“By collecting over one billion data points each day from all countries in the world, the audience demand that is represented in our global measurement standard (called Demand Expressions) reflects the desire, engagement, and consumption of TV content, weighted by importance,” explains Samuel Stadler, VP marketing, Parrot Analytics. “For example, actual content consumption such as a BitTorrent video stream is scored as a much more important expression of demand, than a simple ‘like’ on a social network.

So what does this all mean?

The dictionary definition of ‘demand’ is: ‘the desire of consumers, clients, employers, etc. for a particular commodity, service, or other item.’ In the most basic sense, demand for television content is what drives transactions and consumption on all platforms, such as linear TV, TVOD or SVOD services. Consumers express their demand for television shows in a variety of ways, including video streaming, social media, photo sharing, blogging and micro-blogging, fan and critic rating platforms, peer-to-peer protocols and file sharing sites.

“These activities are what we track and measure, on a weighted average basis, globally,” says Stadler. “We capture the empirical expressions of demand from all of these sources and combine them into one distinct, global standardized measure of demand. This allows us to compare the popularity of TV shows in all countries, for any platform or device.”

In one recent study, for example, it analysed the popularity of subgenre anime (animation, Japanese style) ranking the demand for such content globally by country (the US tops the list by some margin outside of Japan) and by title.

What is the danger to brands and to media publishers if a universally recognized audience measurement covering multiscreen and time-shift is not reached?

"The issue is the opportunity cost – the value that is left unclaimed or wasted along the entire value chain,” says Stadler.

According to Parrot’s CEO Wared Seger determining what is popular has become a combination of art and science.

“Today, demand measurement is rapidly becoming the global standard for understanding content popularity across platforms, but we would say that it took world-class early adopters that operated at the intersection of media, science and technology to bring it to life. Now more than any time in our history, despite the fractured state of the television industry, we can know more about audiences’ true demand for content around the world; looking through opaque walls and challenging outdated systems – measuring empirical demand for all types of premium content, in all languages, across all platforms, in all markets around the world.

Beyond assessing demand for specific content titles, Parrot can now look at the popularity of certain genres, sub-genres, themes, cast members, show-runners and even more accurately predict what kinds of content will resonate with viewers in certain territories around the world and what non-content brands they’ll have high affinity with (driving sponsorships and partnerships).

“There are virtually endless possibilities and opportunities to slice and examine a global dataset unprecedented in its breadth, depth and categorization to answer any business question or challenge at hand,” says Seger. “Overlay a Content Genome layer on top of the global data and you now also have the ability to find ‘white spaces’ where there will be future demand for premium content not currently available.”

This is a ‘tip of the iceberg' moment in the world of global content demand measurement, where we’re only just beginning to realize the full potential of this kind of technology.

Parrot is not the only analytics firm using the word Genome to describe its research.

At IBC, AI startup Corto said it is building a knowledge engine to help media and entertainment companies develop deep, “genomics”-type insights into how their content resonates with audiences.

“We will be able to extract every possible genomic type of information about a viewer and what they are watching,” explained CEO Yves Bergquist. “We can map how every single emotion is represented in a film and map the emotional journey of each character in every scene. We can output a numerical value to correlate against box office returns and TV ratings.”

He's attempting to out-Netflix Netflix by automatically extracting and then mapping every aspect of a piece of content including values such as white balance and frame composition to the emotional reaction a viewer has on watching it. It is doing the latter by using MRI scans to literally hack the brain.

“We will use MRI scans to measure brain activity to infer what emotional response a character or narrative has,” said Bergquist. “That really is the ultimate - there is no greater level of granularity beyond this.”

You can’t argue with that.