Join or Die: Digital Advertising in the Age of Automation

all advertising falls into one of two buckets—Prospecting or Retargeting.

Contextual targeting is what traditional advertising was built upon, but obviously, it has its flaws.

There are times when we believe that Google’s recommended best practices would be more effective for a given campaign in the long term, but short-term goals or other events might force us to stray from those recommendations.

At this point in the game, your competitors have the same basic knowledge as you do.

In every case, allowing machine learning algorithms to process as much data as possible improves liquidity.

The client admitted that they stuck around because the agency celebrated improvements in Quality Score and decreases in cost per click. So the client, wrongfully, assumed that actual revenue growth would soon follow.

Manual CPC Google Search advertising primarily relies on contextual targeting.

The NASA engineers refer to this analogy as the H-Metaphor, which can be described as such: the humans chart the course, then rely on machines to manage the real-time calibrations.

Imagine that you were a human algorithm who needed to take all this knowledge (data) and translate it into a strategy. How would you create your own set of rules to test and refine over time?

As we discussed in Chapter 3, automation has changed all of this. We should no longer assume that bottom-funnel search terms are more valuable than top of funnel search terms. However, this traditional approach is still useful for many accounts.