Adam Liu

Data Scientist, Conviva

Mater of computer science at the University of Queensland. 10 years data analytics/data scientist and 3 years product management working experience. Hands-on big data and AI skills. Experience in data-driven solutions in various industries like digital marketing, streaming tv and real-estate, etc.

Past sessions

Summit 2021 Play Head Time Analysis On OTT Video At Scale

May 26, 2021 04:25 PM PT

Play Head Time(PHT) is the pointer representing exact point in a video's play-span that is currently being watched by the user.  We are all familiar with Play head pointer being displayed as a slider bar on the video screen.  Play head time can apply to regular media content, as well to Ads.  It is usually displayed on the slider bar of a running video.  However, when measured and analyzed at large scale, with accuracy, in near-real-time, across players and publisher environments - it enables us to solve some very interesting and practical business problems.  

For example: 

  1. Product placement analysis and measurement.
  2. Content viewer engagement analysis.
  3. Ad Content mutual impact analysis.

At Conviva, with its sensor software present on billions of devices on the planet, across hundreds of publishers/players - we are able to analyze video PHT at scale to solve the above use-cases, and more.  There are many challenges to collecting and analyzing Play head time.      

  1. Very large data volume.
  2. Need for high precision, at least seconds level data accuracy.   
  3. Complex and diverse environment.  We need to analyze different user behaviors when watching videos, including pause, buffering, seek, rewind etc.  We need to understand different player behaviors across different publisher environments across different video (Live, SVOD, ...). 
  4.  Final challenge is data sanitization.   

In this talk we will present how in Conviva we collect PHT data from billions of devices across players and publishers. How in Conviva we use Databricks technology stack to analyze, sanitize, store and process Play Head Time from billions of devices in real-time. How in Conviva we use large volume of processed Play Head Time data to solve real-world business problems.

In this session watch:
Adam Liu, Data Scientist, Conviva
Biplab Chattopadhyay, Architect , Conviva

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