US DOJ lifts curtain on company’s search ad price manipulation

Search engine giant Google and its operation as a dangerous monopoly have been debated for years. Many have criticized the company’s unfair practices and the fact that other stakeholders continue to suffer losses.

Now, a new document from the US Department of Justice proves to the world how Google ended up manipulating ad auctions and inflating costs to better increase revenue.

The news comes as the America vs. Google antitrust trial included closing arguments and the final decision is still pending. But on the face of it, Google might not be able to continue its powerful monopolistic behavior without being penalized.

Most of the final arguments are presented in a massive 140-slide presentation emphasizing his unfair position as a search advertising specialist.

The DOJ called the conduct of controlling prices and excluding competition offensive and unfair. Furthermore, Google’s privileged position meant that no other competing advertising prices needed to be reviewed, while other testimony explained that no internal documents were even provided or requested as to the how he was allowed to charge so many unfair prices. strategies. This is the power of monopoly.

Shocking quotes were thrust into the spotlight, including those from several people at Google discussing raising advertising prices to increase the company’s revenue. The company tried long and hard to arrive at better pricing strategies where the new prices were higher than the old ones.

Google had many levers it could use to change the bidding design for ads to achieve a profitable outcome that it could massively benefit from. Let’s not forget the massive 5-15% increase in ad prices. Did we mention how other slides were used to prove another point?

Google search ad CPCs ended up doubling between 2013 and 2020.

The harm caused by advertisers was never taken into account and Google continued to raise its prices whenever it felt like it. This is a practice that Google has called a tweaking of its document list while the Department of Justice has mentioned that it is a type of manipulation.

Image: DIW-Aigen

Aside from that, RGSP, format pricing, and even overwriting were technical terms used by the DOJ on this front. We briefly discuss each of them for better understanding of our readers.

Format pricing is where advertisers pay no more than a certain maximum bid according to the search engine giant. But Google quietly launched another term called Project Momiji, designed to artificially inflate finalists’ bids.

This means a 15% increase in winning advertisers and better revenue chances for Google.

Another point worth mentioning is overwriting. This is where Google improved advertiser lifetime value based on predicted CTR from the higher numbers. So what the company was actually doing silently was raising prices in the face of the highest bidders.

The aim was to result in a wider range of price variations and an overall increase in the market. This led Google ad auction winners to pay more instead of benefiting from the crush. And this led to a most negative user experience, as the company ranked ads sub-optimally in exchange for higher revenue.

Finally, Google has benefited from activities like the RGSP. This is another term reserved for the second random generalized price that appeared in 2019. And that’s when we saw Google call it the ability to allow price increases in small phases over time. time.

This didn’t lead to an improvement in quality, but Google promoted it as if it was the best pricing button over format pricing strategies. Ultimately, the DOJ concluded that Google’s lack of transparency and reporting further harms advertisers because search marketers fail to highlight poorly suited questions via negative keywords.

This is a massive debate that Google has been denying for years. However, the antitrust case has brought some hope to advertisers who are forced to remain silent or pay the price of their voice against the monopoly.

Read next: Microsoft begins training its new AI model intended to compete with Google and OpenAI