5 Skills All Marketing Analytics and Data Science Pros Need Today

Join us at the MADS conference in Washington, D.C., from Sept. 26 to 28, 2023. Learn more below and register with code KDN100 for $100 off your conference pass.

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5 Skills All Marketing Analytics and Data Science Pros Need Today
By Ann Gynn

Speed up and slow down. 

Every marketing analytics and data science professional encounters this seemingly incongruous challenge.

You must adapt to rapid changes, including the growing impact of machine learning and artificial intelligence. But you also have to pull it together in a meaningful and legally compliant way.

That’s the overarching theme several marketing analytics trailblazers and data innovators speaking at the Marketing Analytics & Data Science (MADS) conference identified. Fortunately, they’ve also shared some ideas on overcoming these challenges. (Get even more ideas, inspiration, and advice during the conference, September 26-28, in Washington, D.C.)


Data sources, rules, and relevance change quickly

“The toughest challenge is how quickly the skill sets and the industry are changing,” says Katie Robbert, CEO of Trust Insights. 

Traditional digital marketing avenues, such as organic search and content marketing, are evolving, particularly with the growing impact of artificial intelligence improvements. Social media platforms on which marketers once relied can no longer be counted on to build and influence audiences.

Robbert says this new world of digital marketing changes how and where you reach people. “It’s also going to be increasingly more difficult for marketing analytics practitioners to keep up with where they get their data,” she says.

Twenty years ago, having more data meant you were smarter, says Avinash Kaushik, chief strategy officer at Croud and member of the original Google Analytics launch team. “Now we have more data than God wants anybody to have. So being smart is all about being able to figure out what data to ignore so that you’re able to focus your attention.”

Guan Wang, senior director of marketing intelligence at Snowflake, agrees. He says analysts and scientists need “to bring the data together into one platform to make the AI and machine-learning workload happen.”

And that’s no easy task.

“Marketing intelligence [teams] work so hard because we’re dealing with [over 11,000] applications or solutions. This whole ecosystem is highly fragmented,” Wang says. 


But unifying data and deriving intelligence take time

Fragmented data sources and technologies make it difficult for marketing analytics practitioners to connect the dots in a strategic and actionable way, says Zontee Hou, director of strategy at Convince & Convert.

“More and more organizations recognize the opportunities and need for more unified data,” she says. 

But until they slow down and invest the time in unifying data, they’ll be stuck reporting metrics, not insights. 

Michael Bagalman, vice president of business intelligence and data science at Starz, sees a related challenge. 

“Practitioners must also grapple with efficiently integrating and analyzing vast datasets to glean actionable insights while addressing both the regulatory and ethical implications of data usage,” he says.

Doing so requires navigating intricate legal privacy frameworks like GDPR and CCPA and ensuring that any machine-learning and AI-interpreted algorithms lead to fair and unbiased decision-making, Bagalman explains.

It all adds up to a challenging work environment. To rise to the occasion, the experts recommend the following:


1. Get better at the non-tech side

While those challenges seem to center around technology, the way to address them starts with something else.

Marketing analysts should hone their skills to know who to talk to – and how to talk to them – to secure the information they have. Trust Insights’ Katie Robbert says it requires listening and asking questions to understand what they know that you need to take back to your team, audience, and stakeholders.

“You can teach anyone technical skills. People can follow the standard operating procedure,” she says. “The skill set that is so hard to teach is communication and listening.”


2. Improve your storytelling skills

By improving your communication skills, you’ll be well-positioned to follow Hou’s advice: “Weave a clear story in terms of how marketing data could and should guide the organization’s marketing team.”

She says you should tell a narrative that connects the dots, explains the how and where of a return on investment, and details actions possible not yet realized due to limited lines of sight.
“Teams need to come together cross-functionally and have buy-in from executives to truly solve this problem,” Zontee Hou of Convince & Convert says.


3. Sharpen your focus on business goals

Securing organization-wide support requires leaning into what the data can do for the business.

“Businesspeople want to see the business outcomes. Always remember to align business objectives with your key stakeholders,” Snowflake’s Guan Wang says, noting you should revisit that alignment regularly to ensure it’s still appropriate.

“Make sure they’re comfortable using the model and then constantly iterate. Machine learning is not just one report. You deliver many, many models,” he says.


4. Learn to balance business, legal, and ethical impacts

Aligning with business purposes also requires addressing the legal requirements around data. “(It’s) an intricate balance between data-driven marketing and maintaining individual privacy rights,” Starz’s Michael Bagalman says. “Striking this balance requires a deep understanding of legal frameworks, technical capabilities, and ethical considerations. Regulations like GDPR and CCPA have global implications, each with unique nuances that necessitate careful interpretation and implementation.”

You should set up a compliance system to address those laws as you introduce new marketing tools and data collection methods. “Ensuring data accuracy, transparency, and security demands robust technical infrastructure and ongoing monitoring,” he says.
"The complexity of these challenges requires collaboration between legal experts, data scientists, marketers, and ethicists to develop holistic solutions that respect both user rights and marketing effectiveness,” he says.

What does all that require from an analytics practitioner? 

Bagalman shares the lengthy list: legal/regulatory acumen, technical proficiency, understanding of ethical considerations, communication skills (particularly with non-technical stakeholders), collaboration, data governance, diversity and inclusion awareness, continuous learning, problem-solving, risk management, strategic thinking, adaptability, and empathy – truly understanding the consumer perspective on the ethics of data and privacy.


5. Model the impact

Are you ready to act now? Avinash Kaushik created a model that may help content-focused marketing analytics pros – the Impact Matrix. It enables you to answer these questions:

  • How sophisticated is the team’s analytics practice?
  • What’s the best way to get leaders/analysts away from low-value metrics?
  • How can you create a clear path to analytics glory?
  • How do you bring the role of machine learning and automation to the forefront?
  • What should be on the CMO’s dashboard vs. the director’s?

The matrix’s x-axis details how long a piece of content takes to become valuable – real-time, weekly, monthly, quarterly, or six-monthly. The y-axis runs from super tactical to super strategic. Kaushik walks through how to create it in more detail in this article.

He says, “The Impact Matrix will help you have that conversation based on a framework and then create a plan that says, ‘We’re here today. How do we get there?’”


Learn to conquer marketing analytics and data challenges

Are you and your marketing analytics team ready to go fast as technology and digital marketing evolve rapidly but take the time to get it all working the right way for your business? While these experts highlight potential solutions quickly here, they’ll slow down at the MADS conference with in-depth explanations and answer your questions in person.

Join us at the MADS conference in Washington, D.C., from Sept. 26 to 28, 2023. Learn more here and register with code KDN100 for $100 of your conference pass.