How does Netflix create Customer Loyalty?

Segmentation and Personalization: Netflix’s Secret Sauce for Creating Customer Loyalty

Over 80% of consumers in the US subscribe to at least one streaming service. However, a 2022 digital media trends study by Deloitte revealed that subscriber churn is on the rise. Deloitte notes that “Competition is stronger, the landscape is more dynamic, and consumers have more options to discover content and find value”. With customer churn increasing, brands are under pressure to deliver the best content and customer experience. How do they achieve this? Segmentation and personalization. 
 

The value of customer loyalty and retention

According to Gartner Group, 80% of a company’s future profits come from its existing customer base. This is why brands across every industry are investing in keeping their customers. Netflix’s customer churn rate is 2.4% (see graph below) - a much lower figure compared to its competitors. 

 

Netflix's subscriber churn rate: Image Source

 

Let’s take a look at what the streaming giant is doing to retain subscribers…

 

1 - Intelligent Segmentation

AI segmentation tools can identify clusters of people with similar content preferences. Netflix puts each subscriber into a “community” that drives what they see on a row. The “Popular on Netflix” row is akin to “Popular with segments that have similar preferences and viewing histories as you”.
 

Netflix also has a rating system showing the percentage match of a piece of content to your profile, or what others in your ‘segment community’ have rated highly. The platform recently introduced a “double thumbs up” button, which lets users ‘vote’ on what they want to see more of. The thumbs up and thumbs down buttons have helped Netflix learn more about each segment. However, ratings go beyond the simple dichotomy of “like” or “dislike”. The double thumbs-up tells Netflix when users are really enjoying content, helping them to create profiles better suited to each segment's exact tastes. 
 

Netflix thumbs up and thumbs down vote
Netflix Thumbs up and Thumbs down buttons

How can AI tools help drive customer loyalty?

Find out here

 

2 - The creation of seamless, personalized experiences
 

Netflix's personalisation mission

 

Streaming services like Netflix and Amazon Prime have expansive content catalogues. To ensure the right content is shown to the right audience, a recommendation algorithm suggests what each user should watch. This algorithm uses data such as viewing history and rating feedback. Personalized recommendations are precise - Netflix previously announced that a staggering 80% of content is watched via the recommendations algorithm. 

Looking for more personalization strategies?

Check out these examples

 

Netflix’s algorithm can even personalize the image preview shown to each viewer. Using data about what someone has clicked on previously, the platform displays a different image title to an audience based on what it thinks will catch their attention. We may be taught to not “judge a book by its cover” - but the reality is that viewers are more likely to select a title that catches their eye. The more a viewer interacts with titles, the more data gets fed into the algorithm to understand what grabs attention and what keeps someone scrolling.
 

Images can be personalised according to the genres viewers prefer. For example, if a user’s watch history is mostly romance movies, they will see thumbnails featuring a couple. If a user watches mostly horror movies, they will see thumbnails highlighting the scary scenes of a series…

Netflix personalized thumbnail options
Netflix series Stranger Things thumbnail preview options

 

Netflix personalized thumbnail options
Riverdale personalized thumbnail options

 

The Netflix Tech Blog also explains how actors and actresses are used as a metric in their algorithm. Watched the Kill Bill trilogy? You are likely to see a Pulp Fiction thumbnail centered on Uma Thurman. Or perhaps you enjoy movies like Grease. Instead of Uma, your Pulp Fiction thumbnail will focus on John Travolta instead…

 

With personalization on the rise across many industries, what else can streaming services do to retain customers?

Netflix’s competitors are likely to be working on similar recommendations algorithms to compete with the streaming giant. But we have all been there: opening up the Netflix app to find yourself scrolling for hours for something to watch. The algorithm may be highly personalized, but we don’t always find what we want. So the question is: what else can streaming services do to ensure their audiences are engaged and loyal?

 

Increasing engagement and loyalty by creating more value for paying subscribers

Customer loyalty is driven by creating value for consumers. One method to achieve this is introducing reward mechanics. Building on the principles of psychology, customers are more likely to repeat a certain behaviour if it fires up the reward centre in the brain. This gives brands the flexibility to drive more of the specific activities they want to see.
 

Customers who engage the most with a platform - whether that’s viewing time, rating content, referring friends and family, or simply talking about the latest releases on social media - could receive rewards like discounts or access to exclusive content. This will ensure Netflix subscribers are still interacting with the brand even if they cannot find something they want to watch. 

Event-based rewards system

To do this, companies need an event-based system. White Label Loyalty’s event-based logic allows complete customization. It doesn’t matter whether a platform wants to reward transactions, product reviews, or any other customer interactions - with our software, all of these behaviours and more can initiate a personalised reaction. 

 

You are watching Netflix. But Netflix watches you. And it knows what you will want to watch next!

Netflix’s army of product designers and data analysts have successfully created a personalization engine that gathers data on how each viewer clicks, watches, searches and chooses content. And it just keeps getting more intelligent. Each time a subscriber watches something, the personalization system becomes more accurate. This detailed algorithm helps Netflix retain its customers by displaying relevant content to each user, right down to the preview image. 
 

Why is personalization so important? For customers, it creates a better, more relevant user experience. For brands, it can reduce customer churn and increase revenue; according to Monetate and WBR Research, 93% of companies that use intelligent personalization strategies increased their profits last year.

So, what can you learn from Netflix’s personalization strategies?

Segmentation and personalization are the streaming service's secret recipe for creating customer loyalty. The media industry is driving these strategies forward, forcing brands from other industries to follow suit. If you cannot create the same kind of hyper-personalized experiences that customers are used to with brands like Netflix, you risk losing them to competitors who can. 
 

For example, if you’re an eCommerce business - do you have a rating system on your site that can be used to understand your customer's product preferences better? 

Are you able to use data to segment your customers and offer them more personalized recommendations for their next purchase? 

Can you use segmentation to tailor your communications to each group? 
 

To get started with personalization, you need access to customer data. Then, you need a platform that allows you to segment your customers. You can drive the behaviours you want to see by rewarding each segment with something valuable.  All of this, and so much more, is possible with White Label Loyalty’s software. Fill in our get in touch form to get started. 

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Helen Walker

Helen Walker

Creative & Content Marketing Executive

Helen is our Creative & Content Marketing Executive. She shares valuable information about the Future of Loyalty and will keep you up to date on the latest industry insights...

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Customer Retention
Technology
Data
Personalisation