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Programmatic Video Advertising

Everything about Programmatic Video Advertising

     

What is Programmatic Video Advertising?

Programmatic Video Advertising is a term that refers to the use of software or bots to purchase digital video advertising space online. Essentially, the practice uses an algorithm operating in real-time to replace a variety of menial activities and improve on targeting and cost-efficiency. Programmatic video advertising as an emerging industry essentially has two ends. On one end, sellers hoping to gain more value out of their content make advertising space available to sell-side platforms (SSPs), while on the other end, advertisers apply software to bid on and purchase video ad space based on set criteria given to the bots.

How can Programmatic Video Advertising be used?

Programmatic video advertising can be used in a number of ways to benefit various industries. It can be used to expand the reach of ads by more effectively targeting groups and demographics that are likely to be interested in the product or service. Many companies have also switched to programmatic as a response to a lack of resources or a dip in profitability. Programmatic advertising as a whole has been shown to dramatically increase the effectiveness and efficiency of advertising campaigns, as well as to make better use of dedicated budgets.

Programmatic video advertising can be used across various digital platforms, including online, in-app, on TV, and in digital out-of-home (DOOH) displays. Online, there are three main programmatic video advertising formats:

  • In-stream: These video ads appear at the beginning, in the middle, or at the end of online videos.
  • Out-stream: These video ads appear in the middle of online articles (often as pop-ups).
  • In-display: These ads appear as separate videos, displayed alongside the content that the user is consuming. They require the user to make an active decision to click on the ad.

In-app programmatic video advertising is growing in popularity, as more people are using mobile apps to watch videos. Mobile apps also provide more accurate audience targeting, as they often collect more detailed user data that can be used to target and personalize ads.

What are the benefits of Programmatic Video Advertising?

Aside from the cost effectiveness that comes about due to the reduction in menial labor required, a better use of dedicated resources, and increased ROIs, programmatic video advertising offers a number of additional benefits. First, the software enables marketing teams to collect valuable and comprehensible data on the audience that is viewing their content. Ad-buying algorithms are increasingly being developed to learn and adapt based on this data. This learning curve provides a road-map for marketers to understand who is really interested in their product and whether or not they have misidentified their key demographics. As a whole, programmatic video advertising allows marketers to take a step back from the details and focus on the big picture when it comes to strategy.

Why is it important?

There are two sides to consider when it comes to the current importance of programmatic video advertising. On one side, there is the general misunderstanding of the term and the software behind it, even among marketers. One recent survey by the Association of National Advertisers and Forrester indicated that only 23% of marketing teams understood the term and used the technology. On the other side, there are the massive resources being invested in it by those who do understand it. eMarketer forecasts that in the US, spending on programmatic advertising will reach a staggering $59.45 billion in 2019, and that video advertising will play an important role in fueling this growth.

How Programmatic Video Advertising works

Programmatic video advertising requires a number of key players and software to deliver its impressive results. One aspect involves algorithms and AI that use data, such as that obtained from cookies, to paint a clear picture of the kinds of visitors and viewers that advertisers should be targeting. This can either be done in-house or outsourced to a data management platform. Another aspect involves advertisers connecting their ad-buying software with an SSP. Publishers use the SSPs to advertise their content and sell ad space based on attention data that the SSP itself has acquired.

Data-driven programmatic video advertising

The foundation of programmatic video advertising is personalization. Understanding the customer, by drawing behavioral insights from data, is the key to an efficient programmatic advertising strategy. There are three tiers of data to be considered for programmatic video advertising: first-party data, second-party data, and third-party data.

First-party data is the advertiser’s own data on the customer, based on primary research. Second-party data is customer insights collected by a constituent of the company, such as an agency. Third-party data is data that is available to the public at a cost and is usually sold on a rate card basis.

Data-driven programmatic video advertising enhances targeting. In digital out-of-home (DOOH), for example, there are a variety of triggers that can be used: time of day, weather, stock trends, outcomes of sports events, face detection, etc. This means that a far greater proportion of meaningful impressions, relative to the total number of impressions, can be achieved through the precise data triggering capabilities of programmatic video advertising. The goal behind programmatic video advertising is to deliver the right ad to the right audience in a more appealing way, all in an effort to spur conversions and sales. Audiences are a lot less likely to ignore ads if they are tailored directly to them.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.