Quality user experience is an essential part of any business wanting to operate within the services industry. Netflix is a perfect example of the opportunities that can be created by focusing a company’s efforts into obtaining the right information to perpetually refine their customer’s user experience. Throughout this article, we will be examining the methods with which Netflix utilises and how similar methods can be applied to professional services companies such as Accodex Partners to improve customer experience and contribute toward positive growth.

 

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Netflix the Road to World Domination

Netflix has become the most prevalent online streaming service in the last few years. Founded in 1997, it started as an online movie rental service. Today, Netflix is available in 190 countries with approximately 75 million customers (Granados, 2016).
As an online entertainment service, Netflix has invested much of their resources in ensuring that demand for their service is high. Like Accodex, Netflix’s approach revolves around customer experience and as such the company puts a lot of emphasis on data collection; analysing and extrapolating customer preferences to predict and cultivate future trends.

 

 

“What, an algorithm?”

So the question is, how does Netflix even begin to know the correct content to distribute? The short answer, a proprietary algorithm used to predict consumer behaviour and trends. Netflix’s algorithm is a recommendation algorithm, with suggestions based on what you watch, rather than just the ratings you give. These recommendations are also affected by variables such as the time of day you visit Netflix, and which device you use. In order to successfully assess and satisfy the demands of their customers, the algorithm incorporates all of these variables to create a network of connectors that categorises the results accordingly.
In spite of the vastness of Netflix’s clientele database, there has been a positive response to the algorithm, with approximately “75 percent of what people watch on Netflix (as a result of) the site’s recommendations” (Kleinman, 2013).

 

How does this all work?

Originally the ratings’ system was more important than the recommendation system. The system enables users to discover new movies and TV shows that they will enjoy by rating movie genres and specific movies when they are onboarding with the Ratings either increasing or decreasing in prominence of a show or movie.
Collaborative filtering is a dynamic and organic filtering system, which involves the input of clients, specifically their ratings, views, and genre categories, to be able to create a personalised dashboard. The overall filtering process is a series of equations, with Netflix utilising a Hybrid type of collaborative filtering. This means that it is simultaneously made up of both memory based and model based collaborative filtering. While memory-based filtering allows Netflix to calculate how similar users are, the model-based filtering allows Netflix to look for habits in user’s viewing preferences.

 

Netflix’s Individualised Dashboard User Interface

 

Netflix Tagging

Let’s start with the ‘tagging’ system. As explained previously, Netflix utilises a ‘Hybrid’ Collaborative Filtering algorithm that incorporates collected data to consistently refine its customer experience. This essentially means that each time you view content, each time you rate or add it to your personal playlist, Netflix is always collecting your viewing information.

 

Feedback Loop

As with any other online business, information is key; especially when it pertains to the habits of your customers purchasing power. In the case of Netflix, the knowledge obtained through the data permits the company to decide the plethora of content on the site. As most of Netflix’s content relies heavily on obtaining licences to popular shows, it is imperative that the company purchases licences to shows based on the titles which will deliver the highest number of viewers in relation to the licensing cost.
Furthermore, this feedback loop allows the user to enhance the tagging system by showing Netflix a variety of different things, for instance; Netflix knows how long a user sticks with a certain program before moving on. In essence, this feedback loop allows for quality, by involving the user in deciding the quality of their experience.

 

 

Netflix Original

Recently, customers will have noticed the influx of shows that are being produced and distributed exclusively by Netflix. Extrapolating from the success of Netflix’s algorithm and the data obtained from users’ viewing behaviours, Netflix has been quite vigorous in producing a lot of their own branded programs; for instance, Orange is the New Black, House of Cards and the Marvel T.V. Series (Daredevil, Jessica Jones). As we can see, the company’s ability to be able to produce exclusive and popular shows had largely been due to the assistance of their collected data.

 

Netflix Originals Exclusive and First-Party production content

 

So what does this mean for Netflix?

As previously explained, the main function of the algorithm is to not only help with recommendations but to enable Netflix to improve its marketing, finance, and competitive advantage. By collecting the right data, Netflix has been able to provide a dynamic user experience as well as expand the quality of its content by producing their own programs.

 

How is Netflix’s algorithm relevant to Accodex’s Partner Experience?

Netflix offers one core product, streaming entertainment. Accodex’s partner channel offers Quality Partner Experience by providing training, data, automation, the sharing of resources, and functional support.

In terms of my role as Business Development Executive, and improving Partner Experience, it is essential for me to understand the differences with each partner’s individual needs. Our Enterprise Resource Planning (ERP) system is like Netflix, with users – in this case, Partners – having a different user-experience dependent upon their specifications. Similarly to how the data collected by Netflix helps to determine what shows to license, data collected from the partners help to shape our Partner program. Our Partner program offers native training content (similar to Netflix Productions), as well as facilitating internal communication and functional support. This enables tracking and analysis (like Netflix’s feedback loop).

The tagging system we utilise enables me to categorise partners by their location, function, and client base – the more appropriate tags, the more accurate and quality data there is to be collected. It improves the user experience by simplifying the navigation time. For instance, if a partner has an issue, the tagging system allows us to easily identify which information pertains to the problem and efficiently identify and isolate the causes of bottlenecks that the partner is facing.

 

“We will have the ability to swiftly resolve the problem”

 

Tagging is also helpful in tracking company operations in real time, as we have the ability to see what projects partners are working on, as well as how many people they have in their team. In the instance in which a partner is having a problem, if a similar problem has occurred in the past under similar circumstances, we will have the ability to swiftly resolve the problem and ensure it does not happen again.

Our ERP has a Feedback loop which helps collect the necessary data to provide an insight into the company’s current operations and processes and how to critically improve upon them. From a growth perspective, our ERP is still in its early stages; of course, there WILL be mistakes in anticipating and predicting what our partners need especially when they are new and or from a relatively new background (one that we have yet to tap into). Feedback lets us prepare for said partners by preparing training wise, alongside providing functional support to partners and developing our Community channel.

 

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Within any services industry, user experience is vital. As we have illustrated, in focusing their efforts on improving user experience, Netflix has successfully opened themselves up to a plethora of opportunities that have expanded the company’s service offerings. The culmination of their efforts had afforded the company the ability to evolve beyond a simple streaming service to a First-Party production company.

 


 

Written By: Sammie Johannes, Director of Business Development

 


 

References

  1. Kleinman, A. (2013). How Netflix Gets Its Movie Suggestions So Right.Available: http://www.huffingtonpost.com.au/entry/netflix-movie-suggestions_n_3720218.html?section=australia. Last accessed 27th May 2015.
  2. Kleinman, A. (2013). How Netflix Gets Its Movie Suggestions So Right.Available: http://www.huffingtonpost.com.au/entry/netflix-movie-suggestions_n_3720218.html?section=australia. Last accessed 27th May 2015.

 

Images

  1. http://www.benzinga.com/analyst-ratings/analyst-color/16/01/6125161/netflixs-global-dominance-in-1-chart
  2. https://www.statista.com/chart/1620/top-10-traffic-hogs/
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