Ad Delivery and the Pacing Algorithm
The Importance of Pacing?
Pacing is the control logic that determines how an advertiser's budget should be spent relative to time (your duration). An analogy is to an athlete running in a race: sprint too early and risk fading away before the finish line, but sprint too late and never make up the distance. Pacing ensures uniform competition throughout the day across all advertisers and automatically allocates budgets to different ads. Pacing is a core part of the optimization which ensures that return on investment (ROI) is maximized for the advertisers and for any given budget. Pacing ensures predictable delivery. This consistent delivery allows for stable prices throughout the day and helps all advertisers get fair access to their target audience.
How Facebook's pacing algorithm works
To explain how pacing works, I’ll go through 3 different cases of bidding strategy below to understand why pacing provides the maximum value for this advertiser. Note that the example talks about click, but the same idea applies for view, conversion, action, reach, etc.
Case 1: No pacing
Without pacing, the advertiser is getting all clicks up front (potentially the costly clicks) exhausting all the budget in the early part of the day. The effect is illustrated in the below figure where the blue dots are ad opportunities and the yellow circles are the opportunities won.
Case 2: Bidding too low
When pacing is bidding low on the cheapest clicks, the advertiser gets very few clicks as shown and budget is not exhausted.
Case 3: Balanced Pacing
When pacing is done optimally, as shown in the image, the advertiser is getting the most number of clicks while exhausting the set daily budget. As you can see from the above scenarios, when we use a constant bid over the entire period, the value for the advertiser is maximized as compared to no pacing or bidding too low or too high. To achieve this goal pacing comes up with an optimal bid by learning from other ads competing for the same target audience. Determining this optimal bid value is the core learning part of the pacing algorithm, which includes feedback systems to keep pacing on track. These values are constantly being improved for accuracy and are influenced by many different factors such as the type of ad, the targeted audience, and time of the day.
