Line Delivery Optimization

Line delivery optimization is the process of identifying campaign-level and line-level configurations that throttle line delivery and making adjustments to those configurations to optimize line delivery.

Manual Line Delivery Optimization

Manual line delivery optimization is the process of identifying campaign-level and line-level configurations that throttle line delivery and making adjustments that boost the delivery of ad impressions.

This is a manual process that requires a careful observation of each change and a weighing the benefits of increased line delivery against the potential hazards of decreased line performance.

It can be difficult to know what exactly is affecting line delivery. A line may fail to deliver the expected number of ad impressions for a variety of reasons, including:

  • Campaign-level budget caps may constrain line budgets and prevent the line from reaching its target audience.
  • The line may be sub-optimally configured.
  • The target audience is too narrowly defined and too few consumers are available.
  • The maximum bid price is set too low and insufficient inventory is available at that price.
  • The line’s frequency cap may restrict the available target audience.

Note

As a best practice, line delivery optimizations should be implemented one at a time and given sufficient time to make a difference. Make one optimization at a time and check to see if delivery increases before making further adjustments.

We recommend the following optimization strategies for increasing line delivery. Make these adjustments one at a time in the following order.

Step 1: Check Campaign Budgets

As a first step, confirm that campaign-level budget caps and flight schedules do not constrain line delivery.

In DSP, a line inherits budgets and schedules from its parent campaign. These campaign-level settings may constrain budgets and flight dates specified at the line level and adversely affect line delivery.

  • Budget caps. Campaign-level total budgets and daily budgets constrain line-level configurations. A line may fail to deliver as expected because a budget cap specified at the campaign-level overrides a line-level setting.
  • Flight dates. Campaign schedules constrain line schedules. A line may fail to deliver as expected because the beginning or end of its flight may fall outside the date range allowed by the campaign.

Step 2: Optimize Line Daily Budgets

Once you verify that campaign-level settings are not constraining the line’s budget and delivery, you may adjust the line’s daily budget and see if that improves line delivery.

A line’s daily budget specifies the total ad spend available to that line in a 24-hour period. Daily budgets can be defined by two means: as a user-defined value (a specified amount) or auto-allocated based on the line’s total budget.

  1. Ensure that the daily budget is defined as a user-defined value rather than as an auto-allocated value. This provides you with greater control over the allocation of a line’s daily budget than you would if the daily budget is defined as a specified amount. To learn more about line-level daily budget configurations, see Budgets.
  2. Increase the line’s daily budget by 10%.
  3. Assess whether the line’s increased budget improves line delivery.

Again, make incremental changes and give each change time to take effect before making another optimization.

Step 3: Expand Line Targeting

Line reach impacts line delivery. A line may fail to deliver the expected volume of ad impressions if the target audience too small and there are too few opportunities to serve ad impressions.

A line’s targeting strategy identifies the target audience for the line—that is, the consumers that may be served ad impressions. Advertisers can target audiences by exchanges or deals, locations, demographics, ad positions, frequency, audiences, devices, days of the week, apps, sites, page relevancy, mobile carriers, language, and other features. To learn more about targeting, see <no title>.

To ensure that the line’s reach is sufficient to meet your delivery goals, use the Forecaster to review your targeting strategy and see if you can identify opportunities to expand the line’s target audience.

  • If a targeting parameter is specified too narrowly, the line’s target audience may be too small.
  • If multiple targeting parameters are specified, the line’s target audience may be too small.

The Forecaster enables you to visualize how changes in your targeting strategy affect line reach and line delivery. Using the Forecaster, you can make incremental adjustments to your targeting strategy and see a forecast of how those changes will affect line reach and line delivery. To learn more about forecasting, see Forecasting.

Step 4: Adjust the Maximum Bid Price

A line may fail to deliver ad impressions because the maximum bid price is set too low and insufficient inventory is available at that price.

The more an advertiser is willing to bid, the greater the available inventory. Increasing the line’s maximum bid price may open up more inventory for you to bid on and enable you to increase the ad impressions delivered in the flight.

The best strategy for optimizing is to increase the line’s maximum bid price in small increments (at most a dollar at a time) to see those changes affect delivery.

Again, the Forecaster is a valuable tool that will enable you to visualize targeting optimizations may affect line delivery. To learn more about forecasting, see Forecasting.

Step 5: Adjust Line Frequency Caps

Finally, you can attempt to increase line delivery by increasing the line’s frequency cap.

A frequency cap is a line-level configuration that specifies the number of times that a consumer can be served ad impressions during a specified time period.

Frequency cap adjustments should be attempted only as a last resort because it can adversely affect line performance.

To learn more about frequency capping, see Frequency Capping.

Programmatic Pacing Optimization

DSP uses programmatic pacing optimization to regulate line delivery and to improve line performance.

Line pacing optimization enables the DSP to automatically adjust the line’s spend rate to meet the advertiser’s line delivery expectations. If a line under-paces (under-delivers ad impressions) or over-paces (over-delivers ad impressions), DSP attempts to regulate line pacing and bring the line back “on pace” by recalculating the line’s expected spend rate.

The DSP dynamically recalculates a line’s spend rate every five minutes to bring the line back on pace with the expected pacing. The adjusted spend rate is based on the line’s remaining budget and the time remaining in the day:

Adjusted Spend Rate = Remaining Daily Budget/Remaining Hours in Day

The DSP automatically recalculates the spend rate to compensate for changes to the line’s daily budget.

For example, imagine a line with a daily budget of $1000. At the beginning of the day the spend rate is the quotient of the daily budget divided by the hours in the day:

$41.67 = $1000/24

Now, imagine that it is halfway through the day and the advertiser adds $200 to line’s daily budget, which now stands at $1200. The increased budget means that the line is now under-pacing expectations by $100. If the total budget was $1200 at the beginning of the day, the line would have spent $600 in 12 hours rather than $500.

The DSP automatically recalculates the line’s spend rate to bring line pacing in line with the expected spend rate. There are now 12 hours remaining in the day and the line has spent less than half ($500) of its daily budget ($1200).

$58.34 = $700/12

Assuming that the line is using even pacing (the default), remaining budget is distributed evenly across the remaining hours of the day.