While you make some good points, I think you may be underestimating the feedback mechanisms of the industry.

Viewability measurement is in its infancy, and still has many issues. That said, it is fast becoming a standard measure, and any savvy display advertiser will be using it. At the end of the day, the ones most at risk are brand advertisers who aren't running direct response campaigns. They may have ad recall studies and Marketing Mix Modeling setups that give them some visibility, but there will always be some inventory wasted at the scale those advertisers are dealing with.

For direct response advertisers, things are getting better. While it may be harder to target some segments, and that % may be growing, the tools advertisers have available to them simply did not exist even a few years ago.

Take for example Google Analytics attribution and multi-channel reports. They have made a basic cross-channel attribution toolset available. To everyone. For free. Think about where the industry was even five years ago and let the impact of that sink in.

Facebook's acquisition of Atlas, Google's acquisition of Adometry, and other recent acquisitions in the bid management/dedicated attribution platform space are all pointing in one direction: better visibility into the contribution of your individual efforts.

I manage digital advertising for a living and have done so both client-side and at a top agency in the space. When it comes to the space, and in my not-so-humble opinion, the #1 thing clients wanted (and that I want doubly so now that I'm client-side) is better attribution.

When you are sitting on the types of data FB and Google are, you have many pieces of that puzzle, particularly the cross-channel and cross-device pieces. You also have the statistician brainpower and engineering talent to create the modeling tools that can give this visibility to advertisers. Why they haven't pushed harder on making that data visible is anyone's guess (I do wonder about how any negative revelations might impact their business), but the acquisitions seem like a big step in the right direction.

That said, digital media needs to go beyond static attribution models like: linear decay, time decay, U-shaped, first touch, last touch, etc. Instead, it needs to move more to the dynamic models, where data is assessed at the individual conversion path level. When you look at attribution at the channel or even campaign level, you are missing a ton of the story since the impact of say, a generic video ad vs. a laser-targeted retargeting ad can be night and day. Sure you might want to see channel data in aggregate, but you can't effectively optimize much at that level.

The advertising bubble savvy individuals in this industry are aware of those is video advertising. There's been a big hype train, CPMs are frothy, and everyone is switching to some sort of auto-play/auto-play-next-video format. Personally, I'm not convinced the value is really there at many of these CPMs, but I test and let the data decide.

The best thing companies like Google and Facebook can do to safeguard against any growing mistrust of online advertising efficacy is to keep improving their attribution tools, particularly for display and view-through performance.

Knowing what I do about the data available to me and its strengths/weaknesses I sometimes wish I was back in the days of last-touch models. There's few things as painful for me as knowing that better data exists to optimize against, but not having all the tools I need to get it because they are prohibitively expensive still for many budgets.