I discuss the utility-maximizing routing function that optimized digital advertising plays in Does digital advertising create demand?, so I won’t repeat those arguments here. From my perspective, understanding the impact that the degradation in advertising efficiency wrought by ATT will have on overall mobile ad spend requires an acknowledgement of two things: 1) which advertisers have been driving growth for mobile ad platforms in recent history (the last 3-5 years), and 2) how do those advertisers allocate budget?
Direct response (DR) advertising, particularly from small and medium-sized businesses (SMB), has mostly driven the economic growth of mobile ad platforms in the past several years. This is demonstrable in the increase in the number of advertisers on eg. Facebook’s platform, which stood at five million in 2017, grew to 7 million in 2019, and now sits at more than 10 million. The largest advertising platforms view direct response ad dollars from small businesses as their most important source of revenue buoyancy. This is because, prior to ATT, new ad targeting tools allowed legacy business categories to connect with potential customers via digital advertising for the first time, but also because these tools allowed for the creation of whole new categories that couldn’t have existed absent these advertising tools. From Is it healthy for start-ups to spend so much money on user acquisition?:
The paid growth machine described above could only exist in the environment that has been created by Facebook and Google, especially for mobile developers. Facebook and Google are eminently efficient and measurable (transparency concerns around irrelevant video view metrics aside). A more incisive question than “What are the alternative channels to Facebook and Google for a company that relies on paid user acquisition?” is: Could a company that relies on paid user acquisition exist without Facebook and Google? Without very clear lines of attribution and measurement, could D2C brands exist? Mobile games? Meditation apps? Most travel apps? Mobile commerce apps? Some apps tap into deep wells of virality and experience frenzied growth without spending any money at all on paid marketing, but virality is more fickle than a finely-tuned media buying model (and, anyway, virality and paid user acquisition shouldn’t be mutually exclusive). Besides, virality has a tendency to peter out and evaporate.
The precision targeting of Facebook and Google’s machinery was the sine qua non of many product categories that consumers take for granted now but didn’t exist — at least, not at mass-market scale — on mobile even as recently as 2016. This machinery mostly created opportunities for SMBs with direct response advertising, allowing them to deploy ad spend predictably and often on tight recoup timelines. Some of the products that Facebook and Google, especially, rolled out to facilitate this automated targeting and budget distribution weren’t popular with large advertisers precisely because they took away so much control and transparency from the advertising optimization process so as to make it easier for SMBs to scale spend. From Understanding Google’s Universal App Campaign (UAC) changes:
The principal benefit of the UAC system is that it allows Google to do the heavy lifting of optimizing at the event level so that budget can be allocated to the combinations of creative / channel / targeting parameters that provide the highest levels of ROI. Given this, it’s also easy to understand why Google would make the decision to unify everything: many advertisers lack the infrastructure (and desire to build the infrastructure) that allows them to calculate granular LTV metrics, and they’d prefer to let Google handle that while they focus on product. The UAC interface is intuitive and easy to use: integrating all channels into it and only asking advertisers to set bids is an easy way to onboard advertisers who have no interest in or ability to build out user acquisition teams.
The empowerment of SMBs has mostly been provided by tools that automate targeting by using the user profiling mechanism via third-party conversion data that I describe in this article. These user profiles allow ad platforms to quickly understand product relevance for users and to allow for a level of product discovery and ad spend validation that would never be possible for small businesses otherwise. These tools — such as Facebook’s AEO and VO campaign types — created a virtuous circle of traffic targeting and conversion measurement for small advertisers that they could instantiate on small budgets without needing to waste large amounts of money in testing targeting segments and collecting data. The value of these tools to not only small business advertisers but also to Facebook is manifest: as I show in this article from 2017, Facebook’s quarterly ARPU and quarter-over-quarter ARPU rate of change increased upon the rollout of its AEO product.
And how do these direct response advertisers determine how to deploy advertising spend? Generally, they carefully construct recoup curves based on historical monetization rates from acquired cohorts and work backward from there into target bids based on some required profit margin. In contrast to brand advertisers, which often operate against budgets that are pre-determined and mostly not evaluated against real-time conversions (sales), direct response advertisers tend to not work with concrete budgets but instead use forward-looking curves to determine at what price any given cohort of users can be acquired. In other words: direct response advertising is undertaken on the basis of unit economics, not overall levels of spend, as I describe in this article.
Direct response advertisers as a group mostly focus on unit economics and scale total spend to whatever degree possible so long as the profit target is reached. If advertising efficiency is broadly impaired, in order to honor their operating standards, advertisers can either reduce spend or lengthen the timelines against which they must recoup spend. I discuss the peril of extending payback windows in this article, but in short: while increasing the length of a payback window allows the advertiser to increase bids and thus spend in the short term, it reduces the velocity of their deployed spend over time since they recycle recovered ad spend back into new campaigns at a slower rate.
This is all to say: if the efficiency of their ad spend decreases, direct response advertisers will spend less money on ads. Direct response advertisers mostly don’t have budget goals, or at least, they don’t have them in the long run: DR advertisers spend against performance standards and absolutely will decrease ad spend as campaign performance degrades because any given cohort funds the next.
The notion that advertisers will consolidate money into their top ad channels because ad budget must be spent somewhere is fanciful: as advertising efficiency materially degrades as expected with ATT and other privacy changes, direct response advertisers — but especially SMBs, operating on thin margins and without large balance sheets — will have less money to spend. Like a glacier receding into arctic waters, mobile ad spend can disappear: unable to recoup enough money to fund growth, the direct response advertiser simply has to spend less than it previously did in the face of a step-change in advertising performance.