Ad Pods (Podding) – Introduction, Measurement, and Personalization

In this deep dive on adtech, let’s take a look at ad pods or podding, and learn how they work, how to measure the performance or ad pods, and how to personalize ad pod technology.

What are Ad Pods?

“Ad Pods” or “Podding” is a term used to refer to multiple ads that are placed together and then played back one after the other (back to back playback) in a single ad break.

But, why the name ad pods? Well, try to think of a bunch of peas in a pod. Like the image below.

In a pea pod, all the peas are placed next to each other – one after the other. You have an outer structure “the pod” which contains a series of “peas”.

Now take this picture and imagine that the pea pod is an “Ad Pod” and the individual peas are “Ads”. So, you have a wrapper of sorts (the Ad Pod) which contains a series of advertisements in it.

Here’s a more formal, engineering depiction of Ad Pods and Videos. The figure shows a couple of ad pods that are inserted into the videos either via SSAI or CSAI. When an ad break is reached, the video playback stops, and the ad pod takes over. The first ad in the pod is played back, followed by the second ad, and so on. All the ads in the pod are played back and the control returns to the video.

It’s also quite common to have “Skip Ad” options in Ad Pods. So, its possible that a user watches the first ad and skips the rest of the ads in the pod.

There are a few important things to know about Ad Pods –

• Individual ads in an ad pod have “sequence numbers” and these numbers determine the order in which the player should playback the ads.
• If an ad cannot be played, then the player moves on to the next ad based on the sequence number.
• The player must attempt to play all the ads in the pod, unless, the ads cannot be played back or they do not fit into the ad slot. For example, if three 30-second ads are returned for a 60-second ad slot.
• If an ad cannot be played, the player can playback the next ad in the sequence or playback a stand-alone/non-sequenced ad (these are ads that are considered part of an “ad buffet” from which the player may select one or more ad to play in any order, see IAB’s VAST Spec.).

Personalizing Ad Pods

Ad Pods offer a great deal of flexibility to publishers such as the ability to

• Decide the maximum length of each Ad Pod
• Choose how many ads are in each Ad Pod
• Decide the length of each ad inside an Ad Pod

One could use advertising analytics to track all of this information, correlate it with content viewing statistics, and make marketing decisions based on solid data.

For example, if you insert four ads in each pod, and distribute 10 pods in your long-form content, what is the ad completion and ad skip rates that you’re experiencing? Are your users experiencing ad-fatigue and are they skipping the 3rd and 4th ad pods? And, are they skipping most of the latter ad pods?

This is information that you can extract very easily using an ad analytics service and tune your ad campaigns accordingly. For example, you can take decisions such as –

• Does my audience prefer two or three ads in each pod?
• If we insert two ads in each pod, how many ad pods should we use in the movie?
• Which is working better? 10-second ads in each pod, 15-second ads, or one single 30-second ad in each ad pod?
• How is each ad in each pod performing concerning its position?

To make such fine-grained decisions, a publisher should have access to information and data about the ad playback. In the next section, let’s take a look at what data can be collected by the platforms to guide solid marketing decisions.

Gathering Information about Ad Pods

Most ad service providers have the means to extract fine-grained information about ad playback. Let’s take Google IMA as an example and dive into their docs.

Google’s definition also sums up ad pods perfectly – “An ad may be part of a pod of ads”. Here is all the information that the Google IMA’s Web SDK exposes for CSAI and DAI. Using this SDK, you can extract –

• The position of an ad within an ad pod.
• The maximum duration of an ad pod.
• The Index of an ad pod – is it the first ad pod, or the second, etc.
• The total number of ads inside an ad pod.
• Bumper ad information – are there bumper ads in the pod?
• The time at which the ad pod was scheduled to begin.

An ad may be part of a pod of ads. This object exposes metadata related to that pod, such as the number of ads in the pod and the ad position within the pod.

Public Method Summary

abstract int getAdPosition()
Returns the position of the ad within the pod.

abstract double getMaxDuration()
Returns the maximum duration of the pod in seconds.

abstract int getPodIndex()
Client side and DAI VOD: Returns the index of the ad pod.

abstract double getTimeOffset()
Returns the content time offset at which the current ad pod was scheduled.

abstract int getTotalAds()
Returns the total number of ads contained within this pod, including bumpers.

abstract boolean isBumper()
Returns true if the ad is a bumper ad.

This is all very useful and critical information that should be extracted and analyzed for maximizing the ROI on ad campaigns. With this information, you can easily analyse which genres of ads work well with your core audience, what is their level of tolerance for Ad Pods, how many ads should ideally be in each pod, frequency of ad pods, etc.

Conclusion

I hope this article on Ad Pods / Podding was useful and helped you learn more about this particular technology in the advertising industry. If you are interested in ad insertion, do check out our articles on CSAI vs. SSAI, VPAID, VAST, Pre-Mid-Post Roll ads, and more.

Until next time, take care and happy streaming.