New York City and San Francisco are home to some of the most valuable real estate and highest costs of living in the country. This may be common knowledge, but do you know the most expensive city on Facebook®? That’s right, different cities are more expensive than others on Facebook – in terms of advertising costs, anyway.

Facebook uses an auction system where advertisers “bid” on how much they are willing to pay for a user to click on their ad – the more advertisers that compete for clicks in a given target audience, the more expensive that click will be.

Facebook provides a “suggested bid” based on the competitive landscape of the audience you choose. To give you some context, at the time of this experiment, the suggested CPC bid for targeting the entire United States was $0.92/click.

Since price is driven by competition for the audience, there isn’t necessarily a direct correlation to population or cost of living, so some of the most costly cities on Facebook may surprise you. I took the top 100 most populous cities in the United States to see which ones cost the most when it comes to Facebook targeting.

Without further ado, here are the top 10 most expensive cities on Facebook:

#10 (Tie)  Garland, TX & Jersey City, NJ – $0.97 CPC

garland jersey
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est.
Garland $0.97 156,000 234,556
Jersey City $0.97 240,000 257,342

 

#8 (Tie) – New York, NY & Irvine, CA – $0.98 CPC

nyirvine
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est.
New York $0.98 5,400,000 8,405,837
Irvine $0.98 260,000 236,716

 

#6 (3-Way Tie )– Seattle, WA, Durham, NC, and Fremont, CA – $0.99 CPC

seattledurhamfremont
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est.
Seattle $0.99 1,000,000 652,405
Durham $0.99 220,000 245,475
Fremont $0.99 178,000 224,922

#3 – Oakland, CA – $1.00 CPC

oakland
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est
Oakland $1.00 380,000 406,253

#2 – Washington, DC – $1.01 CPC

dc
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est
Washington DC $1.01 1,200,000 646,449

 

#1 – San Francisco, CA – $1.02 CPC

sf
City FB Suggested Bid (CPC) FB Population 2013 Pop. Est
San Francisco $1.02 1,140,000 837,442

 

Honorable Mentions:

City FB Suggested Bid (CPC) FB Population 2013 Pop. Est.
Palo Alto $1.05 102,000 66,642
Los Altos Hills $1.18 10,000 7,922

Palo Alto is where Facebook grew up, and where I’m from! Los Altos Hills is a neighboring town where stars like Barry Bonds and tech moguls like Yuri Milner reside – The median home value is $5.4 Million. Neither city makes this list, as the actual populations are much smaller than the top 100 cities in the US, but the high CPCs in both cities deem these to be competitive Facebook advertising markets

Methodology:

In order to generate a suggested bid for each one of these cities, I first opened up Facebook’s Ads Manager in one of our test accounts. I selected my goal of “Clicks to Website” and proceeded to the targeting section. I left most of the settings default, but changed a few certain attributes.

First, since we’re talking about real estate, I selected only the “Newsfeed” placement on Facebook. The desktop and mobile Newsfeed on Facebook is the prime “real estate” in terms of ad placement, as the Newsfeed typically gets higher click through and conversion rates (and usually at a higher cost, vs. the right hand column placement).

Second, I narrowed geography targeting down to the city level. The default on Facebook is “City + 25mi,” but I only wanted to see the bid when targeting the city itself, so I removed the +25mi radius.

Finally, I captured the “suggested bid” for each of the 100 most populated cities (according to a 2013 population est. in Wikipedia). When optimizing for clicks and setting the max price you will pay per click, Facebook inserts a default “suggested bid.”

According to Facebook’s Ads Manager:

The suggested bid amount is based on how many people are competing to show an ad to your target audience.”

It is important to note that the suggested bid is always subject to change, as the competition in each target fluctuates by day, time, and even per advertiser! This data was initially analyzed in February 2015.

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