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Data Summit Connect
DATA SUMMIT CONNECT
May 24-26, 2021
We can't get together in Boston in May, but you can still see where the world of big data and data science is going and find out how to get there first by joining us for Data Summit Connect, a free series of video webinars that will run from June 9 - 11. In addition, we're offering a day of ...

AI, Data Analytics & Insights Summit Online
AI, DATA ANALYTICS & INSIGHTS SUMMIT ONLINE
April 15-16, 2021
KEY TOPICS addressed by case studies, interactive presentations, round tables and panel discussions:
  • How AI-powered personalization improves user experience
  • How are we able to achieve Algorithmic Transparency in Artificial Intelligence?
  • How to overcome c...

BIG DATA and ANALYTICS SUMMIT CANADA
BIG DATA AND ANALYTICS SUMMIT CANADA
March 03-04, 2021
The Big Data & Analytics Summit Canada is the only event for data and analytics leaders where you can connect with hundreds of like-minded peers to discuss big data business and technical uses, AI and ROI optimization with analytics.

C-SUITE ON DECK

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Q&A With Thomas Zawacki, Chief Digital Officer- Strategy & Innovation At Data Axle

January 27, 2021 / Media 7
SHARESHARESHARE
Thomas Zawacki, Chief Digital Officer- Strategy & Innovation at Data Axle, is an accomplished business leader, motivator, and innovator with a successful track record in both established and entrepreneurial settings. He is known for consistently achieving positive financial outcomes via outstanding revenue growth, product innovation, marketing strategy, and operational efficiencies.

Consider the four C’s of marketing strategy: customer, channel, creative, and conversion. Using data analysis and AI/ML predictive modeling, weigh each element differently depending on your KPIs.



MEDIA 7: Please take us through your professional journey. What prompted/inspired you to join Data Axle?
THOMAS ZAWACKI: My career has come full circle. I graduated from college as an anthropologist, with a bent toward technology. My two passions at that time—outside of drinking and traveling were coding and anthropology.

Anthropology is all about immersing yourself in cultures and understanding what makes them tick. It might have seemed like a strange choice for a major to my parents, but it really laid the perfect groundwork for my journey in digital marketing. In the early days of the internet, I was fortunate to be part of the team that built the first-ever banner placed online. Back then, we were building the foundational elements of the digital marketing industry, and doing so was all rooted in customer empathy, understanding how people were using new technology to improve their lives, and inventing new ways for brands to participate.

As the behavior of consumers and business customers shifted, my career shifted as well. Over time, website usage evolved into social and mobile usage. I pivoted my career to helping brands communicate within social networks and helping Fortune 500 companies to transform their businesses for a mobile world. Basic e-commerce and digital advertising became mobile commerce and mobile advertising within the confines of a much smaller screen. Then came the next big sea change in business strategy—the use of data and artificial intelligence to optimize consumer experiences. And so those were the areas where I refocused my career.

The common thread throughout my career has been the triangulation of consumer behavior, technology innovation, and business needs. That’s what brought me to Data Axle. At Data Axle, I’m applying all of the same techniques and methods that I learned back in my anthropology days to use data and artificial intelligence and understand what makes consumers and business customers tick. Then, we leverage those insights to help Fortune 500 companies transform their businesses and exceed their goals.

M7: What according to you is the best way to find a qualified audience for your platform?
TZ: There are four levels of data and intelligence that I would use to help a customer determine which audience to target. First, start with foundational data—basic elements about your audience that don’t change much over time. Depending on your goals, that might be demographics or firmographics. But whatever the case, accuracy is absolutely essential at this foundational level as it drives downstream marketing performance.

Once you have your foundational data, you want to layer on interests and psychographics. You might be targeting moms, but there’s a big difference between moms who garden and those who love heavy metal. You need to be able to acknowledge who these people are at a human level within your marketing, and that’s what you achieve with this second layer of intelligence.

At the third level, as we get more focused on recency, you want to look at whether a person is in the market for your particular product at that time, or has a life-stage trigger related to needing new items. So again, if an auto company is targeting moms with an SUV, they’ll want to know who within your target audience has watched a video or read a consumer report on SUVs, and perhaps had a new baby within the past 30 days. In other words, you’re looking for intent or behavioral observations that would suggest they’re looking to convert sometime soon.

Finally, at the very top of the customer intelligence pyramid are moments: Is it the right moment to communicate with a person who has demonstrated intent to buy? Is it the right time and place? Are they in the right mindset to give your brand permission to talk to them as a potential customer? That’s what we’re talking about when we talk about real-time marketing to your target audience.

You can’t make everyone happy all of the time, but if you lead with empathy, you can minimize risk and deliver strong performance across a wide variety of measures.



M7: What marketing channels do you use and which ones do you see as the most promising given your target customers?
TZ: As an omnichannel marketing partner, the bigger question here at Data Axle would be, “Which channels don’t you use?” We live in a world where media consumption is incredibly fragmented, even within a given channel. Companies need to contemplate all channels without bias to determine which ones are going to help them reach consumers in the right moment and with the best economic ROI for the brand, but also the best ROI in customer satisfaction.

Consider the four C’s of marketing strategy: customer, channel, creative, and conversion. Using data analysis and AI/ML predictive modeling, weigh each element differently depending on your KPIs. The ideal media mix for each company and each program is going to be different, so you need to be open to all of them and let data/intelligence lead.

M7: What do you see as the most noticeable change right now happening in the workforce, encouraged by the rise of digital technologies?
TZ: We’re living in a predictive world. As marketers, that just became a more daunting prospect than ever, given how the B2B and B2C worlds have collided in the pandemic. Our work and home lives used to be compartmentalized, and that’s just not the case anymore. We dip in and out of our business and personal personas all day long.

As consumers, we have come to expect ubiquitous optimized product experiences every day. And now, we expect those same experiences as business professionals and—importantly—as employees. We expect to have all of the capabilities we need to do our jobs, wherever and whenever we need them.

Consider the concept of becoming an “open-source business.” Buildings, offices, and cubes matter less than they ever have. The infrastructure of business capabilities is no longer hermetically sealed within a company’s walls, confined to the company LAN. Open-source software development was a tectonic shift from coding in secret offices by small teams of engineers to free source code open for development by a remote distributed community. Similarly, all aspects of businesses are now remote, distributed, and yet stable and efficient. We must find opportunities to succeed in this new open-source business environment. I’ll admit, I do miss my whiteboard though.

M7: What do you believe are the top three product marketing challenges in the post COVID-19 era?
TZ: Perhaps the top challenge faced by product marketers right now is identity resolution. Marketers need to be able to identify people as they move across channels and platforms. But, given the volume and velocity of data and platform proliferation, we have more IDs for a given person than ever before. In a matter of years, we’ve gone from perhaps 10 identifiers for a person to hundreds of identifiers. What’s particularly challenging is that more and more of them are probabilistic rather than deterministic, which means it’s incredibly hard to be confident that you’re accurately identifying individuals along their journey. That’s why we see so many examples of bad ad targeting out there today. (Please leave me alone, Zappos. And while I could rock them, those high-heeled shoes were for my wife’s birthday, I swear.)

Another challenge is the evolution from graphical user interfaces (GUI) to voice user interfaces (VUI). Marketers have made significant investments in creating beautiful visual experiences; however, people are shifting their journeys in a way that doesn’t require them to look at screens. They simply say, “hey” and ask Alexa, Siri or Google for directions, to play a song or to buy a gift—all without seeing or clicking on anything. Terms like affordance, nav taxonomy, indexing and CTR go away. Businesses and brands must complement their IA and UX visual design with a voice-activated UX at the same speed that consumers are shifting their behavior.

And finally, there’s privacy and data security. In a world where cross-channel personalization is more important than ever, marketers have to contend with a growing number of requirements and standards when it comes to legal and ethical compliance when managing customer data. It’s essential that marketers work with partners who prioritize keeping audience data and intelligence safe.

Consider the concept of becoming an “open-source business.” Buildings, offices, and cubes matter less than they ever have.



M7: In your digital marketing approach, how do you balance inbound and outbound marketing?
TZ: The most important part of balancing inbound and outbound marketing is being empathetic to the mindset of the individual consumer or business customer. An inbound prospect is already in the consideration phase. They’re seeking answers, and marketers have to be standing ready with real solutions to their problems. That’s incredibly different from someone you’re reaching with outbound marketing. That kind of outreach is all about awareness, and your goal is to essentially transform that outbound marketing into a positive inbound experience. If you’re sensitive to a person’s current mindset, you’re going to deliver a great inbound or outbound experience.

M7: How do you work with your marketing team in order to get the most out of them? Any advice for the budding marketers?
TZ: It’s all about empathy, really. As marketers, we serve a vast number of stakeholders—from the CEO, who has a specific set of business goals, to the chief product officer and development team, who want to ensure what they’re building is positioned as the best thing since the Bernie mittens meme. Then, of course, there are the consumers who receive all of your messaging, and their wants and needs can sometimes be in conflict with your internal stakeholders. On top of that, you’ve got shareholders and the press and any number of other parties who might have an interest in what your brand has to say.

Ultimately, as a marketer, you have to step back, take a deep breath and think about the hopes and dreams, and business requirements of each of your stakeholders and calibrate what you’re doing according to your audience in that given moment. You can’t make everyone happy all of the time, but if you lead with empathy, you can minimize risk and deliver strong performance across a wide variety of measures.


About Data Axle


Data Axle, formerly known as Infogroup, is a leading provider of data and real-time business intelligence solutions for enterprise, small business, nonprofit and political organizations. The company’s solutions enable clients to acquire and retain customers, and enhance their user experiences through proprietary business and consumer data, artificial intelligence/machine learning models, innovative software applications and expert professional services. Data Axle’s cloud-based platform delivers data and data updates in real-time via APIs, CRM integrations, SaaS, and managed services. Data Axle has 45+ years of experience helping organizations exceed their goals. For more information, visit www.data-axle.com.

SPOTLIGHT

Data Axle, formerly known as Infogroup, is a leading provider of data and real-time business intelligence solutions for enterprise, small business, nonprofit and political organizations. The company’s solutions enable clients to acquire and retain customers, and enhance their user experiences throug...

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EVENTS

Data Summit Connect
DATA SUMMIT CONNECT
May 24-26, 2021
We can't get together in Boston in May, but you can still see where the world of big data and data science is going and find out how to get there first by joining us for Data Summit Connect, a free series of video webinars that will run from June 9 - 11. In addition, we're offering a day of ...

AI, Data Analytics & Insights Summit Online
AI, DATA ANALYTICS & INSIGHTS SUMMIT ONLINE
April 15-16, 2021
KEY TOPICS addressed by case studies, interactive presentations, round tables and panel discussions:
  • How AI-powered personalization improves user experience
  • How are we able to achieve Algorithmic Transparency in Artificial Intelligence?
  • How to overcome c...

BIG DATA and ANALYTICS SUMMIT CANADA
BIG DATA AND ANALYTICS SUMMIT CANADA
March 03-04, 2021
The Big Data & Analytics Summit Canada is the only event for data and analytics leaders where you can connect with hundreds of like-minded peers to discuss big data business and technical uses, AI and ROI optimization with analytics.

DataAnalytics.Report

DataAnalytics.Report

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