Tag Archive for algorithms

Floors In RTB: Are hard and soft reserve prices known to the DSP?

I assumed that before bidding, DSPs could not be sure whether an SSP applies floor price rules to an auction. Now, I saw some remarks in the academic literature implying that buyers know about the existence or even the exact quantity of floor prices.

In practice, do SSPs communicate their floors?

This question was asked on quora, below is my answer.

Floor Prices in an AuctionThe answer is: sometimes. Exchanges sometimes express floor or bid guidance in the bid request. This is not required for the market to operate; so many exchanges do not provide any guidance. Floors are almost always in play. In most cases they are dependent on a wide variety of variables including: the site, browser, device, day of week, time of day, audience data, user’s language, and geographic location of the user.

Auction Mechanics

Floor prices, from an academic standpoint, are there to protect the base value the publisher has placed on the inventory. Bids falling below the floor, or reserve, are usually rejected by the exchange. Losing bid information might be recorded to give the publisher insight on the value advertisers are placing on the inventory and accompanying traffic. Read more

Audience Forecasting and Campaign Pacing

Audience Forecasting and Campaign Pacing“In online advertising, how can I predict/forecast the traffic (number of requests) for a day ?
For a given day, I would like to get the estimated number of eligible impressions a campaign will have, in order to allocate my budget and implement a traffic based pacing algorithm.”
This question was asked on Quora, below is my answer.

The estimated number of eligible impressions, or audience forecasting or “avails” as they say in the industry, can be derived in several ways. I will illustrate two of the methods.

The long, but easy method

The easiest way to estimate your avails would be to just take a whole day’s worth of data and determine how many of your target users are in there. The problem with this method is that it can take a whole day. If you have a day to spare, this is a good way to go.

The short, but difficult method

For this to work you’ll need the total traffic available for some previous day, or week. You’ll want that data broken down by hour or maybe 15 minute interval. With more traffic, your breakdown can be smaller. For the sake of this example let’s look at an hourly breakdown and a single day’s worth of data. Read more

Disrupting the Bid in the RTB Auction

RTB Bid Keys

Your eyeballs are on the block, but they don’t always go to the highest bidder.

“In RTB, will the bid with the highest CPM always win? If not, what are the other factors?”

This question was asked on quora, below is my answer.

In a pure auction, the highest bid should always win. In many cases an RTB auction ends with this result, but not always. There are two or three things that will adjust the auction mechanics to give a lower bidder the impression. Most of the time a modified auction is at the behest of the publisher. Read more

Using Proportional Control for Better Campaign Pacing

My post was originally published on the Rubicon Project blog. It was written with contributions from Dr. Neal Richter and Jonathan Zhuang.

Pacing algorithms come in a few basic forms at the Rubicon Project. The most basic is one called “as fast as possible” which can hardly be shown to do anything that resembles pacing. The Pacing controller is supposed to spread out impressions served for a campaign throughout the day. In general it takes the goal of impressions to serve in a given day as input and calculates a serving schedule for the campaign.

Estimated Curve of Available Impressions

A naive pacing algorithm will break the day up into 24 segments, let’s call them hours. It will allocate equal amounts of campaign impression for each hour and then recommend the campaign get impressions until the hour’s allocation is exhausted. This algorithm has a couple of pretty big flaws. Primarily it tends to serve the campaigns at the beginning of each hour and then once the allocated impressions are used up it stops serving until the next hour. The second flaw is that it has no understanding of the traffic distribution throughout the day. The 1AM hour doesn’t have the same amount of traffic coming in as the 10AM hour. If the inventory is relatively scarce the campaign will under-serve during the early hours, catch up during the peak hours, and then under-serve again in the later hours. Ultimately campaigns using this algorithm may not achieve their goals at the end of the day and it won’t serve evenly in a given hour. Read more