Ever since the earliest days of digital marketing, the best marketers distinguished themselves not just through dedication and hard work, but also their ability to wield the tools of their trade. Anyone can upload an ad, but success is highly dependent on one’s ability to understand the meaning of every setting and the effectiveness of every targeting option.

The problem with this mastery is that it’s not scalable. There’s only so much work a marketer can do manually, after all – even if they’re brilliant at their job. Moreover, their skills are in such high demand that everyone but the largest advertisers cannot afford to work with them.

It isn’t in the best interest of the industry to have this inherent complexity. The digital marketing space works best when everyone has an opportunity to advertise to potential clients or at least a fair shot at setting up a successful campaign.

Both Google and Facebook – two of the largest ad platforms on the planet – have recently taken steps to rectify this situation. And while their approaches are different, both provide glimpses of the future that awaits all digital marketing.

By learning from these today, we can make sure we’re ready for tomorrow.

Less is more?

The concept which both Google and Facebook are currently beginning to embrace is that of increased reliance on algorithmic automation. Instead of having marketers set all of the parameters for their campaigns, some are now entrusted to proprietary algorithms which ostensibly provide better results.

Google went all in – but only for one ad category. Ever since 2017, it’s impossible to conduct an app install campaign on Google properties without using “App Campaigns” – a mechanism designed to remove most targeting decisions from the campaign creation process.

Facebook doesn’t restrict its decision automation to app campaigns but does limit its scope. The feature, named CBO (campaign budget optimization) is about to become mandatory in September. When it does, it will replace marketers’ ability to distribute their budget between ad sets. Facebook will handle the budget distribution automatically, diverting the largest share to the ad set, which shows the most promise.

Make no mistake; this is just the beginning. Every setting removed from the ad upload interface, every decision offloaded to the algorithms, serves multiple purposes for ad platforms:

  • Friction reduction – tasks like targeting and budget optimization are among the most difficult for the smallest advertisers, who aren’t well-versed in the methodologies and best practices of digital advertising. Replacing them with a “Trust us, we know best” prompt makes advertising more accessible for all.
  • Effectiveness barrier – for ad platforms to be popular, they need to be effective. Both Google and Facebook now trust their algorithms enough to be as good as humans (and often better) at specific tasks within the campaign cycle.
  • Self-powered improvement – control over an essential aspect of a campaign enables the platform holder to experiment proactively, rather than just analyzing data provided by others. Features offloaded to algorithms can evolve faster.
  • Performance Reliability – as ad platforms trust their algorithms, they genuinely want people to use them. Increased usage, based on their data, leads to better results for the users. When results are better, the trust in the platform grows – and with increased confidence come increased budgets.
  • Inventory Maximization – When algorithms decide on the inventory and its placement, they’re able to maximize the efficiency and the placements of this inventory.

What Does This Mean for Me?

With every passing day, advertising platforms’ reliance on algorithms for parts of their campaign management grows. Every step in that direction means that the best marketers – those who outsmart the competition every day – lose some of their technological edge over the system. Meanwhile, with lower entry barriers, an ever-increasing number of small advertisers flock to the ad platforms – empowered to use them for the first time. They aren’t savvy, but savviness is no longer required to get one’s ad in front of the audience.

The competition is shifting to the one thing that’s still bound to remain controlled by the advertisers: the content of the ad. Text, images, video, playable elements – these play an ever-greater role in determining the success of an advertisement.

Intelligent asset management is the new competitive battleground. With part of the process obscured, the mix of ingredients is the key to winning performance. Input the correct blend of creatives, copy, audience, and targeting objectives – and you’ll get better results than ever. Feed an ineffective mix to the AI, and it won’t be able to do much.

A multi-channel strategy is paramount. Different platforms have different approaches when it comes to inventory, audiences, and targeting. They also use different algorithms to make decisions about your ads. Loss of control over some processes on one platform can be negated by working with several of them – optimizing campaigns for platforms as well as optimizing platforms for campaigns.

Patience and trust are necessary. Algorithms need data to be truly effective, and assembling enough data takes time. If you’re used to trusting only yourself, don’t worry, you’re still in control – it’s just a different type of control. AI will surface more insights and recommendations for you to fine-tune your high-level strategy, research, and asset optimization while taking the labor-intensive campaign optimization off your shoulders.

 

At Bidalgo, we’re uniquely positioned to help marketers address the challenges posed by this new algorithm-driven reality and maximize its advantages. Our channel unification capabilities make it possible to execute an effective multi-channel strategy; our AI is built to analyze vast amounts of data to provide actionable insights about your user acquisition, creative and asset performance, and our automation is built to work in tandem with the automation implemented by the channels themselves.