Blog Hashbrown

Netflix’s Becoming of a Rubric for The Big Flicks

The company became data-driven before it was in vogue


Aastha Khanna

In January 2007, JP Morgan Securities downgraded the Netflix stock citing high competition and most wondered how Netflix might create a ‘second act’ beyond DVD Distribution. Not many might know this but Netflix started in 1997 as a DVD-by-Mail business with a monthly subscription fees so that consumers could avoid late fees. During the first decade, it had built impressive logistics chain with over 50 regional warehouses to distribute the DVDs to its customers. By February 2007, it had distributed its billionth DVD. 

That success and kind of growth should have trapped the company to define its business model with core competency in logistics and distribution. But Netflix is different in the sense that it had recognized the power of data and analytics. 

So, it developed a superior recommendation engine, Cinematch, to better predict the pattern of request of DVD titles by subscribers. It even organized an open contest—Netflix Prize—and offered a $1 million prize to anyone who could improve on its algorithms.  

Logistics and analytics to disrupt physical stores 

By 2009, it had over 100,000 DVD titles and 10 million customers. It could have continued on its trajectory. But, it didn’t. Netflix innovation focused on two dimensions: logistics and analytics. 

Blockbuster and other video-rental physical stores didn’t recognize possible disruption from a mail-order subscription company like Netflix. Blockbuster even turned down an opportunity to acquire Netflix in 2000. 

So, Netflix 1.0 was about the disruption of physical stores. 


Netflix 2.0—Video streaming 

By the end of 2016, it had nearly 94 million members globally— expected to reach the 100 million mark during the first half of 2017. Netflix video streaming consumes 37% of downstream internet bandwidth during primetime hours in the USA—far ahead of YouTube, Amazon and Facebook. 

Netflix has become the de facto primetime entertainment on the web. It can be streamed on computers, mobile phones, tablets, smart televisions and video game consoles. 

Cloud plus data and analytics 

The digital business transformation of Netflix can be seen through two lenses: technology and data & analytics. 

Through the technology lens, you see how Netflix worked with Amazon to develop a world-class back-end infrastructure. 

Working with Amazon Web Services, Netflix could quickly deploy thousands of servers and terabytes of storage within a short span of time. 

Through the information lens, you can see how Netflix has collected the most detailed data possible to be the best at knowing their customers on an individual basis, to really understand customer preferences and to continually sharpen the recommendation engine. 

Personalization at its core 

Today, everything that Netflix provides to each customer is a recommendation. The core DNA of Netflix is Personalization—which builds on its data-rich recommendation engine. 

Personalization in the homepage consists of groups of videos arranged in horizontal rows. Each row has a title that conveys the meaningful connection between the videos in that group. Personalization is how Netflix selects the rows, the items for each row and the order. And that varies for every individual. And that is done by machines and at scale and speed. 

Not only this, Netflix has been able to add more useful data to make its recommendation even more powerful, based on its strategic relationship with Facebook. 

Specifically, it has been able to add preferences of friends on the social network to refine the recommendations.


So, where is Netflix headed? It has so far capitalized on technology developments and grabbed on the information-driven advantage to continually refine its business model. 

Now, internet TV is replacing linear TV. This means that apps are replacing channels and Netflix is one such leading app. 

Television is no longer the only screen. Netflix is now available on any screen and is optimized for any size. 

The innovation—disruption—transformation journey for Netflix 2.0 shows mastery of different competencies than what we saw with DVD-by-Mail business model. 

Hashbrown Systems, with its intelligent, customised solutions and data centric approach, has demonstrated direct savings, waste reduction and a direct increase in sales for SMEs and established brands. 

Learn about our software, solutions and services, so that we could be of service to your organization.

More Hashbrown Stories

Hashbrown Systems Case Studies

Bubna Advertising

Our first case study briefly analyses the first outdoor monitoring and compliance system for the largest outdoor agency in India by volume.

Case study


Our OOH Audit & Monitoring System uses Machine Learning techniques and a uniquely crafted allocation model to optimize fund allocation for 88 billboard locations, a breakthrough in the Out-of-Home Advertising & Marketing industry.

Case study

Spotlight - Brand Sales & Distribution

An overview of digital transformation that employed cloud computing, data analytics, machine learning and location intelligence to create a constantly connected and data driven enterprise.

Case study

Building Digital Infrastructure for the Physical World

A triumphant tale of putting IOT to work for Out-of-home media owners and advertisers.

Case study