Sun Jan 06 19:02:44 PST 2019

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New Filters
As markets evolve, the types of noise (affiliate, arbitrage, double dipping ads,
dictionary attacks, deceptive ads, etc.
change and search engines must come up
with new ways to protect the relevancy of their ads.
Google has blocked some forms of ads using a mixture of sophisticated algorithms
and editorial guidelines, but they have also began to look at ways of pricing noise
out of the market by discounting ads for trusted sources and charging new
advertisers, unproven advertisers, or abusive advertisers premiums to be displayed.
Buying Trust Over Time
In much the same way that old domains may be trusted more in organic search
results as they age and gain links, Google may trust proven advertisers and proven
websites more, and give them a discount for the trust they have built up.
Just by having an AdWords account, spending money, and not being abusive, your
ad account gains some level of trust.
Free Market Feedback
Google keeps collecting more and more market data using a wide array of data
points along the supply chain. They can see relative changes in a host of areas:
? Brand awareness and search volumes and trends
? News trends and content production trends
? Number of advertisers, types of advertisers, bid prices and trends
? User acceptance via conversion data and their toolbar
? General trust based on the link graph and surfing trends via their
toolbar
? Keyword relationships (based on AdWords accounts and text analysis
of web content

? Conversion data (via Google Analytics, Google AdWords Conversion
Tracker, and Google Website Optimizer

? Conversion data via Google Checkout
Each of these tools layered on top of one another add to how much value Google
can extract by making their ad platform more relevant and more efficient. The
tools that Google offer cost them next to nothing in regards to the value they help
Google create by offering Google a clearer picture of the market.
Deception as a Filter
Google keeps collecting more and more market data using a wide array of data
points.