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Facebook reported earnings for the first quarter of fiscal year 2020, which ended March 31, according to foreign media reports. Facebook reported first-quarter revenue of $17.74 billion, up 18 percent from $15.08 billion a year earlier, net income of $4.9 billion, up 101.6 percent from $2.43 billion a year earlier, and earnings per share of $1.71, up 101.2 percent from $0.85 a year earlier.

In terms of revenue, Facebook's first-quarter revenue from its advertising business was $17.440 billion, up 17 percent from $14.912 billion a year earlier, and Facebook's first-quarter payment and other service charges revenue was $297 million, up 80 percent from $165 million a year earlier.

From the form of diversity, functional integrity, targeting users, real-time, data analysis report all comprehensive indicators Facebook is the industry leader, the following is their internal analysis of the advertising system Pacing algorithm, but also suitable for advertising technology to get started to view.

Pacing is an algorithm in Facebook's advertising system that regulates the budget of spending, an analogy for competing athletes:Early sprinting means you're out of the end, but sprinting too late may not finish the race.Pacing guarantees that all advertisers automatically allocate different advertising budgets on a competitive basis.Pacing is the core component of optimization that gives advertisers the greatest return on investment (ROI).

How does Facebook's Pacing algorithm work?

We explain how Pacing works by an example. The following will involve clicks, the same ideas can be applied to browsing, conversion, behavior, arrival rate, etc.

An advertiser wants to advertise a brand. Budgeted at $10 per day, based on CPC billing, we assume that each ad click will generate $5 revenue (the average profit after the user buys)

When he/she creates an ad and does an optimization on the LINK_CLICKS (click link), the bid_amount (bid) is set to $5, billing_event (triggering charged events) for LINK_CLICKS, based on these for the true condition. The target group is male 25-35 years old.

Here are three examples to understand the maximum value that Pacing algorithms offer advertisers:

Case 1: When there is no Pacing algorithm.

Without Pacing, advertisers' budgets are spent cleanly (potentially expensive clicks) in the first place, and pre-intense, late-non-competitive, resulting in a certain waste of resources. The blue dot sin below represents the opportunity for the ad to get a display, the yellow circle represents the ad winning the display, and the red line represents the price of the bid. The result is that the average cost will be higher, but advertisers will get the most desired run based on your ad settings. This is called accelerated delivery.

Profit - Revenue - Cost.

So the income here is 6 x $5 x $30.

The cost, of course, is the 10 we used.

Total proceeds : $30 - $10 - $20.

Case 2: Bid too low.

In this case, the lowest click price is pursued, but the advertiser's budget is not used up in the end, and the resulting ad performance is the worst.

Earnings: $20 - $4 - $16.

Please note that here's 10 knives a day advertising costs we have not used up! Because our bid was so low, we didn't beat the other competitors - advertisers, our ads didn't air.

Case 3: Equilibrium state under pacing algorithm.

At this point, advertisers get the most hits, get the most revenue, and run out of daily budgets.

Earnings: $35 - $10 - $25.

Here we get the results of our final optimization very well.

The importance of Pacing.

Pacing maximizes advertisers' profits under a given budget. It makes advertisers more authentic, and Vickrey-Clarke-Groves (VCG prices the auction by calculating the sum of the losses that an advertiser takes to other advertisers), which has no benefit in spoofing the value and doesn't have to think about how much the maximum bid should be. This avoids special opportunities in the auction system.

Pacing guarantees a predictable delivery. This steady delivery stabilizes daily prices and helps advertisers get fair access to the threshold for their target users.

Related: http://outofmemory.cn/wiki/facebook-ads-pacing-algorithm.

Some of the content is taken from the network:
RELATED LINKS https://www.jianshu.com/p/bfed7fe8dae0.

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