TripleLift Invents New Ad Units for Real-Time Product Placement in Streaming TV Using ML on AWS
Overview
As consumers move toward streaming TV, marketers need new ways to reach viewers with compelling advertising in video. Consumers also want shorter ads with fewer interruptions, creating a challenge for publishers and advertisers to produce more effective, engaging ad units. Programmatic advertising technology company TripleLift pioneered a solution for dynamically inserting product placement ads into streaming TV shows by using a combination of custom-built models and machine learning (ML) on Amazon Web Services (AWS). The solution first identifies locations and surface areas in premium video and TV content using an ML pipeline; it composites brands and nonintrusive ad units into select scenes; and then it inserts the new scenes into the real-time stream using server-side ad insertion, all without interrupting the viewing experience. Using this solution, TripleLift enables advertisers to improve ad effectiveness and recall and provides publishers with an automated way to monetize over-the-top (OTT) and connected TV.
Using AWS Elemental MediaTailor, TripleLift can serve these experiences dynamically and with frame-level accuracy to deliver different experiences to different users."
General Manager of Connected TV Business, TripleLift
Adjusting Advertising to Meet Evolving TV-Watching Habits
One of TripleLift’s premier partners is food and lifestyle brand Tastemade, which has now deployed TripleLift ad experiences in over 200 episodes of its programming. “TripleLift’s deep learning–based video analysis provides us with a scalable solution for finding thousands of moments for inserting integrated ad experiences in programming, supplementing a high-touch marketing function with artificial intelligence,” says Jeff Imberman, Tastemade’s head of sales and brand partnerships.
Pioneering an Advertising Solution on AWS in Less than 6 Months
Continuing to Refine Its ML Solution
About TripleLift
Benefits of AWS
- Built an infrastructure for video analysis at scale in 5–6 months
- Reduced video analysis time by about 50%
- Scales to manage high volumes of content
- Saves staff time
- Created a new solution to meet a changing advertising industry