From The Trenches Part 4: From Marketing Specialist To Strategist

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Digital Marketing job titles have been rather like a jungle lately. When we see “Marketing Lead” on someone’s resume, is that a Lead Specialist or a Team Lead? We’re all familiar with the term “Marketing Specialist”, but what exactly is a Strategist?

To make sense of the Digital Marketing world, maybe we need to get titles out of our heads and go back to a concept from Sangeet Paul Choudhary’s book “Reshuffle” on the framework of work-as-a-service vs. results-as-a-service vs. outcomes-as-a-service.

Here’s how I would map it out for the various Marketing roles:

Work-As-A-ServiceResults-As-A-ServiceOutcomes-As-A-Service
WhatSet up campaignsDrive ROAS to or beyond targetsSet ROAS targets and deliver revenue
Who (Before)Marketing Specialist AgenciesManager DirectorVP CMO
Who (After)Agencies, increasingly automated with AIMarketing Strategist AgenciesHead of Growth

Can you see how the entire ladder has flattened? The biggest few companies that rely significantly on paid marketing can afford to operate with in-house teams following the “Before” org structure, but most companies are mid-size or smaller and would find the “After” configuration to be more scalable and flexible.

You can also see that in the “Before” configuration, the centre of gravity was at work-as-a-service, but with data and bidding automation driving the “After” situation, results-as-a-service becomes the baseline. Because middle management was responsible for turning work-as-a-service into results-as-a-service, when everybody moves up, the organization flattens.

AI In Bidding Isn’t New. The Question Is Where The AI Sits.

AI has existed in paid search bidding for well over a decade. Although most advertisers used manual bidding prior to the introduction of Smart Bidding in 2016, the largest ones were able to set and adjust bids using machine learning algorithms developed in-house, which led to a great efficiency advantage over advertisers with less resources.

With the advent of Smart Bidding, Performance Max, Demand Gen and now AI Max, the point of leverage in paid search bidding is shifting. Even with manual bidding, the platform was already able to recommend optimizations. Now, new bidding tools can automate entire processes, even creating and deploying customized ad copy variations.

Being a Marketing Specialist was – and still is – a highly technical process, for now at least. The hierarchical nature of the “Before” job ladder was because efficient CPC (cost-per-click) bidding needed strong domain and analytical knowledge, built through years of experience and experimentation. Specialists needed strong mentorship to develop that expertise. Also, the complexity of campaign setup meant that work-as-a-service held considerable value, especially before Smart Bidding.

Now that more of bidding happens in a “black box”, we have less control over driving results. The AI driving bidding efficiency now sits firmly with platforms, although in-house analytics are still important to inform targeting and capital allocation strategy and to measure performance. Campaign management complexity hasn’t gone down that much yet, because we still must choose between the traditional Smart Bidding algos and the newer campaign types. But with fewer bidding levers in the platform, the focus for campaign management teams is shifting away from work-as-a-service and towards results-as-a-service.

Results-As-A-Service Mean We All Need To Own ROI

As we move our mindset from “setting up campaigns” to “increasing ROAS (Return on Ad Spend)” or “reducing CAC (Customer Acquisition Cost)”, everyone needs to become more data-literate. However, this doesn’t have to be rocket science.

Conceptually, ROAS is your P&L, because it’s your revenue divided by your cost. If your ROAS is greater than your cost, i.e. your ROAS is greater than 1, you’re profitable. Everyone managing campaigns, even the teams who are hands-on-keyboard in platforms, need to understand the mechanics of CPM (Cost per Mile), CTR (Click-Through Rate), and CVR (Conversion Rate) to understand what drives ROAS and diagnose performance trends.

Specifically, when your ROAS dips, you’ll want to focus on the following questions:

  • Has traffic gotten more expensive on your channels?
  • How is this driven by the competitive landscape?
  • Are consumers interacting less with your ads? Check if your creatives might be fatiguing.
  • Are you getting less qualified traffic? Is this related to the placements you’re showing up on? Can you test into different targeting?

And if the term “marketing attribution” sounds very technical to you, think of it as how your company bakes their business model into marketing:

  • Lookback periods are the amount of time your business thinks it takes for ads to influence and drive purchase decisions.
  • Last-touch, first-touch and multi-touch attribution reflect decisions about how to give credit to different channels that a customer interacts with, knowing that people are engaging with an increasing number of digital touch points.
  • Media Mix Modelling (MMM) is a machine learning driven approach to predicting how your company’s total revenue moves with investing in different channels.

You don’t need to be too intimidated by coding (AI can help here too) nor to set up machine learning from scratch, but you should understand the formulas for essential channel metrics and be able to translate them into business terms.  And then, apply those to your channel to move from the “what” to the “why” and the “so what / what’s next”.  

Data fluency that used to happen at the Manager and Group Marketing Manager level now must happen at the Individual Contributor (IC) level – which is why every paid marketer needs to invest time into having a deep understanding of metrics and funnel mechanics. This is table stakes because with AI, knowing how to toggle settings in an ad platform is not enough to be a human’s secret sauce anymore – platforms could take that away from us anytime.

Of course, one big thing happened last week which is that ChatGPT announced the integrations of Etsy, Shopify, and a whole slew of apps into their interface. This probably isn’t the end of the story yet as OpenAI is in the thick of hiring product and engineering talent to drive their growth with B2B and B2C audiences.

In Part 5, I’m going to talk about how shifts in consumer pathways to interact with brands will mean content is coming to the fore as a key strategic pillar and driving the need for multi-channel fluency in marketing leadership. I’ll also talk more about how my former job at Expedia has evolved, reflecting how the positioning of paid media channels is changing in businesses.

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