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Marketing analytics: are you a data-savvy marketer?

Published 1 June 2022 in Management • 6 min read

Data-driven marketing requires a certain level of data-savviness to cut through the noise and realize the most value from marketing analytics 

 

Advances in quantitative analytics are permeating every aspect of digital marketing. But what exactly is marketing analytics? Data-driven marketing is the process of optimizing brand communications based on customer information. Netflix, for example, collects large amounts of data from its 222 million subscribers worldwide, which it uses to create its recommendation algorithm. Why? Because the data says it will work, and generally, it does. 

Indeed, Nicolas Chu, Professor of Practice in the School of Marketing at UNSW Business School, said there has been a definite shift towards digital post-COVID. “While for some companies, paid search, social advertising, and other algorithmic channels were just a nice addition to more traditional channels, it has radically changed during the pandemic and became at the core of any advertising strategy,” he said. “COVID accelerated the shift to digital that heavily relies on certain forms of tracking, i.e., cookies, that will soon become obsolete.” 

So, while data allows marketers the ability to solve some of their most complex challenges, it also presents new challenges. How can marketers who aren’t data analysts benefit from its vast potential? 

According to Dr David Botkin, Principal of Dave Botkin Consulting LLC, all marketers today need to become more data-savvy, but this doesn’t necessarily mean they need a PhD in data science. Being data-savvy is more about recognizing what data might be beneficial, said Botkin, who recently spoke with UNSW Business School’s Prof. Chu about some of the biggest challenges facing marketers at the 2022 Marketing Analytics Symposium – Sydney (MASS). 

“Digital marketing analytics has radically changed during the pandemic and became the core of advertising strategies.”
- Nicholas Chu

Trends in data science: insights from Silicon Valley 

Throughout his career, Botkin has built and run analytics and data engineering teams in startups and Fortune 50 companies. As a former physicist turned data scientist who started his career at IBM, he ‘retired’ in 2018 to focus on analytics consulting and advisory services through his firm, Dave Botkin Consulting, LLC. Based in Silicon Valley, California, he advises clients in e-commerce, mobile gaming, streaming audio, healthcare, the internet of things (IoT) and realizing more value from data. 

Botkin is a former Senior Director of Marketing Analytics in Google’s Ads business, where his teams evaluated marketing program effectiveness and developed machine-learning models to route leads to sales. In addition, he led analytics at Square, Disney Interactive Games, and Playdom, which Disney acquired in 2010, where he used data to help Disney create and market social, mobile, console and MMO (massively multiplayer online) games. He also has a PhD in Physics from UC Berkeley and an MBA from the Haas School of Business. 

“The analytics being done today to optimize products is increasingly overlapping with marketing analytics”, he said. “In Silicon Valley now, for example, there is a lot of innovation around pulling data from product and marketing customer touchpoints into one data store and making it available to marketers in formats they can consume. I think people are very interested in customer 360 – understanding every touchpoint that a customer has with your company and reacting appropriately to that. 

“If someone has been a long-time loyal user and calls customer support, and later has some problem with their product and calls again, you want to know everything that’s happened to make decisions about refunds, offers or upsell with more context about who they are and how they perceive the company, and that is something that a lot of data and integration of data is making possible. It was a lot harder in the past.” 

Digital Strategy & Analytics

Build an integrated understanding of digital strategies and data analytics
There’s a creative side to marketing and a consumer psychological side, and it’s hard to get that full mix in any one person.

Marketers today need to be able to engage with data analysts 

With great power comes great responsibility. As analysts dig in without enough discipline, they may just be analyzing noise.  

“A lot of what people dig into, I think, is noise,” Botkin said. “So, it puts a premium on a marketers’ ability, or an analyst’s ability, to understand what’s important to focus on; what’s the lever that will help us drive the business forward, versus a rabbit hole that’s not going to go anywhere? I think that’s a skillset marketers haven’t needed as much in the past, but that is becoming a premium.”  

So, data provides a unique challenge and a huge opportunity for marketers. “If you’re an online marketer, you have five different ad networks telling you how they’re doing, hourly if you want, and pumping data into your data warehouse… there’s just a limitless number of things that you could look at, and it’s important to be strategic in how you think about using that data,” Botkin said. 

While marketers do need to become more data-savvy, one of the best and easiest ways to do this is to make friends with a data analyst and learn how to engage with them in a mutually beneficial way. “If you have a savvy data marketer who can get in there and run their data and focus on things that will help them improve their marketing efforts, that is a great skill set for a modern marketer to have.” 

Marketers can’t possibly tick all the boxes – there is too much that they need to do and not enough time to become good at everything. “There’s a creative side to marketing and a consumer psychological side, and it’s hard to get that full mix in any one person. If you rely on all marketers to be like that, you need a team of unicorns, and it’s hard to find them. If you’re a senior marketer, you need to be able to have analysts on your team and engage with them productively, so they work on the right things.” 

With the rise of data science and the number of graduates increasing, now is a good time for marketers to learn as much as they can from graduates and offer something in return. “There’s been an explosion in the number of talented people who could work on significant marketing problems that would help you know your business, but they don’t understand marketing; you almost need to teach it from scratch,” Botkin explained. 

“So, marketers need data savviness, but data analysts also need business savviness and marketing savviness to work on the right problems and narrow the scope of the kinds of analysis they’re working on.”  

Marketing analytics requires marketing engineering 

Another unsolved problem in marketing is engineering – a systematic approach to utilizing data and knowledge to drive effective marketing decision-making and implementation through a technology-enabled and model-supported decision process. 

“There’s a need to be able to advocate for the tools and systems that you need, to build those out, and to modernize them over time,” Botkin explained. “So, if you’re transforming a legacy marketing team and haven’t built those systems or built them from scratch, or if you’re at a younger company and just building them up, there will be that challenge. Getting the systems and the data in place is one challenge, but then using that to sort of propel yourself forward is the next one, and that’s going to be sort of the marketing analytics part.”  

Finally, he said, marketers also need to get better at thinking about the long-term value of customer engagement. “I think there’s a challenge of making sure that you’re keeping your eye on the long-term value of customer relationships – it’s not about sending 20 emails until your customers open it or unsubscribe.”  

This article first appeared on the UNSW business school website. 

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