{"id":108514,"date":"2015-06-04T16:45:00","date_gmt":"2015-06-04T21:45:00","guid":{"rendered":"https:\/\/www.dacgroup.com\/the-professional-outlook-for-digital-marketers-in-the-face-of-automation-2\/"},"modified":"2024-12-20T09:24:42","modified_gmt":"2024-12-20T14:24:42","slug":"the-professional-outlook-for-digital-marketers-in-the-face-of-automation-2","status":"publish","type":"post","link":"https:\/\/www.dacgroup.com\/en-gb\/insights\/blog\/strategy\/the-professional-outlook-for-digital-marketers-in-the-face-of-automation-2\/","title":{"rendered":"The Professional Outlook for Digital Marketers in the Face of Automation"},"content":{"rendered":"

Like many of you, I jumped ship from a career in another industry into the \u201ccutting-edge\u201d world of digital marketing. Migrating to an industry in high demand and experiencing unprecedented growth seemed like a very smart and sensible choice. But, following a year of working with various software applications, I grew suspicious of automation\u2019s role in my career. Now, after an introduction to a very compelling argument by Nicholas Carr in his latest book, The Glass Cage<\/em>, I\u2019m finding that the outlook for \u201ccutting-edge\u201d digital marketing jobs isn\u2019t exactly what I once thought it was.<\/p>\n

Automation Makes Sense<\/h2>\n

Digital marketing<\/a> has experienced monumental growth in recent years, sparking an explosion of new businesses, jobs, tools, and skills – all designed to help organizations zero in on target segments with a new standard of measurable efficiency and precision. The initial growth spurt was met with some growing pains, requiring expertise to bridge the gap between new users and the new platform. This exposed a great opportunity for agencies and marketers alike – which was quickly exploited.<\/p>\n

With software as the backbone, the tools and platforms in this industry iterated and evolved at a frenetic pace – having quickly transformed from a primordial soup of simple tools (by today\u2019s standards) into a suite of sophisticated, nimble, data-driven, self-serve platforms. Today, Google AdWords hosts millions of advertisers, and arguably several hundred thousand expert users who use the platform on a daily basis, driving a predicted spend of $103B online in 2019<\/a>, more than broadcast and cable television combined.<\/p>\n

Woven into the DNA of these platforms, however, is the unstoppable force of automation. The more, the faster, and the better search ads can be created and delivered with all of the right extensions and features, the more revenue the industry stands to generate. With gargantuan crowds being steered by a technology giant like Google, to the tune of billions of dollars annually, the automation of these processes is a most obvious and sensible strategy. As a consequence, online advertising has become more of a commodity than we think.<\/p>\n

According to Nicholas Carr, the \u201canalytic information worker\u201d is certainly subject to the effects of automation. And being at the mercy of one of the most innovative and agile companies the world has ever known, the SEM specialist is particularly vulnerable.<\/p>\n

Software automation has a few very simple goals: embed more and more skill into the software, limit human dependence, and gain efficiencies. These goals run counter to those of the digital marketer; he or she wants to gain skill, to grow as a professional, and to offer unique value as his or her career progresses.<\/p>\n

This raises very significant questions. What is the search engine marketer to do in the face of automation? How can we protect our value and build a marketable set of skills while Google, and other third party software, rapidly iterate toward complete automation? How will we fend off extinction? First, here\u2019s what not to do.<\/p>\n

Don\u2019t Become a Platform Expert<\/h2>\n

We all know that when Google announces an update, we have to learn what it\u2019s about (hopefully accompanied by a free lunch at their office with some cool swag to bring home), tell our team about it, and implement it in our accounts. We don\u2019t decide what to do next, Google does. Like a remora fish following a great white shark, digital marketers swim where the shark swims in order to eat. Tweet “Like a remora fish following a great white shark, digital marketers swim where the shark swims in order to eat.”]\u00a0Google makes a change, and millions of accounts need to change, whether we like it or not.<\/p>\n

We evolve our skills to accommodate the changes made to the search engine. We are what Harvard professor James Bright terms \u201cmachine operators\u201d – workers who operate machines designed to make the workflow more efficient. The machine is adjusted and managed by controls, such as levers and buttons, and is monitored by its operator. This contrasts with a \u201cmachinist,\u201d who uses the machine to suit his or her purposes according to his or her skill level (think of a trained carpenter using a circular saw).<\/p>\n

Machine operators apply themselves to a process as defined by the machine\u2019s architects. And so, the machine\u2019s design dictates what skills the machine operator contributes to the work. The machine operator, according to Bright\u2019s landmark research across multiple industries, suffers from a \u201cde-skilling\u201d as machines become more capable. Carr cites additional research, particularly studies conducted in the airline industry (which is a mature example of automation), that demonstrates both a convergence and drop in the skill level of all pilots. As the machines progress, they assume more and more of the workload, leaving operators with less and less responsibility, and consequently, less skill.<\/p>\n

Google Adwords is a very elaborate machine. The Adwords platform hosts millions of machine operators, pulling levers and pressing buttons day in and day out. As the platform continuously streamlines its processes<\/u>, creating increasingly frictionless software, the SEM specialist will fly the way of the pilot. With every update to make keyword uploads simpler, to make tagging smoother, to make keyword bid suggestions smarter<\/u>, and changes of the sort, the demands of the specialist will lessen and the province of SEM expertise will shrink. We will be inevitably relegated to monitoring accounts and maybe to intervening in the event of errors or problems – something Carr shows results in a disengaged workforce due to limited active participation. Platform expertise will lead you down a road of basic, common, easy-to-acquire skills, and leave you occupying a less and less interesting job.<\/p>\n

Make Way For Automated Bidding Platforms<\/h2>\n

I recently had the privilege of using a third party automated bid management platform this year. Anticipating an incredible learning opportunity, I dove into hours of webinars describing the mechanics of the system. The theory of the tool was very interesting – predictive modelling that integrates user behaviour, aggressive bid strategies to test predictions, and more. But learning the theory was akin to learning the aerodynamics that are particular to a specific modern aircraft: very interesting, but not easily applied to piloting said aircraft, rendering it a rather non-marketable skill.\u00a0 My actual learning came in the form of interface navigation, report creation, and basic parameter changes – the algorithm did most of the heavy lifting, whether I knew how it worked or not. This, of course, is somewhat of an over-simplification, but it serves as a great example of things to come.<\/p>\n

Additionally, though many SEM specialists hold mistrust of such automated tools, my experience showed that the software can deliver impressive results. Regardless, these tools (like all software) are only going to get more powerful, more sophisticated, more effective, and easier to use as time goes on. If software is successfully trading billions of dollars in the financial markets today, displacing tens of thousands of traders out of their jobs, eventually these processes will be adapted to keyword auctions in Google. It\u2019s not going to be easy for a human to keep up with the rushing stream of data underpinning the automated decision processes that these platforms will soon perform.<\/p>\n

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Don\u2019t Become a Plain Old Analyst<\/h2>\n

It\u2019s a common sense theory that with the rise of automation, the analyst is liberated from technical and manual tasks, and is now free to perform deeper analyses and more nuanced work. Upon examining that logical connection, the details of that corollary appear a little fuzzy. Carr demonstrates that the anticipated liberation from more routine tasks simply doesn\u2019t materialize, across a number of fields.<\/p>\n

With additional layers of automation, the speed at which information is processed far outstrips what the human mind can keep track of (I already noticed this with the automated bidding platform). It becomes increasingly difficult to implement changes proposed by limited \u201chuman analytics\u201d when the system is mechanically and informationally complex. The layers that automation erects between the operator and task create a distance, where the operator has no real feel for what lies beneath the code. The specialist will slowly have a weakening understanding of the workings of the process, and passivity results. The tool becomes more opaque until it is eventually a black box.<\/p>\n

Carr illustrates that automation creates a skill \u201cdegeneration effect,\u201d where the mind performs more poorly the less cognitive lifting it does. The less we participate, the more our skills atrophy and so too our capacities for higher functions. This effect has been observed after automation has been introduced in multiple industries, including the medical profession, the airline industry, finance, and more.<\/p>\n

Of course, not all automation results in the degeneration effect. For example, the automation of purely repetitive tasks, or information organization and retrieval, free up the human for more subtle and complex work. Features aiding in bulk uploads, or QA for URLs, are great time savers and reduce human error, allowing us to spend our time on deeper issues. But we are moving far beyond this degree of automation. With Google at the helm, machine learning and big data will continue to charge forward and further encroach on \u201cSEM expertise\u201d.<\/p>\n

So what\u2019s left for someone working with search engines? To find the answer, one must accept automation as a given, and build one\u2019s career around that assumption, looking for opportunities borne out of the software revolution.<\/p>\n

Anticipate Strategic Differentiation<\/h2>\n

Both software providers and agencies alike will have to pursue sustainable competitive advantages if they expect to last in the automated age.<\/p>\n

It\u2019s a safe assumption that Google will continue to grow, and will maintain a free-to-use platform that is common to all clients<\/u> (Mom & Pop shops and Fortune 500 retailers both use the same system). Third party software businesses will likely step in to offer a layer of automated customization to particular business types and particular verticals looking to gain an advantage of their competition.<\/p>\n

The digital agency value proposition will have to adapt to fit into this picture. Some agencies may design their own proprietary software, effectively becoming software companies. Others will broker software licenses to clients, and consult with these vendors on behalf of clients.<\/p>\n

In all cases, the SEM specialist will have to insert himself or herself into a role that informs decisions made around these tools. And in order to contribute value, the specialist of the future will have to know something that machines don\u2019t easily know – which implies extending themselves beyond the boundaries of the platform\u2019s purview.<\/p>\n

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