The Science of Marketing: Adapting Skills for the Data-Driven Age

Writing exclusively for ExchangeWire, Tug CTO Eoin O'Neill (pictured below) outlines how the value of digital expertise has risen amid COVID-19, and explains why brands should broaden their perception of a promising marketer if they hope to thrive post-pandemic.

Digital skills have been moving up the employer wish list for some time, featuring in over 80% of UK job posts as a necessity pre-pandemic. But over the last 12 months, mass disruption has driven an even greater need — and nowhere more so than in marketing. Not only is ‘digital marketing specialist’ listed among LinkedIn’s top ten in-demand roles, but brands are also keen to bolster their strengths in social media advertising and analytics.

Of course, the rise of digitalised marketing isn’t news, but COVID-19 has pushed forward developments that weren’t set to gain traction for years. Skills once viewed as leading edge or nice-to-have are becoming essentials, especially after the challenges of 2020 demonstrated just how crucial they are: with low computer science proficiency leaving 37% of businesses unable to create specialist campaigns, and a lack of machine learning skills scuppering AI ambitions.

Urgent adaptation is clearly vital. As well as adjusting hiring processes, the industry must start casting its net wider and sourcing talent from different fields, including the often-overlooked realm of science, technology, engineering, and mathematics (STEM).


Understanding the new skills base

Traditionally, the main requirement for marketing professionals was a relevant qualification or experience. To an extent, that is still true: an understanding of how to define core objectives, formulate strategies, and apply varied tactics will always remain a key part of a marketer’s role. But this isn’t all they need. At a basic level, for instance, strong data management is crucial for every marketer to meet modern expectations of insight-driven decision making, efficiency, and performance.

For example, when it comes to post-cookie operations, the stakes will soon be even higher in terms of needing the right skill set. As third-party cookies fade out, new competencies will be crucial to keep personalisation, retargeting, frequency capping, and attribution running. Marketers will need better mastery of consented first-party data — in terms of tracking, segmentation and activation — and the capacity to wield targeting and measurement alternatives built around predictive modelling, rather than personal data. In short, they’ll have to be experts in machine learning and data analysis.

For an example of how these shifts are playing out, take search engine optimisation (SEO). Previously hampered by a high ratio of content to technical specialists, this area is seeing rising recognition that SEO pros need a logical mindset capable of handling refined analytics, such as differentiating correlation and causation. Moreover, demand is growing for technical and programming skills to fuel smarter recommendations about page speed, rendering, and lazy loading, as well as streamlined campaigns and closer developer collaboration.


Refreshing outmoded hiring processes

Eoin O'Neill, CTO, Tug

The in-house skills gap is a well-known problem. According to the IAB, 88% of advertisers, media owners, and agencies were already struggling to find the right candidates pre-pandemic, while the crisis made searches tough for a third of cross-sector firms in 2020. This situation, however, is unlikely to change until companies evolve how they source and onboard talent.

On the data side, hiring processes must stop prioritising complete-package analysts with limited technical experience, especially for senior positions. Although this may seem counterintuitive at a time where most roles are multi-faceted, covering too many bases at once often means in-depth knowledge is missing. Instead, organisations should build teams from the bottom up, bringing in junior workers with core capabilities (such as mechanical engineering and computer science graduates who can programme specific scripts and understand data sets) and nurturing them into well-rounded leaders.

In addition, if brands and agencies want to access candidates with skills and mindsets outside of the creative-centric marketing norm, they will need to explore wider talent pools. One space that offers a particularly valuable selection of transferrable and under-appreciated abilities is STEM. For example, an individual with a biology degree will be accustomed to running various tests and causal modelling, making them an ideal fit for steering data-led marketing campaigns and AI-powered analysis.

All of the above, however, must also consistently focus on addressing other gaps, such as the ongoing challenge of gender parity in several fields, including STEM and SEO. Despite positive initiatives such as Women in Technical SEO, the revelation that only 36 of the top 140 SEO players are women shows that there is some way to go. This makes it paramount for gender balance to be baked into each aspect of hiring and workforce procedures – from open hiring to promotion of exceptional achievers who can offer much-needed role models for aspiring young talent.


What’s next for tech-driven marketing?

It’s important to note that just because tech is playing a bigger role in marketing, it doesn’t mean humans are destined for an increasingly smaller part. If anything, automated tech frees people up to become more strategic and productive – it enables them to leverage data and analytics to enhance their efficiency, output, and potential. What will be most critical to safeguarding future marketing success is ensuring teams have the ability to do just that.

Right now, that means seeking out varied individuals with the capacity to take control of data and use technology to their advantage, not limiting hiring scope by only placing focus on traditional marketing graduates and professionals. In the years ahead, companies will need to continually nurture and support their marketing professionals, investing in development that continues their skills evolution and helps them use data as an objective tool for steering them towards better, and ever-more precise, decisions.