sharing a vision of the future that takes advantage of the best performing functions of technology, like LLMs with datasets, and pairing it with a broad, strategic, even philosophical stance on how to approach attribution and use data to guide agency and client success. 

Sharpening Your Data Interpretation Skills

Next up is Kyle Block, Head of Research for Gradient Metrics who highlights a common pitfall for data analysts in Marketing Data Interpretation, which is focusing too much on methodology and not enough on interpretation.

"There seems to be a lot more of a focus on the methodology, the uniqueness of the method and that is where a lot of resources go,”  says Kyle. “I've always been a bit disappointed that the interpretation and the utility of those very impressive methods is downweighted.”

Kyle has a few simple questions data analysts can ask that will open up their interpretation abilities.

“The first question to ask is, where did this data come from, and what population is it claiming to represent? And secondly, what type of manipulation did this data have to go through? This can reveal if this data scales to a particular benchmark, is it normalized over the course of a year or six months, or is it a projection in the future?" 

Kyle’s suggestion to really understand the source of data and how it has been manipulated is critical to making informed business decisions through analysis.

Turning Data Into Intelligence

In Turning Data Into Intelligence, Aaron Clymer, founder and CEO of Data Clymer, stresses the importance of tools that can centralize data for analysis. 

"There's always some sort of business question you have that a specific application can't answer and you need to be able to be flexible and scale at the speed of your business and answer any questions,” explains Aaron.

“If there are applications out there that can solve the problems of a specific department or specific use case, that's awesome to have that, but eventually you want to have all of your data in one place so you can always answer whatever that question is that you can't get out of a specific application."

Aaron also mentions that trustworthy data is critical to data analysis and deploying invalid, incorrect, or unsubstantiated data can really sink projects and confidence. 

Data Analysts And The Future

Data analysts are key players in shaping the future of marketing. As you continue to hone your skills in interpreting, clarifying, and creatively applying data, you’ll not only enhance your own career but also drive success for the businesses and agencies you support.

Remember, the true power of data analysis lies not in the data itself, but in how you use it to answer the critical questions that fuel business growth. Keep questioning, keep learning, and keep pushing the boundaries of what data can do.

For more detailed discussions, check out the full episodes linked above, subscribe to our podcast, share this episode with your colleagues, and join the NinjaCat newsletter for more exclusive content tailored to data analysis professionals.

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