The Rise of Platform Automation in Performance Media
No one knows more about our potential consumers at the moment before we meet them than the digital marketing platforms. Platforms like Google, Facebook, Amazon, and Pinterest have a better understanding of how our consumers are spending their time each day. After all, they are at the connection point, witnessing every click, view, like, or share that a consumer commits leading up to an engagement with our brands.
To take advantage of that knowledge, the digital platforms require advertisers to trust their increasing levels of automation to help us find our new customers. But, how do we trust the platforms’ algorithms to find the right consumers who align with our business needs? How do we ensure that we give them the strongest signals that result in us finding our ideal consumers?
In this blog series, we’ll share insights on the current drive for more digital marketing automation platforms, offer solutions for handling platform automation, and discuss the Adlucent approach for driving more value in this new world.
LEVERAGING KNOWN DATA TO UNDERSTAND CUSTOMER NEEDS
Data about consumers and their interactions with our sites, ads, posts, and emails never stops flowing. In the time it took you to read to this point in the article, a typical advertiser has collected over 1,500 impressions, driving over a dozen clicks and the resulting conversions. With each of these ad interactions that are followed by some sort of value-based impact for our business, we look to understand more about where those consumers are in their journey. What do they need now? What will they need next?
Adlucent’s tools, algorithms, account teams, data scientists, and AI do a great job of synthesizing the value of those ad interactions through the lens of the subsequent actions taken by consumers on our clients’ sites. But, regardless of the scale of what we do “see,” millions of more consumer interactions take place from those same people across the digital platforms. Engagement with other searches that leads to other websites. Engagements with display ads. Some with competitors. Even more for other services.
The world of our consumers’ experiences is much more expansive than the digital connections we’re able to witness in our scope with our advertisers. Suppose a consumer is planning a move, a baby, a wedding, other major life events, or even considering a routine daily purchase. In that case, the digital platforms they interact with can likely forecast that potential need with stunning accuracy. These digital platforms can understand the overall breadth of the consumers’ actions – at scale. As advertisers, we aren’t privy to those touchpoints beyond the engagement with our brands. This is why we need a way to leverage some form of platform automation in our digital media programs to help us make sense of what consumers likely need and help identify our next best customer.
WHAT IS DIGITAL MARKETING AUTOMATION?
For the point of our discussion, we’re defining automation as the collective technology that allows us to gather, organize, and make decisions on big and little data sets – how to value various consumer interaction points.
We’re focusing on automation tools available at the platform level, but there are three key “owners” of automation that can help drive a performance media program:
1. Advertising Platform Automation: These automation tools are typically “built-in” to the platform. Think of algorithms developed by the platform to connect consumer actions (with your ads and sites and others) and identify a value you should be willing to pay for your ad(s). Examples might include Google’s tROAS or automation built into Smart Shopping or Performance Max Campaigns.
2. Agency Automation: Any performance media agency that is driving digital media for their clients should employ some form of automation, whether it’s a proprietary tool (Adlucent’s preference – we’ve spent 20+ years evolving our Deep Search™ platform) or a third-party technology (like Google’s SA360) that helps them make sense of the millions of touchpoints and transactions that they’re tracking for their clients. In the best cases, these tools are customized for each client’s needs to help drive valuable customers.
3. Advertiser Automation: If an advertiser doesn’t have an agency or third-party tool, they’re surely using some form of automation to gather data on digital interactions to scale their performance marketing programs. Additionally, advertisers are also typically using some system/s (CRM, CDP, etc.) to gather and help interpret consumer touchpoints after advertising. Those systems often have automation that helps define touchpoints with advertisers’ brands across a website, stores, phone, etc.
TO TRUST IN DIGITAL MARKETING AUTOMATION
The question of whether to trust automation to automatically bid your platform campaigns is not a binary on-or-off choice. You’re likely using some level of automation (see above) now, particularly if you’re leveraging an agency to support your digital marketing campaigns. It makes sense to allow automation to make some decisions – with guidance – at scale. It can react to changing market conditions, and the algorithms can run calculations on what works and what doesn’t much faster than any manual approach.
In recent years, advertisers have had the opportunity to leverage automation-heavy campaign solutions, such as Google’s tROAS or Smart Shopping, to make bid decisions. Ideally, these solutions excel at understanding where a consumer is in their purchase journey by combining data observed from consumers’ behavior along with the business objectives of advertiser programs to find the right customers at the right time.
Initially, automation can be intimidating because it can be perceived as relinquishing more control of your advertising program to the “hands of the platform.” But, fundamentally, the automation put forth by the platforms should be leveraged more analogously to cruise control than autopilot. It should be a tool in the toolkit, not used as a set-it-and-forget-it solution for maximizing your campaigns.
WHAT ARE THE BENEFITS OF USING MARKETING AUTOMATION TOOLS?
Although “a history of automation progress in advertising platforms” sounds like a fascinating intellectual dive, we’ll leave that for others to uncover for now. Suffice it to say that, at this point, there are a couple of factors at play that make now the time to test and engage with the platforms’ available automation tools :
The bidding algorithms are reaching a point where, given the proper controls and structure, they’re able to efficiently target desired customers in many of the tests that we’ve run. Google is undoubtedly leading the way in these solutions, specifically with tROAS, Smart Shopping and the evolution to Performance Max campaigns.
Platform automation is the only way to leverage the consumer information that the platforms understand about their customers, such as what they’ve engaged with outside of the advertiser’s programs.
When set right, the automation allows for much faster decision-making.
Often, there is cross-channel integration when you’re looking at consumers engaged with the same partners. For example, Google Ads is able to consider signals from YouTube, DV360, or even Gmail to understand more about the consumer. For Facebook, they can look across both Facebook and Instagram to determine consumer interest.
THE DRAWBACKS TO MARKETING AUTOMATION PLATFORMS
While there are many positives to leveraging automated tools, there are still some shortfalls that have to be considered when deciding how to use automated platform tools and setting the proper structure for your program:
Current automation solutions aren’t quite able to handle extreme or sudden market variances with extreme grace – at least not without some level of oversight from a strategic marketer who understands the larger landscape. Large fluctuations in demand driven by sales, social media, or simply high product turnover are not readily understood by platform automation, even by some of the savviest algorithms.
Platform automation solutions still only have the capability to align to a single numeric goal/KPI, such as ROAS or CPA. Complicated strategic goals that look at ROAS and acquisitions, for example, still need to be considered in the structure and data that the advertiser or agency team sets up. Even balancing advertising objectives between ecommerce sales and in-store sales may be difficult for platform automation to maximize both in a single campaign.
As with any algorithm, there’s a learning period where it has to gain enough data from prior experiences and align to the latest settings/structure to understand how to target consumers.
These platform automation tools cannot handle multi-touch datasets across multiple walled gardens in a graceful way (i.e., including the impact of Facebook impressions into Google Ads bidding).
Most platform automation does not include consideration for specific creative attributes and audience segmentation. For instance, if you know you only want to target the top 10% of households, most automation currently doesn’t provide controls for that targeting flexibility. Or, if your creative is geared more toward driving awareness vs. conversions, the automated tools may not understand that distinction.
As platform automation has improved over recent years, it’s become a necessary tool in a marketer’s arsenal. Automation helps marketers serve relevant, high-performing ads that align with the depth of total connections consumers have across digital platforms today. Clearly, Google’s tROAS and Smart Shopping campaigns are leading the industry in the space, and we expect to see these types of solutions increase with other platforms. As advertisers, we must test these solutions but keep close controls to ensure the platform’s algorithms are working with our business needs.
In our next posts, we’ll explore solutions that Adlucent is putting forth to drive more business value and share specific tactics to improve results. Contact us today if you’re excited to discuss this in more detail.
Ryan is VP of Strategy at Adlucent. He has over 15 years experience working with digital and multi-channel marketers to drive better results from their programs. His perspectives of online marketing are based on analyzing data-driven insights from an array of advertisers - from enterprise to start ups - as they capitalized on customer-centric, full-funnel programs across search, social, shopping and digital media.