netflix design case study

Blockbuster vs. Netflix

If the 2010s taught us anything, it’s that there’s no better example of a business that pivoted to meet customer needs and preferences than Netflix. Likewise, there’s no better example of a business that failed to pivot, innovate and meet modern market demands than Netflix’s original competitor: Blockbuster.

As a brick-and-mortar DVD rental business, customers had to drive to Blockbuster to get the latest new releases on video or DVD. In its early days in the aughts, Netflix delivered movies directly to customer’s doorsteps via the mail. Initially, that was an innovative model — until cable companies started offering movies on-demand. This left Netflix with a dilemma: why would customers order from Netflix and wait a few days when they could stream any movie anytime?

How both companies responded to the shift towards on-demand and online content illustrates the difference between traditional and agile business models, and shows why business leaders must constantly engage with customers to drive innovation and stay relevant.

The streaming revolution

Leaders at Netflix recognized the value of design thinking for what it is: a method to consistently hone their business offerings. Teams were encouraged to look for new opportunities to delight customers, drive engagement and generate new revenue. The approach? Empathize with customers,unearth pain points and find their unaddressed needs. 

Beginning in 2011, Netflix began producing their own original movies and streaming series. But they didn’t just stop at offering new shows: they dropped every episode of each season on the first day it was launched. Original and provocative programming like Orange Is The New Black, House of Cards and Bojack Horseman helped Netflix capitalize on the binge-watching phenomena, even spawning the now ubiquitous catchphrase “Netflix and chill”. With the watch-in-one-sitting binge option catching on like wildfire, shows were devoured by audiences. Eventually, even bigger streaming phenomena, like Stranger Things and Black Mirror, dominated the cultural conversation whenever a new season dropped, leaving everyone talking about one thing: Netflix.

Need to outpace the competition and shift your business model? Learn the basics of design thinking with our free eBook: Design Thinking 101

Continuing to innovate

In 2016, Netflix adapted to the market again, rebuilding their main landing page to capture user’s attention the moment they logged in. Instead of offering still images or series posters, they added auto-play trailers that launched on mouse hover. 

Seeing more opportunities to give users what they didn’t know they wanted, Netflix leveraged artificial intelligence and predictive analytics to create a unique experience for each viewer based on their own viewing habits. The “Because you watched” feature not only transformed the customer experience on Netflix — it transformed expectations for every other entertainment company scrambling to enter the streaming game.

Netflix discovered all of these innovations by using design thinking to empathize again and again with their customers. Meanwhile, Blockbuster stuck to their traditional brick-and-mortar model, making it harder for customers to get what they wanted, when they wanted it. Netflix knew their survival depended on knowing exactly what each and every customer wanted to experience when using their service, and consistently working to meet customers where they were at. By identifying customer needs and adapting, Netflix evolved; whereas Blockbuster, and DVD rentals in general, failed to compete and went extinct. 

An industry changed

The next time you’re tempted to think your business is fine and just sit back and rely on the same old strategies to deliver success, remember this story. The last Blockbuster closed in 2019, and ironically, Netflix eventually bought the IP for the brand and made a streaming comedy about the failed business. 

In the 2020s, more and more people are ditching cable in favor of Netflix and the various other services the streaming wars inspired. Nowadays, there’s nothing worse than sitting in front of the TV waiting for good content to come on. So, remember, “change happens pretty fast, if you don’t stop and look around once in a while, you could miss it.”

Learn how to evolve with the market, change your organization's DNA and gain a new perspective with customer empathy.

Get started with the foundations of human-centered design with ExperienceInnovation™ | Aware . 

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Analyzing Netflix Design, UI and UX: Why It Creates Immersive Experiences

Netflix began in 1997 as a competitor to Blockbuster. Now, it has as many users as the entire population of Canada, UK, and Japan combined.

Last year, 10 out of the top 15 most streamed programs in the world were produced by Netflix. It’s is still the king of streaming.

And its customers continue to renew their subscription, even after their attempts to avoid account sharing and their changes in pricings and plans, some of which now display ads.

So, how does a behemoth like Netflix create immersive experiences so captivating that the platform cannot be dethroned by its sea of competition , including Disney+, HBO and Prime Video?

Let’s break down all the elements of Netflix’s UI design and user experience (UX) .

Table of contents

Seamless onboarding process across all devices.

• How Netflix markets its trending original series 

Personalization for the win

An email marketing strategy that highlights new content, netflix’s user journey: why it keeps new users hooked.

Unlike other platforms, where the “wow” comes after inputting your credit card information, Netflix reels in new users right from their homepage. The design and copy are minimal, with one goal—signups.

The homepage presents a clean visual hierarchy and is free of clutter, reducing friction between the visitor and the single, straightforward call-to-action to enter an email to get started. 

Their unique selling proposition also explicitly describes the biggest benefits and preempts two common FAQs: “Unlimited movies, TV shows, and more. Watch anywhere. Cancel anytime.” 

The goal is obvious, the ask is clear, the task is simple.

Together, the USP and UI makeup a value proposition that is optimized for conversions. They are incredibly specific about what they do, include relevant images in the background that support the “unlimited” claim, and feature a value prop booster (i.e. “cancel any time”).

Other elements below the fold that add value include:

• Mention of the numerous platforms Netflix is compatible with, such as game consoles and connected TV devices
• An example of how to download streaming content to watch offline, as well as the ability to stream unlimited movies across all devices
• The provision of child-friendly programming options
• A Frequently Asked Questions (FAQ) section placed directly above a second opt-in form

Here, Netflix has chosen to emphasize its flexibility. Their homepage isn’t offensively long. They use minimal copy to communicate their offering, features, benefits, and FAQs to combat obstacles and sway hesitant buyers.

From there, the user embarks on a short personalized journey. Netflix highlights that there are only three steps, which work to increase motivation to complete the task at hand. 

The expectancy-value theory postulates that if the expectation of completing a task is high, and the subjective value is also high, people will be more motivated to follow through. In other words, motivation = expectancy x value. If either one of these factors is missing, motivation easily disintegrates.

By centering “Step 1 of 3”, it dictates that the task will take a short amount of time, thus increasing expectancy. By this stage, the value should already be high (given their strong value proposition, USP, and UX). 

On the second screen, they ask you to choose a plan. They again answer the biggest objection upfront to combat hesitancy: “No commitments, cancel anytime.” 

Then, you choose your plan. They follow the rule of three when listing out their plans to keep benefits compact and engaging.

This reduces overwhelm and provides ample opportunity to opt out. They list their core benefits again to remind the user why they clicked the signup button in the first place (this works to keep the subjective value high).

Once a user has created an account, Netflix prompts them to choose a few movies or TV titles they enjoy. This data is then used as inputs in the Netflix algorithm to “jump-start” personalized recommendations (more on personalization based on their algorithm in a moment). 

Post-signup, the first thing you see is an auto-playing video trailer from one of their original productions that is similar to the preferences selected during onboarding.

The primary CTA is to press “Play” to interact with the platform straight away. Akin to “frustration-free” packaging, a prominent play button motivates engagement and works to keep users on the platform longer.

Once watching commences, their behavior supersedes initial preferences as their algorithm continuously populates the homepage with newly relevant media.

Every streaming option on Netflix also allows a user to thumbs up or thumbs down the content, further instructing the preference algorithm. 

For example, when you rate thumbs up for Tiger King, Netflix will show you more true crime documentary series. 

The algorithm also estimates “likelihood to watch” based on dozens of metrics, such as:

• Viewing history
• Genre or category 
• Time of day watched
• How long the user watched
• Devices currently streaming
• Rating history for similar content
• Other Netflix users with similar preferences on the platform 

Their algorithm is continually retrained with specific user signals to improve the accuracy of their recommendations and deliver on their promise of a personalized viewing experience.

Netflix UX lesson #1 

• Simplify the user interface. Make your CTA prominent and clear and state your most important benefits next to relevant images. 
• Specify the number of steps to complete the signup to increase expectancy and boost motivation. Implement user testing to ensure your UX has minimal barriers to conversion. 
• Overcome obstacles by addressing common questions in an FAQ section before your final CTA.
• Emphasize personalization wherever you can. Netflix has taken pains to tailor the experience to users’ expectations. 

There are ways you can implement user preferences even if your platform doesn’t use intelligent algorithms. From the beginning, Netflix asked users to state their preferences. They then delivered a customized homepage based on those answers. 

Netflix’s sign-up process can be completed on many digital devices, including:

• iPhone, iPad, and iPod Touch
• Smart TV and Streaming Media Players

After registering, a user will be brought to a home screen. They can add a profile by clicking on a simple plus sign icon—another example of efficient UI design. 

From here, the user can customize their profile name, add child restrictions, and even add up to four additional profiles for family members or friends to watch across devices anywhere in the world.

To complete the onboarding process, they can customize the type of streaming material they’ll see, including:

• Profile lock 
• Maturity level
• Playback settings
• Viewing activity log
• Subtitle appearance
• Language preference
• Specific viewing restrictions
• Personalized TV show and movie suggestions

Netflix’s customization capabilities aren’t necessarily more intelligent than the competition. What helps them differentiate is that they feature them in their onboarding process instead of hiding them in the settings panel. 

This allows the user to feel like they’re tailoring a unique experience from the beginning (keeping subjective value high).

Netflix UX lesson #2: 

• Another nod to simplification—streamline your onboarding and login screen. Include only the most necessary buttons and copy, and where possible, exchange text for universally understood symbols.
• Give your users the ability to customize their experience. You may already have opportunities to do this in your settings, such as setting language or notification preferences. 
• Let users know about this or walk them through the preference set up in the onboarding stage.

As with the rest of their user journey, the beginning is simple, easy, and customer-focused. Once users get into the platform, they’re given an abundance of choice—starting with Netflix’s original content.

Putting an emphasis on original productions 

Right above the fold are the latest trending content and Netflix originals. The original productions are made to be larger than any other content to communicate their value. 

Recent years have seen a steep increase in the number of households cutting ties with traditional paid TV and opting for other viewing platforms. This trend of cord-cutting and streaming preference was exacerbated by the pandemic and is forecast to continue.

“Consumers are choosing to cut the cord because of high prices, especially compared with streaming alternatives. The loss of live sports in the late years contributed to further declines. While sports have returned, people will not return to their old cable or satellite plans.” – Eric Haggstrom , eMarketer forecasting analys

With this shift has come an increased demand for “streaming originals,” which Netflix has dominated since 2012. Over the past few years, Netflix has grown from just eight hours of original content to nearly 3,000 hours of Netflix originals . 

According to Nielsen research , 10 out of the top 15 most popular original video content among streaming providers in the U.S. in 2022 were produced by Netflix. 

Original Netflix series such as Orange Is the New Black, Stranger Things, and Black Mirror have become cult classics among modern television enthusiasts. More than 105 million users have watched at least one episode of Orange Is the New Black alone, according to an exclusive interview with ex-executive Cindy Holland.

Though the platform’s ease of use may have exploded their popularity, it’s these original productions that continue to add value to a user’s subscription. 

The success of these series has bred innovative tactics that draw users deeper into the Netflix catalog. For each original series, Netflix will develop a dozen thumbnail options that will rotate depending on a user’s specific interests. This tactic is referred to as “ artwork personalization ”.

Take a Netflix original production such as Stranger Things, for instance. If a user has expressed interest in comedies, their platform will display a lighthearted Stranger Things thumbnail with the kids dressed as Ghostbusters. But if a user were to routinely watch crime dramas, Netflix would display a more serious thumbnail of a police officer looking over a foggy pumpkin patch. 

This active personalization and consideration of a user’s preferences is one reason why Netflix’s retention rate has remained so consistent over time.

How Netflix markets its trending original series 

Netflix updated its product design to replace still images with video trailers that auto-play as soon as a customer starts scrolling.

In the example above, hovering over My Unorthodox Life auto-plays a video trailer about how Julia Haart went from escaping a cult to a successful New York City CEO in seven years.

This UX tactic envelops users in potential binge-watch material, providing a quick view of content that may have been skipped over without the trailer. 

Netflix UX lesson #3: 

• Give your high-value content pride of place. Feature it prominently, give it a badge, promote it with video, or find another way to help it stand out among the crowd.
• Continually add value to your platform. Netflix does this through its original content.
• If possible, tailor your high-value content to each segment. Netflix does this through the algorithm’s selection of content and their thumbnail design.

We’ve learned about Netflix’s simple, customer-centric user journey that gets users into the platform quickly and easily. Now let’s look at how they’ve mastered the art of keeping them there.

A retention strategy that puts personalization at the forefront 

Research from Parks Associates indicates that the average Netflix user has had their subscription for more than 50 months. 

On average, two-thirds of users still pay for the service one year after joining. For comparison, only 53% of Hulu users are still signed up in the same timeframe. 

The popularity among existing users may also explain why new users are so attracted to the idea of subscribing.

During the early months of the COVID-19 pandemic, in which many Americans cut back on frivolous spending, Netflix experienced the biggest growth spurt in its history. The company added 15.77 million subscribers in the first three months of 2020 alone. 

Netflix’s growth has slowed as the pandemic eases, but they’re still a consumer favorite.

For the users that do want to cancel, Netflix makes the process easy while still giving them opportunities to change their minds or come back at any time. 

What else can we learn from the platform about how to keep users around for longer?

Personalization is a major factor in why Netflix boasts such high retention rates. As we mentioned above, even thumbnail images on Netflix are customized to match exactly what each user would prefer to see. 

In each row below the fold of the homepage, there are three layers of personalization:

• The choice of a row, such as Continue Watching, New Releases, Trending Now, and Because You Watched
• The choice of titles within the row, such as new comedies within New Releases for users who prefer humor
• The ranking of chosen titles, such as placing a romantic comedy before a children’s comedy for users who enjoy more explicit material 

In each row of recommendations, the Netflix algorithm weighs dozens of different factors (which they keep close to the chest) to present what they believe a user will want to watch at that moment.

For shows you’ve already started watching, the primary button changes from “Play” to “Resume”. It also prominently displays what episode you are on as well as episode progress. 

Offering so much choice may seem like a luxury held in reserve for only the most successful platforms. But leveraging this power of selection has driven their success—and the competition has cottoned on. Hulu, Amazon Prime, and Disney+ all offer ample options to choose from, too.

Netflix also runs a consistent email marketing strategy that highlights new content on the platform. They also invite stagnant users to check out the latest developments in shows they’ve previously watched to spark reengagement. 

After an initial welcome email, they typically send out four to seven emails per month to subscribers. Though highly personalized to a user’s watching history, the email subjects typically include:

• New Netflix original content
• New seasons of a show a user previously watched 

Netflix utilizes a standardized template that allows it to maintain consistent branding across all messaging . The template also allows for GIFs and moving images to grab and hold a reader’s attention. 

Within the email, users can add shows straight to their list or get started watching. 

Netflix UX lesson #4: 

• Give users the opportunity to choose. Let them personalize their experience and give them as many options as you can allow.
• Make cancellation painless, but offer opportunities for users to change their minds. Netflix does this by offering to keep in touch via email (and then showing users what they’re missing regularly throughout the month). 
• Remind users to return to the platform repeatedly through an engaging email marketing strategy.

Of all the streaming platforms, Netflix is the one service that continues to reign supreme, year after year. Both their cutting-edge UI and UX design and high-performing original content keep users engaged and returning. 

From a simple interface to highly customized recommendations, Netflix has managed to create a truly immersive experience. 

To replicate an experience that rivals Netflix, startup founders should pay keen attention to visual hierarchy. Avoid clutter, keep content highly personalized, and always keep your targeted call-to-action front and center.

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Erica Schneider

Erica is Head of Content & Operations at Grizzle, a content marketing & SEO agency that helps SaaS and technology brands achieve organic growth and build media empires.

Join the conversation Add your comment

You’re right! Netflix has definitely created immersive usability. The #1 thing every business owner and company NEEDS to scale. If the product/service gets results – and has high usability – it’ll do exceptionally well. Great article, people underestimate the thought put into even simple campaigns done by large companies. Good stuff here!

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Stay ahead in SaaS: How to out UX your competitors...

How Netflix creates Immersive UX Design and What We Can Learn From Them

19 minutes.

This is, on average, how much scrolling time it takes for a Netflix user to either settle for a show or movie or give up (and change platform).

We have so many titles to choose from that we are flooded with indecisiveness. We are happy when offered a panel of choices but we will become less happy the more options we have. That’s the Paradox of Choice phenomenon that American psychologist Barry Schwartz observed. In addition, the more time we take to choose what to stream, the pickier we are: we want to select the ✨perfect ✨title. But how does Netflix manage to have such an impressive UX design ?

Table of Contents

Who’s Watching?

You’d be shocked about how much Netflix knows about you and your watching habits. It actually knows on which day you open the app and at what time of the day, what type of content you watch and for how long, it also knows when you pause and for how long. All this information goes into their magnificent algorithm which allows to give you the ✨ perfect recommendation page✨ to minimise your effort in finding something to enjoy.

To solve the everlasting problem of not finding anything to watch after infinite scrolling that users are facing, they have come up with many very interesting new features over the years. This includes the Top 10 row, Play Something on TV, the ability to edit and tidy the Continue Watching row.… It has recently introduced a set of new features to help them understand what its customers are actually looking for when they open the app:

Evolutive rating system

👍🏻 thumbs-up/thumbs-down.

Netflix gives the ability to rate movies and tv shows by giving a thumbs up or thumbs down. This allows them to, once again, have more information on your movie and tv series preferences. It also allows comparing what you watch with what other people watch to create a pattern with people who have similar tastes. This is how they are able to suggest titles with a match percentage.

👍🏻 👍🏻 Double Thumbs Up

Their new double thumbs-up feature draws from their already existing rating system with a depth added to it. This is part of their continuing journey in learning to understand their customers better. Netflix actually had a 5-star rating system which they gave up in 2017.

During an interview with the Verge , Christine Doig-Cardet, their director of product innovation and personalisation experiences said: “We hope to end choice fatigue with new features that we’re adding this year. It’s a huge part of where we want to invest — providing those mechanisms to give more of the control back to the user to help tailor their experience to their personal taste.”

Netflix wants to get to know you 😉

🔀 play something.

Want to watch something but not sure what? We got you covered! Starting today you’ll find PLAY SOMETHING when you log on to Netflix — locate it underneath your name, as a row on the homepage, or in the menu. It will show you one of three things… pic.twitter.com/xkHgfMHYpR — Netflix (@netflix) April 28, 2021

A year ago, they introduced “Play Something”, a somehow controversial addition to their extensive features list.

I’ve personally tested Play something for the sake of it. The results I got were not very conclusive. Most of the shows they suggested were titles from My List or shows that I had already watched on another streaming platform.

Play Something is a tool that will show us:

• A new series/film similar to the ones you’ve watched before,
• An episode/film you’ve already watched and may want to watch again if it’s been a while, or
• An episode from a show you’ve started but haven’t finished (it will pick up where you left off).

This makes sense, most of the titles suggested have already been featured on my homepage. This feature would be great for people who are indecisive about what they want to watch but not when they want something new. I would rather keep scrolling or choose something from My List.

🔥 New & hot: Coming soon, Everyone’s watching, Top 10

Netflix has added a new section on their mobile app, called New & Hot which includes three categories of recommendations:

The three categories follow the same model of user interaction. You watch the snippet offered to you and choose to either interact with it (add it to “My List” or stream the title) or skip to the next snippet. This section allows to keep the user updated on what they will be able to watch on the app very soon.

People influence people. It’s common for a user to ask their friends whether this show or movie is worth watching. Netflix made it easier for users to know what people worldwide are binging. They created a new section where users can find what’s popular to watch.

🤣 Fast Laugh

This feature allows the user to watch ten second-snippets of movies and tv series. The format follows the structure TikTok has popularised these last few years with infinite scrolling. The user, after watching the snippet, can interact with the content by giving “LOL”, adding the show to their “My List”, sharing the snippet on social media, or playing the movie/show directly. This features more titles that haven’t been previously suggested on the Homepage. Again, this allows Netflix to get to know your tastes better by suggesting titles that you haven’t been familiar with, at least not to their knowledge.

How does their recommendation system work?

Netflix has perfected its recommendation system through the years to give its users the best experience possible when logging in. Not only do they include titles based on your watching history (what you liked, disliked and binge-watched), but it will also choose which rows to suggest first, such as Continue Watching, Watch it Again, Only on Netflix, or, you might even have heard or experienced yourself some hilarious category name:

I didn't realise #Netflix had a category based on the PhD experience #phdlife #phdlife pic.twitter.com/3hdL5n624Y — Alex Mullins (@AlexJMullins) February 21, 2019

They also pay attention to the rank of each title on every row they are suggesting, making it sometimes wholesome.

Netflix also showing love to @KimsConvenience in a number of other categories ("Oddballs & Outcasts"?) pic.twitter.com/aHgQVUvh6T — Kevin Lee (@kglee) July 29, 2018

🤔 Netflix tagging

These category names have a background to them. Each title has “tags” on it, such as genres: Comedy, Romance, Thriller…, but also basic tags: Quirky, Provocative, Suspenseful, Psychological… I think you get the gist. These tags come from professional taggers, and they are exactly what you think they are: people whose job is to watch movies and tv shows with the sole purpose of tagging with words or phrases that describe them the best so that you, as a user, can enjoy very precise recommendation afterwards.

🎨 Netflix artwork

Have you ever noticed the artwork suggested on your homepage? Here are three of the many artworks for Stranger Things that showed up on my homepage the last few days.

This helps to know what kind of artwork would attract the most users, and which artwork would be the most persuasive to you . If you’ve spent the last week watching female leading tv shows, for example, the first artwork would show up. This works for any title but has a focus on Original content.

Netflix doesn’t want you to leave, at all.

🫂 retention.

All of the features mentioned earlier are a part of Netflix’s strategy for customer retention. In this section, we are tackling retention when watching a series. Netflix has popularised binge-watching series, but they are continuing to better it.

In 2019, they changed the countdown time before the next series episode will start. They discovered that the ten-second countdown massively increased hours watched . When you’re binge-watching your series, cosily wrapped in your blanket, you absolutely don’t want to move a finger to press the “watch next episode” button, and you surely don’t want to wait an eternity before continuing your series. This is how they designed it. Enough time for you to digest the episode but not too much that you would lose interest, and surely not enough time to decide to stop watching the series.

👀 binge-watching, verb, /ˈbɪndʒ ˌwɑːtʃ/ to watch several episodes (= separate parts) of a television series or programme, one after another.

🥱 Idleness aversion

You can’t expect your customer to have 100% engagement on your product; our attention span doesn’t allow us to do that. But you can still make your customer happy by subconsciously keeping them busy. Netflix’s way of tackling idleness aversion is genius, here’s why:

Netflix: Should I play this movie? Me: No no I'm just looking at it for a second Netflix: I'll put it on Me: I'm just literally reading what it is Netflix: It's playing 🙂 — Jon (@ArfMeasures) October 28, 2019

Netflix wants you to check out what they have for you. Auto Play will always be here to ensure you are fed with information. This strategy works wonders. Your brain might be focused on that specific title you wanted to stream, but while looking for it, it will give you information on other titles that might pique your interest.

Netflix’s strategy is not about collecting the more information possible from their customers. It’s actually about collecting the right information to improve their recommendation algorithm while also not losing money. They have thoroughly understood why UX is so important and continue to shoot for the moon to find new ways to keep their customer experience as seamless as possible. It strives to achieve a user experience that is both inclusive and innovative. Here are four lessons that we can learn from Netflix:

• Keep a simple user interface with clear CTAs that make users want to click.
• Focus on personalisation as much as you can; users need to feel that they are listened to and understood. Provide a tailored user experience whenever you can; this will make your customers engage with your product much more easily.
• Continuously adding value to your brand. Find a competitive advantage that users can only find with you, just like Netflix originals.
• Apply Idleness Aversion by keeping your customer engaged with information (visuals, animation or gamification )

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How Netflix Uses Design Thinking to Reinvent Itself Over and Over

Netflix Design Thinking? You bet! Within the past decade, there isn’t a better example of a business that has pivoted on the basis of customer preferences, wants and needs than Netflix. And there’s no better example of a business that didn’t, than Netflix competitor Blockbuster.

Do you remember when you had to drive to Blockbuster to get the latest new releases on video or DVD? In its early days, Netflix was a service that delivered movies to customers direct to your doorstep by mail. That was an innovative model until cable companies started offering movies on-demand. Why would someone order from Netflix and wait a few days for a physical cassette when they could stream a movie right there and then?

Time for some Netflix Design Thinking?

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Netflix’s Competitive Strategy & Growth Strategies

Netflix’s competitive strategy and growth strategies define the operational activities and tactics for developing the business. The competitive advantages based on the company’s generic competitive strategy support competitiveness against many large firms in the entertainment industry. Netflix’s intensive growth strategies use these competitive advantages to grow the business, such as by competing to grow the company’s market share. The company’s strategic objectives indicate the importance of low costs and a large international subscriber base. The combination of Netflix’s competitive strategy and growth strategies ensures that the company improves its financial performance and finds new ways to generate more revenues.

The appropriateness of Netflix’s competitive strategy depends on the industry situation and the competitive environment. The company’s strategic prioritization of cost effectiveness for competitive advantage is based on the industry environment where many firms compete based on price. As a result, Netflix’s growth strategies prioritize market share growth to ensure profitability despite low-cost measures.

Netflix’s Competitive Strategy

Netflix’s competitive strategy is cost leadership , which functions as the primary strategy for the company’s competitive advantages. According to Porter’s model of generic strategies, cost leadership ensures competitive advantage based on low costs that can be used to offer competitive prices to the company’s target customers, e.g., subscribers. The cost-based nature of this competitive strategy has wide-ranging effects on Netflix’s strategic objectives. For example, competitive prices facilitate market reach maximization, which is a strategic goal based on Netflix’s mission statement and vision statement . Low costs enable profitable operations despite low prices, which attract more subscribers around the world. This means that Netflix’s competitive strategy of cost leadership facilitates endeavors for growing the company’s market share.

Netflix also uses differentiation as a secondary competitive strategy. The goal of this strategy is to develop competitive advantages based on factors that make the company stand out when compared to rivals. For example, as one of Netflix’s competitive strategies, differentiation is implemented in the production of original content (movies and series), which ensures the company’s competitive advantages by retaining subscribers who prefer to watch content that is not available from competing video streaming services. These competitors include the entertainment production and streaming services of Disney , NBCUniversal, and Sony , as well as Google’s (Alphabet’s) YouTube, Apple , Amazon , Microsoft , and Facebook (Meta) . The Five Forces analysis of Netflix demonstrates that these companies’ competitive strategies create a challenging industry environment. Netflix’s competitive strategy of differentiation helps address this competition and its strategic challenges.

Netflix’s Growth Strategies

Netflix’s growth strategy is market penetration , which is the primary driver of the company’s growth and expansion in the international market. In Ansoff’s matrix, this intensive growth strategy’s objective is to grow the business by selling more of current products to the company’s current market. For example, Netflix aims to gain more subscribers through its current operations in North America, Europe, and Asia. A bigger market share equates to higher revenues and a bigger market presence that can be used to launch new products. For this intensive growth strategy of market penetration, the competitive advantages enumerated in the SWOT analysis of Netflix are used to penetrate markets and gain market share despite competition. Also, the generic competitive strategies of cost leadership and differentiation enable attractive pricing and unique entertainment content, respectively, to attract more subscribers for this growth strategy of market penetration.

Netflix also uses product development as a secondary growth strategy. The Ansoff matrix states that this intensive growth strategy involves offering new products to the company’s current market. In this case of Netflix’s growth strategy, the company’s strategic objective is to produce new original movies and series, which are new products for current and new subscribers in current markets. New original content makes the company’s streaming service an attractive option for customers. The requirements of product development as an intensive growth strategy apply to Netflix’s operations management , such as in maximizing productivity in producing new movies and series. New entertainment content resulting from the application of this growth strategy contributes to uniqueness that enables the company’s generic competitive strategy of differentiation.

Netflix applies diversification as a minor growth strategy with a limited impact on the company’s current business growth. In Ansoff’s matrix, this intensive growth strategy’s objective is to produce new products for new markets. In this case of Netflix’s growth strategy, product development involves offering entirely new products other than the company’s initial core offerings. For example, the company now offers mobile games. The mobile gaming market can support new business growth by attracting gamers, especially those who do not yet have a Netflix account. As a growth strategy, diversification involves new teams, groups, or divisions in Netflix’s organizational structure (business structure) , which influences the availability of resources for implementing this growth strategy. The generic competitive strategy of differentiation ensures that these new products are unique. Also, Netflix’s competitive strategy of cost leadership determines the cost structure and limits for these new products’ competitive advantage based on low costs that translate to affordability.

• Gómez, R., & Munoz Larroa, A. (2023). Netflix in Mexico: An example of the tech giant’s transnational business strategies. Television & New Media, 24 (1), 88-105.
• Iordache, C., Raats, T., & Mombaerts, S. (2023). The Netflix Original documentary, explained: Global investment patterns in documentary films and series. Studies in Documentary Film, 17 (2), 151-171.
• Leppänen, P., George, G., & Alexy, O. (2023). When do novel business models lead to high performance? A configurational approach to value drivers, competitive strategy, and firm environment. Academy of Management Journal, 66 (1), 164-194.
• Netflix, Inc. – Form 10-K .
• Netflix, Inc. – Long Term View .
• Netflix, Inc. – Top Investor Questions .
• U.S. Department of Commerce – International Trade Administration – Media and Entertainment Industry .
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Netflix case study, inspiration feature.

Spend less time browsing and more time watching

Introduction

• Interface Design
• Future Scope
• Roles & Responsibilities

This is not a real project and we have not worked with Netflix in any official capacity.

Imagine sitting down after a hard days work, wanting to find something new to watch but instead you've found yourself browsing an endless library of thumbnails for over 10 minutes.

You read the odd description, watch the odd preview but it's maybe not the right genre, or you don't have 3 hours to sit through a film. You are stumped.

This sounds familiar doesn't it?

What we wanted to achieve, was an easy to access feature within the app that felt native to the Netflix ecosystem, was quick to use and helped people find something to watch quicker.

We designed an icon that compliments the current set of Netflix assets, striking and obvious. New, yet familiar.

User Interface

The UI of the Inspire feature leans on the existing elements of the Netflix user interface.

We used a segmented control as a way of progressively disclosing further options to refine the search. These controls are an easy way to choose between a movie, a series or a documentary before refining.

The idea for this concept came from two particular frustrations whilst using Netflix.

Struggling to find media of a certain run time

As a result losing time endlessly browsing

The result of these issues generally led to not watching anything at all so with this concept we wanted to change that. The current Netflix search function is a simple text entry system, with this you already need to know what you're looking for or who you want to watch.

The Inspire feature at the most basic level is simply an advanced search, with fields that target the above pain points and get users to media they want to watch quicker.

It is a small feature that offers a very positive impact.

Future enhancements

This concept could be built out to include features such as a Netflix Originals checkbox. We may also take a look in future as to how this solution could work across the entire Netflix ecosystem.

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Your targets are our targets. We approach every project with empathy, creative thinking and a focus on user experience.

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We shared a presentation of the prototype on various social media platforms.

We were not surprised that the feedback reflected our own experiences of using Netflix. Whilst we focused our efforts in this occasion on the Netflix app, these ideas could be applied to most streaming services.

As this was a conceptual RAD project, we took care of the journey mapping, investigation, creative thinking, user interface design and prototyping. Ideas based on experience.

This case study is an example of the work RAD can do by alleviating pain points by implementing small, non-disruptive, changes to the UI to make a big difference in the UX.

We don't need to design projects from the ground up, we can improve products without impacting on existing brand guidelines or design systems.

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Designing Netflix is a quite common question of system design rounds in interviews. In the world of streaming services, Netflix stands as a monopoly, captivating millions of viewers worldwide with its vast library of content delivered seamlessly to screens of all sizes. Behind this seemingly effortless experience lies a nicely crafted system design. In this article, we will study Netflix’s system design.

Important Topics for the Netflix System Design

• Requirements of Netflix System Design
• Microservices Architecture of Netflix 
• How Does Netflix Onboard a Movie/Video?
• How Netflix balance the high traffic load
• Data Processing in Netflix Using Kafka And Apache Chukwa
• Elastic Search
• Apache Spark For Movie Recommendation
• Database Design of Netflix System Design

1. Requirements of Netflix System Design

1.1. functional requirements.

• Users should be able to create accounts, log in, and log out.
• Subscription management for users.
• Allow users to play videos and pause, play, rewind, and fast-forward functionalities.
• Ability to download content for offline viewing.
• Personalized content recommendations based on user preferences and viewing history.

1.2. Non-Functional Requirements

• Low latency and high responsiveness during content playback.
• Scalability to handle a large number of concurrent users.
• High availability with minimal downtime.
• Secure user authentication and authorization.
• Intuitive user interface for easy navigation.

2. High-Level Design of Netflix System Design

We all are familiar with Netflix services. It handles large categories of movies and television content and users pay the monthly rent to access these contents. Netflix has 180M+ subscribers in 200+ countries.  

Netflix works on two clouds AWS and Open Connect . These two clouds work together as the backbone of Netflix and both are highly responsible for providing the best video to the subscribers. 

The application has mainly 3 components:

• Device (User Interface) which is used to browse and play Netflix videos. TV, XBOX, laptop or mobile phone, etc
• CDN is the network of distributed servers in different geographical locations, and Open Connect is Netflix’s own custom global CDN (Content delivery network).
• It handles everything which involves video streaming.
• It is distributed in different locations and once you hit the play button the video stream from this component is displayed on your device.
• So if you’re trying to play the video sitting in North America, the video will be served from the nearest open connect (or server) instead of the original server (faster response from the nearest server).
• This part handles everything that doesn’t involve video streaming (before you hit the play button) such as onboarding new content, processing videos, distributing them to servers located in different parts of the world, and managing the network traffic.
• Most of the processes are taken care of by Amazon Web Services.

2.1. Microservices Architecture of Netflix 

Netflix’s architectural style is built as a collection of services. This is known as microservices architecture and this power all of the APIs needed for applications and Web apps. When the request arrives at the endpoint it calls the other microservices for required data and these microservices can also request the data from different microservices. After that, a complete response for the API request is sent back to the endpoint. 

In a microservice architecture, services should be independent of each other. For example, The video storage service would be decoupled from the service responsible for transcoding videos.

How to make microservice architecture reliable?  

• Use Hystrix (Already explained above)
• We can separate out some critical services (or endpoint or APIs) and make it less dependent or independent of other services.
• You can also make some critical services dependent only on other reliable services.
• While choosing the critical microservices you can include all the basic functionalities, like searching for a video, navigating to the videos, hitting and playing the video, etc.
• This way you can make the endpoints highly available and even in worst-case scenarios at least a user will be able to do the basic things.
• To understand this concept think of your servers like a herd of cows and you care about how many gallons of milk you get every day.
• If one day you notice that you’re getting less milk from a cow then you just need to replace that cow (producing less milk) with another cow.
• You don’t need to be dependent on a specific cow to get the required amount of milk. We can relate the above example to our application.
• The idea is to design the service in such a way that if one of the endpoints is giving the error or if it’s not serving the request in a timely fashion then you can switch to another server and get your work done.

3. Low Level Design of Netflix System Design

3.1. how does netflix onboard a movie/video.

Netflix receives very high-quality videos and content from the production houses, so before serving the videos to the users it does some preprocessing.

• Netflix supports more than 2200 devices and each one of them requires different resolutions and formats.
• To make the videos viewable on different devices, Netflix performs transcoding or encoding, which involves finding errors and converting the original video into different formats and resolutions. 

Netflix also creates file optimization for different network speeds. The quality of a video is good when you’re watching the video at high network speed. Netflix creates multiple replicas (approx 1100-1200) for the same movie with different resolutions.

These replicas require a lot of transcoding and preprocessing. Netflix breaks the original video into different smaller chunks and using parallel workers in AWS it converts these chunks into different formats (like mp4, 3gp, etc) across different resolutions (like 4k, 1080p, and more). After transcoding, once we have multiple copies of the files for the same movie, these files are transferred to each and every Open Connect server which is placed in different locations across the world. 

Below is the step by step process of how Netflix ensures optimal streaming quality:

• When the user loads the Netflix app on his/her device firstly AWS instances come into the picture and handle some tasks such as login, recommendations, search, user history, the home page, billing, customer support, etc.
• After that, when the user hits the play button on a video, Netflix analyzes the network speed or connection stability, and then it figures out the best Open Connect server near to the user.
• Depending on the device and screen size, the right video format is streamed into the user’s device. While watching a video, you might have noticed that the video appears pixelated and snaps back to HD after a while.
• This happens because the application keeps checking the best streaming open connect server and switches between formats (for the best viewing experience) when it’s needed. 

User data is saved in AWS such as searches, viewing, location, device, reviews, and likes, Netflix uses it to build the movie recommendation for users using the Machine learning model or Hadoop. 

3.2. How Netflix balance the high traffic load

1. elastic load balancer.

ELB in Netflix is responsible for routing the traffic to front-end services. ELB performs a two-tier load-balancing scheme where the load is balanced over zones first and then instances (servers).  

• The First-tier consists of basic DNS-based Round Robin Balancing. When the request lands on the first load balancing ( see the figure), it is balanced across one of the zones (using round-robin) that your ELB is configured to use.
• The second tier is an array of load balancer instances, and it performs the Round Robin Balancing technique to distribute the request across the instances that are behind it in the same zone.

ZUUL is a gateway service that provides dynamic routing, monitoring, resiliency, and security. It provides easy routing based on query parameters, URL, and path. Let’s understand the working of its different parts:

• The Netty server takes responsibility to handle the network protocol, web server, connection management, and proxying work. When the request will hit the Netty server, it will proxy the request to the inbound filter.
• The inbound filter is responsible for authentication, routing, or decorating the request. Then it forwards the request to the endpoint filter.
• The endpoint filter is used to return a static response or to forward the request to the backend service (or origin as we call it).
• Once it receives the response from the backend service, it sends the request to the outbound filter.
• An outbound filter is used for zipping the content, calculating the metrics, or adding/removing custom headers. After that, the response is sent back to the Netty server and then it is received by the client.

Advantages of using ZUUL:

• You can create some rules and share the traffic by distributing the different parts of the traffic to different servers.
• Developers can also do l oad testing on newly deployed clusters in some machines. They can route some existing traffic on these clusters and check how much load a specific server can bear.
• You can also test new services. When you upgrade the service and you want to check how it behaves with the real-time API requests, in that case, you can deploy the particular service on one server and you can redirect some part of the traffic to the new service to check the service in real-time.
• We can also filter the bad request by setting the custom rules at the endpoint filter or firewall.

In a complex distributed system a server may rely on the response of another server. Dependencies among these servers can create latency and the entire system may stop working if one of the servers will inevitably fail at some point. To solve this problem we can isolate the host application from these external failures.

Hystrix library is designed to do this job. It helps you to control the interactions between these distributed services by adding latency tolerance and fault tolerance logic. Hystrix does this by isolating points of access between the services, remote system, and 3rd party libraries. The library helps to:

• Stop cascading failures in a complex distributed system.
• control over latency and failure from dependencies accessed (typically over the network) via third-party client libraries.
• Fail fast and rapidly recover.
• Fallback and gracefully degrade when possible.
• Enable near real-time monitoring, alerting, and operational control.
• Concurrency-aware request caching. Automated batching through request collapsing 

3.3. EV Cache

In most applications, some amount of data is frequently used. For faster response, these data can be cached in so many endpoints and it can be fetched from the cache instead of the original server. This reduces the load from the original server but the problem is if the node goes down all the cache goes down and this can hit the performance of the application.

To solve this problem Netflix has built its own custom caching layer called EV cache. EV cache is based on Memcached and it is actually a wrapper around Memcached. 

Netflix has deployed a lot of clusters in a number of AWS EC2 instances and these clusters have so many nodes of Memcached and they also have cache clients.

• The data is shared across the cluster within the same zone and multiple copies of the cache are stored in sharded nodes.
• Every time when write happens to the client all the nodes in all the clusters are updated but when the read happens to the cache, it is only sent to the nearest cluster (not all the cluster and nodes) and its nodes.
• In case, a node is not available then read from a different available node. This approach increases performance, availability, and reliability.  

3.4. Data Processing in Netflix Using Kafka And Apache Chukwa

When you click on a video Netflix starts processing data in various terms and it takes less than a nanosecond. Let’s discuss how the evolution pipeline works on Netflix. 

Netflix uses Kafka and Apache Chukwe to ingest the data which is produced in a different part of the system. Netflix provides almost 500B data events that consume 1.3 PB/day and 8 million events that consume 24 GB/Second during peak time. These events include information like:

• UI activities
• Performance events
• Video viewing activities
• Troubleshooting and diagnostic events.

Apache Chukwe is an open-source data collection system for collecting logs or events from a distributed system. It is built on top of HDFS and Map-reduce framework. It comes with Hadoop’s scalability and robustness features.

• It includes a lot of powerful and flexible toolkits to display, monitor, and analyze the result.
• Chukwe collects the events from different parts of the system and from Chukwe you can do monitoring and analysis or you can use the dashboard to view the events.
• Chukwe writes the event in the Hadoop file sequence format (S3). After that Big Data team processes these S3 Hadoop files and writes Hive in Parquet data format.
• This process is called batch processing which basically scans the whole data at the hourly or daily frequency.

To upload online events to EMR/S3, Chukwa also provide traffic to Kafka (the main gate in real-time data processing).

• Kafka is responsible for moving data from fronting Kafka to various sinks: S3, Elasticsearch, and secondary Kafka.
• Routing of these messages is done using the Apache Samja framework.
• Traffic sent by the Chukwe can be full or filtered streams so sometimes you may have to apply further filtering on the Kafka streams.
• That is the reason we consider the router to take from one Kafka topic to a different Kafka topic.  

3.5. Elastic Search

In recent years we have seen massive growth in using Elasticsearch within Netflix. Netflix is running approximately 150 clusters of elastic search and 3, 500 hosts with instances. Netflix is using elastic search for data visualization, customer support, and for some error detection in the system.

For example:

If a customer is unable to play the video then the customer care executive will resolve this issue using elastic search. The playback team goes to the elastic search and searches for the user to know why the video is not playing on the user’s device.

They get to know all the information and events happening for that particular user. They get to know what caused the error in the video stream. Elastic search is also used by the admin to keep track of some information. It is also used to keep track of resource usage and to detect signup or login problems.  

3.6. Apache Spark For Movie Recommendation

Netflix uses Apache Spark and Machine learning for Movie recommendations. Let’s understand how it works with an example.

When you load the front page you see multiple rows of different kinds of movies. Netflix personalizes this data and decides what kind of rows or what kind of movies should be displayed to a specific user. This data is based on the user’s historical data and preferences.

Also, for that specific user, Netflix performs sorting of the movies and calculates the relevance ranking (for the recommendation) of these movies available on their platform. In Netflix, Apache Spark is used for content recommendations and personalization.

A majority of the machine learning pipelines are run on these large spark clusters. These pipelines are then used to do row selection, sorting, title relevance ranking, and artwork personalization among others. 

Video Recommendation System

If a user wants to discover some content or video on Netflix, the recommendation system of Netflix helps users to find their favorite movies or videos. To build this recommendation system Netflix has to predict the user interest and it gathers different kinds of data from the users such as:

• User interaction with the service (viewing history and how the user rated other titles)
• Other members with similar tastes and preferences.
• Metadata information from the previously watched videos for a user such as titles, genre, categories, actors, release year, etc.
• The device of the user, at what time a user is more active, and for how long a user is active.
• Netflix uses two different algorithms to build a recommendation system… 
• The idea of this filtering is that if two users have similar rating histories then they will behave similarly in the future.
• For example, consider there are two-person. One person liked the movie and rated the movie with a good score.
• Now, there is a good chance that the other person will also have a similar pattern and he/she will do the same thing that the first person has done. 
• The idea is to filter those videos which are similar to the video a user has liked before.
• Content-based filtering is highly dependent on the information from the products such as movie title, release year, actors, the genre.
• So to implement this filtering it’s important to know the information describing each item and some sort of user profile describing what the user likes is also desirable.  

4. Database Design of Netflix System Design

Netflix uses two different databases i.e. MySQL(RDBMS) and Cassandra(NoSQL) for different purposes. 

4.1. EC2 Deployed MySQL

Netflix saves data like billing information, user information, and transaction information in MySQL because it needs ACID compliance. Netflix has a master-master setup for MySQL and it is deployed on Amazon’s large EC2 instances using InnoDB. 

The setup follows the “ Synchronous replication protocol ” where if the writer happens to be the primary master node then it will be also replicated to another master node. The acknowledgment will be sent only if both the primary and remote master nodes’ write have been confirmed. This ensures the high availability of data.  Netflix has set up the read replica for each and every node (local, as well as cross-region). This ensures high availability and scalability. 

All the read queries are redirected to the read replicas and only the write queries are redirected to the master nodes.

• In the case of a primary master MySQL failure, the secondary master node will take over the primary role, and the route53 (DNS configuration) entry for the database will be changed to this new primary node.
• This will also redirect the write queries to this new primary master node.  

4.2. Cassandra

Cassandra is a NoSQL database that can handle large amounts of data and it can also handle heavy writing and reading. When Netflix started acquiring more users, the viewing history data for each member also started increasing. This increases the total number of viewing history data and it becomes challenging for Netflix to handle this massive amount of data.

Netflix scaled the storage of viewing history data-keeping two main goals in their mind:

• Smaller Storage Footprint.
• Consistent Read/Write Performance as viewing per member grows (viewing history data write-to-read ratio is about 9:1 in Cassandra).

Total Denormalized Data Model   

• Over 50 Cassandra Clusters
• Over 500 Nodes
• Over 30TB of daily backups
• The biggest cluster has 72 nodes.
• 1 cluster over 250K writes/s

Initially, the viewing history was stored in Cassandra in a single row. When the number of users started increasing on Netflix the row sizes as well as the overall data size increased. This resulted in high storage, more operational cost, and slow performance of the application. The solution to this problem was to compress the old rows.

Netflix divided the data into two parts:

• This section included the small number of recent viewing historical data of users with frequent updates. The data is frequently used for the ETL jobs and stored in uncompressed form.
• A large amount of older viewing records with rare updates is categorized in this section. The data is stored in a single column per row key, also in compressed form to reduce the storage footprint.

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How Netflix Became A Master of DevOps? An Exclusive Case Study

Find out how Netflix excelled at DevOps without even thinking about it and became a gold standard in the DevOps world.

Table of Contents

• Netflix's move to the cloud

Netflix’s Chaos Monkey and the Simian Army

Netflix’s container journey, netflix’s “operate what you build” culture, lessons we can learn from netflix’s devops strategy, how simform can help.

Even though Netflix is an entertainment company, it has left many top tech companies behind in terms of tech innovation. With its single video-streaming application, Netflix has significantly influenced the technology world with its world-class engineering efforts, culture, and product development over the years.

One such practice that Netflix is a fantastic example of is DevOps. Their DevOps culture has enabled them to innovate faster, leading to many business benefits. It also helped them achieve near-perfect uptime, push new features faster to the users, and increase their subscribers and streaming hours.

With nearly 214 million subscribers worldwide and streaming in over 190 countries , Netflix is globally the most used streaming service today. And much of this success is owed to its ability to adopt newer technologies and its DevOps culture that allows them to innovate quickly to meet consumer demands and enhance user experiences. But Netflix doesn’t think DevOps.

So how did they become the poster child of DevOps? In this case study, you’ll learn about how Netflix organically developed a DevOps culture with out-of-the-box ideas and how it benefited them.

Simform is a leading DevOps consulting and implementation company , helping businesses build innovative products that meet dynamic user demands efficiently. To grow your business with DevOps, contact us today!

Netflix’s move to the cloud

It all began with the worst outage in Netflix’s history when they faced a major database corruption in 2008 and couldn’t ship DVDs to their members for three days. At the time, Netflix had roughly 8.4 million customers and one-third of them were affected by the outage. It prompted Netflix to move to the cloud and give their infrastructure a complete makeover. Netflix chose AWS as its cloud partner and took nearly seven years to complete its cloud migration.

Netflix didn’t just forklift the systems and dump them into AWS. Instead, it chose to rewrite the entire application in the cloud to become truly cloud-native, which fundamentally changed the way the company operated. In the words of Yury Izrailevsky, Vice President, Cloud and Platform Engineering at Netflix:

“We realized that we had to move away from vertically scaled single points of failure, like relational databases in our datacenter, towards highly reliable, horizontally scalable, distributed systems in the cloud.”

As a significant part of their transformation, Netflix converted its monolithic, data center-based Java application into cloud-based Java microservices architecture. It brought about the following changes:

• Denormalized data model using NoSQL databases
• Enabled teams at Netflix to be loosely coupled
• Allowed teams to build and push changes at the speed that they were comfortable with
• Centralized release coordination
• Multi-week hardware provisioning cycles led to continuous delivery
• Engineering teams made independent decisions using self-service tools

As a result, it helped Netflix accelerate innovation and stumble upon the DevOps culture. Netflix also gained eight times as many subscribers as it had in 2008. And Netflix’s monthly streaming hours also grew a thousand times from Dec 2007 to Dec 2015.

After completing their cloud migration to AWS by 2016, Netflix had:

And it handled all of the above with 0 Network Ops Centers and some 70 operations engineers, who were all software engineers focusing on writing tools that enabled other software developers to focus on things they were good at.

Migrating to the cloud made Netflix resilient to the kind of outages it faced in 2008. But they wanted to be prepared for any unseen errors that could cause them equivalent or worse damage in the future.

Engineers at Netflix perceived that the best way to avoid failure was to fail constantly. And so they set out to make their cloud infrastructure more safe, secure, and available the DevOps way – by automating failure and continuous testing.

Chaos Monkey

Netflix created Chaos Monkey, a tool to constantly test its ability to survive unexpected outages without impacting the consumers. Chaos Monkey is a script that runs continuously in all Netflix environments, randomly killing production instances and services in the architecture. It helped developers:

• Identify weaknesses in the system
• Build automatic recovery mechanisms to deal with the weaknesses
• Test their code in unexpected failure conditions
• Build fault-tolerant systems on day to day basis

The Simian Army

After their success with Chaos Monkey, Netflix engineers wanted to test their resilience to all sorts of inevitable failures, detect abnormal conditions. So, they built the Simian Army , a virtual army of tools discussed below.

• Latency Monkey

It creates false delays in the RESTful client-server communication layers, simulating service degradation and checking if the upstream services respond correctly. Moreover, creating very large delays can simulate an entire service downtime without physically bringing it down and testing the ability to survive. The tool was particularly useful to test new services by simulating the failure of dependencies without affecting the rest of the system.

• Conformity Monkey

It looks for instances that do not adhere to the best practices and shuts them down, giving the service owner a chance to re-launch them properly.

• Doctor Monkey

It detects unhealthy instances by tapping into health checks running on each instance and also monitors other external health signs (such as CPU load). The unhealthy instances are removed from service and terminated after service owners identify the root cause of the problem.

• Janitor Monkey

It ensures the cloud environment runs without clutter and waste. It also searches for unused resources and discards them.

• Security Monkey

An extension of Conformity Monkey, it identifies security violations or vulnerabilities (e.g., improperly configured AWS security groups) and eliminates the offending instances. It also ensures the SSL (Secure Sockets Layer) and DRM (Digital Rights Management) certificates were valid and not due for renewal.

• 10-18 Monkey

Short for Localization-Internationalization, it identifies configuration and runtime issues in instances serving users in multiple geographic locations with different languages and character sets.

• Chaos Gorilla

Like Chaos Monkey, the Gorilla simulates an outage of a whole Amazon availability zone to verify if the services automatically re-balance to the functional availability zones without manual intervention or any visible impact on users.

Today, Netflix still uses Chaos Engineering and has a dedicated team for chaos experiments called the Resilience Engineering team (earlier called the Chaos team).

In a way, Simian Army incorporated DevOps principles of automation, quality assurance, and business needs prioritization. As a result, it helped Netflix develop the ability to deal with unexpected failures and minimize their impact on users. 

On 21st April 2011 , AWS experienced a large outage in the US East region, but Netflix’s streaming ran without any interruption. And on 24th December 2012 , AWS faced problems in Elastic Load Balancer(ELB) services, but Netflix didn’t experience an immediate blackout. Netflix’s website was up throughout the outage, supporting most of their services and streaming, although with higher latency on some devices.

Netflix had a cloud-native, microservices-driven VM architecture that was amazingly resilient, CI/CD enabled, and elastically scalable. It was more reliable, with no SPoFs (single points of failure) and small manageable software components. So why did they adopt container technology? The major factors that prompted Netflix’s investment in containers are:

• Container images used in local development are very similar to those run in production. This end-to-end packaging allows developers to build and test applications easily in production-like environments, reducing development overhead.
• Container images help build application-specific images easily.
• Containers are lightweight, allowing building and deploying them faster than VM infrastructure.
• Containers only have what a single application needs, are smaller and densely packed, which reduces overall infrastructure cost and footprint.
• Containers improve developer productivity, allowing them to develop, deploy, and innovate faster.

Moreover, Netflix teams had already started using containers and seen tangible benefits. But they faced some challenges such as migrating to containers without refactoring, ensuring seamless connectivity between VMs and containers, and more. As a result, Netflix designed a container management platform called Titus to meet its unique requirements.

Titus provided a scalable and reliable container execution solution to Netflix and seamlessly integrated with AWS. In addition, it enabled easy deployment of containerized batches and service applications.

Titus served as a standard deployment unit and a generic batch job scheduling system. It helped Netflix expand support to growing batch use cases. 

• Batch users could also put together sophisticated infrastructure quickly and pack larger instances across many workloads efficiently. Batch users could immediately schedule locally developed code for scaled execution on Titus.
• Beyond batch, service users benefited from Titus with simpler resource management and local test environments consistent with production deployment.
• Developers could also push new versions of applications faster than before.

Overall, Titus deployments were done in one or two minutes which took tens of minutes earlier. As a result, both batch and service users could experiment locally, test quickly and deploy with greater confidence than before.

“The theme that underlies all these improvements is developer innovation velocity.” 

-Netflix tech blog

This velocity enabled Netflix to deliver fast features to the customers, making containers extremely important for their business.

Netflix invests and experiments significantly in improving development and operations for the engineering teams. But before Netflix adopted the “Operate what you build” model, it had siloed teams. The Ops teams focused on deploy, operate and support parts of the software life cycle. And Developers handed off the code to the ops team for deployment and operation. So each stage in the SDLC was owned by a different person and looked like this:

The specialized roles created efficiencies within each segment but created inefficiencies across the entire SDLC. The issues that they faced were:

• Individual silos that slowed down end-to-end progress
• Added communication overhead, bottlenecks and hampered effectiveness of feedback loops
• Knowledge transfers between developers and ops/SREs were lossy
• Higher time-to-detect and time-to-resolve for deployment problems
• Longer gaps between code complete and deployment, with releases taking weeks

Operate what you build

To deal with the above challenges and drawing inspiration from DevOps principles, Netflix encouraged shared ownership of the full SDLC and broke down silos. The teams developing a system were responsible for operating and supporting it. Each team owned its own deployment issues, performance bugs, alerting gaps, capacity planning, partner support, and so on.

Moreover, they also introduced centralized tooling to simplify and automate dealing with common development problems of the teams. When additional tooling needs arise, the central team assesses if the needs are common across multiple development teams and built tools. In case of too team-specific problems, the development team decides if their need is important enough to solve on their own.

Full Cycle Developers

Combining the above ideas, Netflix built an even better model where dev teams are equipped with amazing productivity tools and are responsible for the entire SDLC, as shown below.

Netflix provided ongoing training and support in different forms (e.g., dev boot camps) to help new developers build up these skills. Easy-to-use tools for deployment pipelines also helped the developers, e.g., Spinnaker. It is a Continuous Delivery platform for releasing software changes with high velocity and confidence.

However, such models require a significant shift in the mindsets of teams/developers. To apply this model outside Netflix, you can start with evaluating what you need, count costs, and be mindful of bringing in the least amount of complexities necessary. And then attempt a mindset shift.

Netflix practices are unique to their work environment and needs and might not suit all organizations. But here are a few lessons to learn from their DevOps strategy and apply:

• Don’t build systems that say no to your developers

Netflix has no push schedules, push windows, or crucibles that developers must go through to push their code into production. Instead, every engineer at Netflix has full access to the production environment. And there are neither strict policies nor procedures that prevent them from accessing the production environment.

• Focus on giving freedom and responsibility to the engineers

Netflix aims to hire intelligent people and provide them with the freedom to solve problems in their own way that they see as best. So it doesn’t have to create artificial constraints and guardrails to predict what their developers need to do. But instead, hire people who can develop a balance of freedom and responsibility.

• Don’t think about uptime at all costs

Netflix servers their millions of users with a near-perfect uptime. But it didn’t think about uptime when they started chaos testing their environment to deal with unexpected failure.

• Prize the velocity of innovation

Netflix wants its engineers to do fun, exciting things and develop new features to delight its customers with reduced time-to-market.

• Eliminate a lot of processes and procedures

They limit an organization from moving fast. So instead, Netflix focuses on hiring people they can trust and have independent decision-making capabilities.

• Practice context over control

Netflix doesn’t control and contain too much. What they do focus on is context. Managers at Netflix ensure that their teams have a quality and constant flow of context of the business, rather than controlling them.

• Don’t do a lot of required standards, but focus on enablement

Teams at Netflix can work with their choice of programming languages, libraries, frameworks, or IDEs as they see best. In addition, they don’t have to go through any research or approval processes to rewrite a portion of the system.

• Don’t do silos, walls, and fences

Netflix teams know where they fit in the ecosystem, their workings with other teams, dependents, and dependencies. There are no operational fences over which developers can throw the code for production.

• Adopt “you build it, you run it” culture

Netflix focuses on making ownership easy. So it has the “operate what you build” culture but with the enablement idea that we learned about earlier.

• Focus on data

Netflix is a data-driven, decision-driven company. It doesn’t do guesses or fall victim to gut instincts and traditional thinking. It invests in algorithms and systems that combs enormous amounts of data quickly and notify when there’s an issue.

• Always put customer satisfaction first

The end goal of DevOps is to make customer-driven and focus on enhancing the user experience with every release.

• Don’t do DevOps, but focus on the culture

At Netflix, DevOps emerged as the wonderful result of their healthy culture, thinking and practices.

Get in Touch

Netflix has been a gold standard in the DevOps world for years, but copy-pasting their culture might not work for every organization. DevOps is a mindset that requires molding your processes and organizational structure to continuously improve the software quality and increase your business value. DevOps can be approached through many practices such as automation, continuous integration, delivery, deployment, continuous testing, monitoring, and more.

At Simform, our engineering teams will help you streamline the delivery and deployment pipelines with the right DevOps toolchain and skills. Our DevOps managed services will help accelerate the product life cycle, innovate faster and achieve maximum business efficiency by delivering high-quality software with reduced time-to-market.

Hiren Dhaduk

Hiren is CTO at Simform with an extensive experience in helping enterprises and startups streamline their business performance through data-driven innovation.

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10 Successful Design Thinking Case Study

Dive into the realm of Successful Design Thinking Case Studies to explore the power of this innovative problem-solving approach. Begin by understanding What is Design Thinking? and then embark on a journey through real-world success stories. Discover valuable lessons learned from these case studies and gain insights into how Design Thinking can transform your approach.

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Design Thinking has emerged as a powerful problem-solving approach that places empathy, creativity, and innovation at the forefront. However, if you are not aware of the power that this approach holds, a Design Thinking Case Study is often used to help people address the complex challenges of this approach with a human-centred perspective. It allows organisations to unlock new opportunities and drive meaningful change. Read this blog on Design Thinking Case Study to learn how it enhances organisation’s growth and gain valuable insights on creative problem-solving.

Table of Contents   

1) What is Design Thinking?

2) Design Thinking process   

3) Successful Design Thinking Case Studies

      a) Airbnb

      b) Apple

      c) Netflix

      d) UberEats

      e) IBM

       f) OralB’s electric toothbrush

      g) IDEO

      h) Tesla

       i) GE Healthcare

       j) Nike

3) Lessons learned from Design Thinking Case Studies

4) Conclusion    

What is Design Thinking ?

Before jumping on Design Thinking Case Study, let’s first understand what it is. Design Thinking is a methodology for problem-solving that prioritises the understanding and addressing of individuals' unique needs.

This human-centric approach is creative and iterative, aiming to find innovative solutions to complex challenges. At its core, Design Thinking fosters empathy, encourages collaboration, and embraces experimentation.

This process revolves around comprehending the world from the user's perspective, identifying problems through this lens, and then generating and refining solutions that cater to these specific needs. Design Thinking places great importance on creativity and out-of-the-box thinking, seeking to break away from conventional problem-solving methods.

It is not confined to the realm of design but can be applied to various domains, from business and technology to healthcare and education. By putting the user or customer at the centre of the problem-solving journey, Design Thinking helps create products, services, and experiences that are more effective, user-friendly, and aligned with the genuine needs of the people they serve.  

Design Thinking process

Design Thinking is a problem-solving and innovation framework that helps individuals and teams create user-centred solutions. This process consists of five key phases that are as follows:  

To initiate the Design Thinking process, the first step is to practice empathy. In order to create products and services that are appealing, it is essential to comprehend the users and their requirements. What are their anticipations regarding the product you are designing? What issues and difficulties are they encountering within this particular context?

During the empathise phase, you spend time observing and engaging with real users. This might involve conducting interviews and seeing how they interact with an existing product. You should pay attention to facial expressions and body language. During the empathise phase in the Design Thinking Process , it's crucial to set aside assumptions and gain first-hand insights to design with real users in mind. That's the essence of Design Thinking.

During the second stage of the Design Thinking process, the goal is to identify the user’s problem. To accomplish this, collect all your observations from the empathise phase and begin to connect the dots.

Ask yourself: What consistent patterns or themes did you notice? What recurring user needs or challenges were identified? After synthesising your findings, you must create a problem statement, also known as a Point Of View (POV) statement, which outlines the issue or challenge you aim to address. By the end of the define stage, you will be able to craft a clear problem statement that will guide you throughout the design process, forming the basis of your ideas and potential solutions.

After completing the first two stages of the Design Thinking process, which involve defining the target users and identifying the problem statement, it is now time to move on to the third stage - ideation. This stage is all about brainstorming and coming up with various ideas and solutions to solve the problem statement. Through ideation, the team can explore different perspectives and possibilities and select the best ideas to move forward with.

During the ideation phase, it is important to create an environment where everyone feels comfortable sharing their ideas without fear of judgment. This phase is all about generating a large quantity of ideas, regardless of feasibility. This is done by encouraging the team to think outside the box and explore new angles. To maximise creativity, ideation sessions are often held in unconventional locations.

It’s time to transform the ideas from stage three into physical or digital prototypes. A prototype is a miniature model of a product or feature, which can be as simple as a paper model or as complex as an interactive digital representation.

During the Prototyping Stage , the primary objective is to transform your ideas into a tangible product that can be tested by actual users. This is crucial in maintaining a user-centric approach, as it enables you to obtain feedback before proceeding to develop the entire product. By doing so, you can ensure that the final design adequately addresses the user's problem and delivers an enjoyable user experience.

During the Design Thinking process, the fifth step involves testing your prototypes by exposing them to real users and evaluating their performance. Throughout this testing phase, you can observe how your target or prospective users engage with your prototype. Additionally, you can gather valuable feedback from your users about their experiences throughout the process.

Based on the feedback received during user testing, you can go back and make improvements to the design. It is important to remember that the Design Thinking process is iterative and non-linear. After the testing phase, it may be necessary to revisit the empathise stage or conduct additional ideation sessions before creating a successful prototype.

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Successful Design Thinking Case Studies  

Now that you have a foundational understanding of Design Thinking, let's explore how some of the world's most successful companies have leveraged this methodology to drive innovation and success:

Case Study 1: Airbnb  

Airbnb’s one of the popular Design Thinking Case Studies that you can aspire from. Airbnb disrupted the traditional hotel industry by applying Design Thinking principles to create a platform that connects travellers with unique accommodations worldwide. The founders of Airbnb, Brian Chesky, Joe Gebbia, and Nathan Blecharczyk, started by identifying a problem: the cost and lack of personalisation in traditional lodging.

They conducted in-depth user research by staying in their own listings and collecting feedback from both hosts and guests. This empathetic approach allowed them to design a platform that not only met the needs of travellers but also empowered hosts to provide personalised experiences. 

Airbnb's intuitive website and mobile app interface, along with its robust review and rating system, instil trust and transparency, making users feel comfortable choosing from a vast array of properties. Furthermore, the "Experiences" feature reflects Airbnb's commitment to immersive travel, allowing users to book unique activities hosted by locals. 

Case Study 2.  Apple    

Apple Inc. has consistently been a pioneer in  Design Thinking, which is evident in its products, such as the iPhone. One of the best Design Thinking Examples from Apple is the development of the iPhone's User Interface (UI). The team at Apple identified the need for a more intuitive and user-friendly smartphone experience. They conducted extensive research and usability testing to understand user behaviours, pain points, and desires.   

The result? A revolutionary touch interface that forever changed the smartphone industry. Apple's relentless focus on the user experience, combined with iterative prototyping and user feedback, exemplifies the power of  Design Thinking in creating groundbreaking products.    

Apple invests heavily in user research to  anticipate what customers want before they even realise it themselves. This empathetic approach to design has led to groundbreaking innovations like the iPhone, iPad, and MacBook, which have redefined the entire industry.  

Case Study 3. Netflix  

Netflix, the global streaming giant, has revolutionised the way people consume entertainment content. A major part of their success can be attributed to their effective use of Design Thinking principles.

What sets Netflix apart is its commitment to understanding its audience on a profound level. Netflix recognised that its success hinged on offering a personalised, enjoyable viewing experience. Through meticulous user research, data analysis, and a culture of innovation, Netflix constantly evolves its platform. Moreover, by gathering insights on viewing habits, content preferences, and even UI, the company tailors its recommendations, search algorithms, and original content to captivate viewers worldwide.

Furthermore, Netflix's iterative approach to Design Thinking allows it to adapt quickly to shifting market dynamics. This agility proved crucial when transitioning from a DVD rental service to a streaming platform. Netflix didn't just lead this revolution; it shaped it by keeping users' desires and behaviours front and centre. Netflix's commitment to Design Thinking has resulted in a highly user-centric platform that keeps subscribers engaged and satisfied, ultimately contributing to its global success.  

Case Study 4. Uber Eats     

Uber Eats, a subsidiary of Uber, has disrupted the food delivery industry by applying Design Thinking principles to enhance user experiences and create a seamless platform for food lovers and restaurants alike.  

One of  UberEats' key innovations lies in its user-centric approach. By conducting in-depth research and understanding the pain points of both consumers and restaurant partners, they crafted a solution that addresses real-world challenges. The user-friendly app offers a wide variety of cuisines, personalised recommendations, and real-time tracking, catering to the diverse preferences of customers.  

Moreover,  UberEats leverages technology and data-driven insights to optimise delivery routes and times, ensuring that hot and fresh food reaches customers promptly. The platform also empowers restaurant owners with tools to efficiently manage orders, track performance, and expand their customer base. 

Case Study  5 . IBM    

IBM is a prime example of a large corporation successfully adopting Design Thinking to drive innovation and transform its business. Historically known for its hardware and software innovations, IBM recognised the need to evolve its approach to remain competitive in the fast-paced technology landscape.   

IBM's Design Thinking journey began with a mission to reinvent its enterprise software solutions. The company transitioned from a product-centric focus to a user-centric one. Instead of solely relying on technical specifications, IBM started by empathising with its customers. They started to understand customer’s pain points, and envisioning solutions that genuinely addressed their needs. 

One of the key elements of IBM's Design Thinking success is its multidisciplinary teams. The company brought together designers, engineers, marketers, and end-users to collaborate throughout the product development cycle. This cross-functional approach encouraged diverse perspectives, fostering creativity and innovation. 

IBM's commitment to Design Thinking is evident in its flagship projects such as Watson, a cognitive computing system, and IBM Design Studios, where Design Thinking principles are deeply embedded into the company's culture. 

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Case Study 6. Oral-B’s electric toothbrush

Oral-B, a prominent brand under the Procter & Gamble umbrella, stands out as a remarkable example of how Design Thinking can be executed in a seemingly everyday product—Electric toothbrushes. By applying the Design Thinking approach, Oral-B has transformed the world of oral hygiene with its electric toothbrushes.  

Oral-B's journey with Design Thinking began by placing the user firmly at the centre of their Product Development process. Through extensive research and user feedback, the company gained invaluable insights into oral care habits, preferences, and pain points. This user-centric approach guided Oral-B in designing electric toothbrushes that not only cleaned teeth more effectively but also made the entire oral care routine more engaging and enjoyable.  

Another of Oral-B's crucial innovations is the integration of innovative technology into their toothbrushes. These devices now come equipped with features like real-time feedback, brushing timers, and even Bluetooth connectivity to sync with mobile apps. By embracing technology and user-centric design, Oral-B effectively transformed the act of brushing teeth into an interactive and informative experience. This has helped users maintain better oral hygiene.  

Oral-B's success story showcases how Design Thinking, combined with a deep understanding of user needs, can lead to significant advancements, ultimately improving both the product and user satisfaction.

Case Study 7. IDEO  

IDEO, a Global Design Consultancy, has been at the forefront of Design Thinking for decades. They have worked on diverse projects, from creating innovative medical devices to redesigning public services.

One of their most notable Design Thinking examples is the development of the "DeepDive" shopping cart for a major retailer. IDEO's team spent weeks observing shoppers, talking to store employees, and prototyping various cart designs. The result was a cart that not only improved the shopping experience but also increased sales. IDEO's human-centred approach, emphasis on empathy, and rapid prototyping techniques demonstrate how Design Thinking can drive innovation and solve real-world problems.   

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Case Study  8 .  Tesla  

Tesla, led by Elon Musk, has redefined the automotive industry by applying Design Thinking to Electric Vehicles (EVs). Musk and his team identified the need for EVs to be not just eco-friendly but also desirable. They focused on designing EVs that are stylish, high-performing, and technologically advanced. Tesla's iterative approach, rapid prototyping, and constant refinement have resulted in groundbreaking EVs like the Model S, Model 3, and Model X.    

From the minimalist interior of their Model S to the autopilot self-driving system, every aspect is meticulously crafted with the end user in mind. The company actively seeks feedback from its user community, often implementing software updates based on customer suggestions. This iterative approach ensures that Tesla vehicles continually evolve to meet and exceed customer expectations .   

Moreover, Tesla's bold vision extends to sustainable energy solutions, exemplified by products like the Powerwall and solar roof tiles. These innovations  showcase Tesla's holistic approach to Design Thinking, addressing not only the automotive industry's challenges but also contributing to a greener, more sustainable future.   

Case Study 9. GE Healthcare 

GE Healthcare is a prominent player in the Healthcare industry, renowned for its relentless commitment to innovation and design excellence. Leveraging Design Thinking principles, GE Healthcare has consistently pushed the boundaries of medical technology, making a significant impact on patient care worldwide.  

One of the key areas where GE Healthcare has excelled is in the development of cutting-edge medical devices and diagnostic solutions. Their dedication to user-centred design has resulted in devices that are not only highly functional but also incredibly intuitive for healthcare professionals to operate. For example, their advanced Medical Imaging equipment, such as MRI and CT scanners, are designed with a focus on patient comfort, safety, and accurate diagnostics. This device reflects the company's dedication to improving healthcare outcomes.  

Moreover, GE Healthcare's commitment to design extends beyond the physical product. They have also ventured into software solutions that facilitate data analysis and Patient Management. Their user-friendly software interfaces and data visualisation tools have empowered healthcare providers to make more informed decisions, enhancing overall patient care and treatment planning.

Case Study 10. Nike 

Nike is a global powerhouse in the athletic apparel and Footwear industry. Nike's journey began with a simple running shoe, but its design-thinking approach transformed it into an iconic brand.

Nike's Design Thinking journey started with a deep understanding of athletes' needs and desires. They engaged in extensive user research, often collaborating with top athletes to gain insights that inform their product innovations. This customer-centric approach allowed Nike to develop ground breaking technologies, such as Nike Air and Flyknit, setting new standards in comfort, performance, and style.

Beyond product innovation, Nike's brand identity itself is a testament to Design Thinking. The iconic Swoosh logo, created by Graphic Designer Carolyn Davidson, epitomises simplicity and timelessness, reflecting the brand's ethos.  

Nike also excels in creating immersive retail experiences, using Design Thinking to craft spaces that engage and inspire customers. Their flagship stores around the world are showcases of innovative design, enhancing the overall brand perception.

Lessons learned from Design Thinking Case Studies

The Design Thinking process, as exemplified by the success stories of IBM, Netflix, Apple, and Nike, offers valuable takeaways for businesses of all sizes and industries. Here are three key lessons to learn from these Case Studies:  

1)   Consider the b ig p icture   

Design Thinking encourages organisations to zoom out and view the big picture. It's not just about solving a specific problem but understanding how that problem fits into the broader context of user needs and market dynamics. By taking a holistic approach, you can identify opportunities for innovation that extend beyond immediate challenges. IBM's example, for instance, involved a comprehensive evaluation of their clients' journeys, leading to more impactful solutions.  

2)  Think t hrough a lternative s olutions   

One of the basic principles of Design Thinking is ideation, which emphasises generating a wide range of creative solutions. Netflix's success in content recommendation, for instance, came from exploring multiple strategies to enhance user experience. When brainstorming ideas and solutions, don't limit yourself to the obvious choices. Encourage diverse perspectives and consider unconventional approaches that may lead to breakthrough innovations.  

3)  Research e ach c ompany’s c ompetitors   

Lastly, researching competitors is essential for staying competitive. Analyse what other companies in your industry are doing, both inside and outside the realm of Design Thinking. Learn from their successes and failures. GE Healthcare, for example, leveraged Design Thinking to improve medical equipment usability, giving them a competitive edge. By researching competitors, you can gain insights that inform your own Design Thinking initiatives and help you stand out in the market.  

Incorporating these takeaways into your approach to Design Thinking can enhance your problem-solving capabilities, foster innovation, and ultimately lead to more successful results.  

Conclusion    

Design Thinking is not limited to a specific industry or problem domain; it is a versatile approach that promotes innovation and problem-solving in various contexts. In this blog, we've examined successful Design Thinking Case Studies from industry giants like IBM, Netflix, Apple, Airbnb, Uber Eats, and Nike. These companies have demonstrated that Design Thinking is a powerful methodology that can drive innovation, enhance user experiences, and lead to exceptional business success.   

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Frequently Asked Questions

Design Thinking Case Studies align with current market demands and user expectations by showcasing practical applications of user-centric problem-solving. These Studies highlight the success of empathetic approaches in meeting evolving customer needs.

By analysing various real-world examples, businesses can derive vital insights into dynamic market trends, creating innovative solutions, and enhancing user experiences. Design Thinking's emphasis on iterative prototyping and collaboration resonates with the contemporary demand for agility and adaptability.

Real-world examples of successful Design Thinking implementations can be found in various sources. For instance, you can explore several Case Study repositories on Design Thinking platforms like IDEO and Design Thinking Institute. Furthermore, you can also look for business publications, such as the Harvard Business Review as well as Fast Company, which often feature articles on successful Design Thinking applications.

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Customer Case Study: SimCorp’s AI Journey with Semantic Kernel

Sophia Lagerkrans-Pandey

July 24th, 2024 0 0

We’re excited to feature the SimCorp team on the Semantic Kernel blog today. The SimCorp team will discuss their AI journey and how they’ve integrated Semantic Kernel to build out their AI solutions. Let’s dive into the details from the SimCorp team!

SimCorp Background:

SimCorp was founded in 1971 and has continuously innovated to create an industry-leading integrated investment management platform that’s built to turn avalanches of information into insights that lead to the decisions that put our clients ahead of the competition. SimCorp’s efficient, flexible front-to-back-offering, provides clients with SaaS (Software as a Service) platform or on-premise solutions.

Some details about SimCorp since their founding:

SimCorp’s Key Objective:

SimCorp’s AI Strategy and Semantic Kernel Integration 

SimCorp’s AI Platform: SimCorp is using Azure Machine Learning by Microsoft as their main AI platform. Currently, SimCorp supports all AI models on the Azure platform.

SimCorp’s Partnership with Microsoft Semantic Kernel: SimCorp is using Semantic Kernel to implement its vision due to its ease of use to integrate in their solutions. SimCorp is actively working with Microsoft on SimCorp’s AI roadmap.

The below interview details the value Semantic Kernel has provided SimCorp and its ease of use.

SimCorp Copilot:

One of the key things SimCorp is using Semantic Kernel for is their AI solution called SimCorp Copilot. SimCorp Copilot has more capabilities than a chatbot and is able to understand the context it’s in and then helps you do your job. Ideally the goal is SimCorp Copilot will know what you are trying to do and be able to pull in relevant data, while keeping data security, reliability and responsible AI top of mind. Below you can see details into the architecture of the solution and learn more in a brief video from SimCorp.

https://learn.microsoft.com/video/media/9908a928-7d21-4215-8287-f51338aa8da8/Media7_1721154933611_640x360_AACAudio_484.mp4

SimCorp’s Wealth Vision AI Solution:

SimCorp has developed a solution called Wealth Vision where you, as a portfolio manager, are provided with a list of portfolios to rebalance. The solution provides the individual with a tool called Wealth Lens which gives a score between 0.00 and 1.00 for each portfolio. A portfolio with a value of 1.00 is a prime candidate to be rebalanced, while a portfolio with a score of 0.00 does not need rebalancing.

https://learn.microsoft.com/video/media/a6c67f8c-b1e1-40f5-a8d9-8f480ed2c2ba/Media10%20slide%2011_1721348530450_640x360_AACAudio_475.mp4

Demo | Digital Engagement Platform

The demo below showcases SimCorp’s digital engagement platform which provides an individual with information requested through retrieval augmented generation (RAG) by scanning documents.

https://learn.microsoft.com/video/media/b16266a6-958c-4ad9-8c35-30d40391d5fc/media_1721415256234_1920x1080_AACAudio_621.mp4

https://learn.microsoft.com/video/media/86578a51-0470-4bbe-8f13-1c23774f95b7/Media11%20slide%2012_1721351740249_640x360_AACAudio_447.mp4

Conclusion:

From the Semantic Kernel team, we want to thank the entire SimCorp team for their time. We’re always interested in hearing from you. If you have feedback, questions or want to discuss further, feel free to reach out to us and the community on the Semantic Kernel GitHub Discussion Channel ! We would also love your support, if you’ve enjoyed using Semantic Kernel, give us a star on  GitHub .

Thanks again to the SimCorp team for their amazing work and partnership!

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More From Forbes

The wild true story behind netflix’s ‘dirty pop: the boy band scam’ and lou pearlman’s ponzi scheme.

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Lou Pearlman and the Backstreet Boys

Netflix’s Dirty Pop: The Boy Band Scam tells the mind-blowing true story of Lou Pearlman, a con artist who catapulted several major boy bands to fame in the Y2K era, only to be later convicted of orchestrating a fraudulent empire and swindling investors out of hundreds of millions of dollars.

The three-part limited series centers on Lou Pearlman, the blimp rental executive turned talent manager who created the Backstreet Boys and managed pop stars like *NSYNC, Aaron Carter, Take 5, O-Town, Brooke Hogan, and more. At the same time, he built a massive Ponzi scheme and engaged in fraudulent activities, including conspiracy and money laundering.

The docuseries explores Pearlman’s rise as a music manager and entertainment mogul before his fall from grace when his financial scheme and empire collapsed. There’s also interviews with the artists he formerly managed, including Backstreet Boys’ AJ McLean and Howie Dorough and *NSYNC’s Chris Kirkpatrick, Natural’s Michael Johnson, and Patrick King.

Uncover the details of the high-profile scandal that rocked the entertainment industry in the 1990s and 2000s, including what charges were brought against Pearlman and where the disgraced music executive is now.

Who Was Lou Pearlman?

Lou Pearlman featured in "Dirty Pop: The Boy Band Scam."

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Lou Pearlman was born and raised in New York City. Growing up, he was fascinated with blimps and aviation. In the ’70s, he founded a helicopter taxi service in New York City before moving into blimp leasing. His business, Airship International, started sourly after its only blimp crashed in New Jersey shortly after takeoff in 1980.

Five years later, in 1985, a public offering for Airship International raised $3 million in a widely suspected “pump and dump” scheme, according to Billboard . He eventually created a private air charter company, Trans Continental Airlines, which flew musicians worldwide — which is how he met New Kids on the Block. Pearlman wanted to get involved after the band’s manager told him that New Kids was grossing $100 million a year, according to Vanity Fair .

“I just didn’t know who they were and I was just questioning, ‘How could these kids afford an airplane?’” Pearlman told ABC News in 2000. “I was told these kids did $200 million in record sales and $800 million in touring and merchandising. I was like, ‘I’m in the wrong business.’”

In 1992, Pearlman officially entered the music business when he placed an advertisement in the Orlando Sentinel to create a group with a “New Kids on the Block look with a Boyz II Men Sound.” As a result, the Backstreet Boys were born.

While the boy group was not an overnight hit, he poured millions into the band as Airship International suffered significant losses, including a $2 million loss in 1992 and a $4 million loss in early 1994, according to Vanity Fair . Of its five blimps, only one was still flying in late 1994. His last blimp expired in 1995.

A much-needed breakthrough came when Backstreet Boys achieved their first big U.S. hit with 1997’s “Quit Playing Games (With My Heart), which sold 2 million copies that year. The rising music mogul decided to apply a similar formula to *NSYNC, eventually growing his fraudulent Trans Continental entertainment empire by signing acts like O-Town, LFO, Aaron Carter, Jordan Knight, Take 5, and more.

The Lawsuits Against Lou Pearlman: What Happened With His Bands?

MIAMI - JUNE 06: Lou Pearlman poses with N'Sync Chris Kirkpatrick, JC Chasez, Lance Bass, Joey ... [+] Fatone and Justin Timberlake seen at N.Y.P.D. pizza in Miami, circa 1996. (Photo by Mark Weiss/WireImage)

In the 1990s, Pearlman was hit with multiple lawsuits for misrepresentation and fraud from the musical acts he managed. In 1998, the Backstreet Boys filed a lawsuit that they had only received $300,000 since 1993, while Pearlman made $10 million. Pearlman also made himself the sixth Backstreet Boys and *NSYNC member without their knowledge.

He was ousted as the manager of the Backstreet Boys and, eventually, *NSYNC when the latter also settled in 1999, giving *NSYNC members the right to control their names.

But the lawsuits didn’t stop Pearlman, because he then created a boy band called LFO, as well as bands like C- Note, Take 5, the girl group Innosense, and O-Town, who won his TV show “Making the Band,” which started on ABC in 2000 and moved to MTV in 2001.

In addition to facing legal issues with artists, Pearlman was also sued by Cheney Mason, the defense lawyer he’d hired to represent him in the Backstreet Boys and *NSYNC cases. He was ordered to pay his ex-lawyers $15 million.

What Was Lou Pearlman Accused Of And Charged With?

NEW YORK - MARCH 6: Record impresario Lou Perlman and singer Aaron Carter attend the 6th Annual ... [+] T.J. Martell 'Family' Day' Indoor Carnival Benefit at Cipriani's Fifth Avenue March 6, 2005 in New York City. (Photo by Evan Agostini/Getty Images)

Pearlman was accused of using the success of his boy bands to lure private investors (which included artists, friends, and business partners) to invest in his other businesses, which he claimed were housed under his corporation, TransContinental. He said the empire included an airline, a film and music studio, talent, travel agencies, restaurants, and real estate.

According to ABC News , he also launched an investment scheme for investors, an “FDIC-insured” savings program with Trans Continental Airlines Inc. and Trans Continental Airlines Travel Services Inc., which didn’t exist in real life.

“One of the first things they do is, ‘Welcome to TransCon. Here’s our card. Here’s all the companies we own,’ and you’re looking at this card that folds, a business card that folds with like 40, 50 companies that he owns,” said Jacob Underwood, a member of O-Town, to ABC News . “Right away, you’re like, ‘Whoa, I mean, I am in with somebody really important, and this is a big deal. If he owns all these things, then he must really understand business and get it.’”

Investigators unraveled Pearlman’s long-running Ponzi scheme in 2006 and discovered that he had defrauded investors of at least $300 million. In 2007, he was charged with conspiracy, money laundering, and making false claims in a bankruptcy. Pearlman was convicted and sentenced to 25 years in federal prison.

Where Is Lou Pearlman Now?

Lou Pearlman (Photo by Johnny Nunez/WireImage)

Lonou Pearlman died in federal prison in 2016 at the age of 62. He suffered a stroke in 2010 that deteriorated his health. Pearlman’s cause of death was an infection following surgery to get a heart valve replaced, the Miami-Dade Medical Examiner reported at the time.

“I hope he found some peace,” Justin Timberlake wrote on X (formerly Twitter) after learning of his former manager’s death. “God bless and RIP, Lou Pearlman.”

Fellow *NSYNC members Chris Kirkpatrick and Lance Bass also commented on Pearlman’s death on social media at the time.

“Mixed emotions right now, but RIP Lou Pearlman,” Kirkpatrick wrote . “Word is that #LouPearlman has passed away,” Bass tweeted. “He might not have been a stand up businessman, but I wouldn’t be doing what I love today wout his influence. RIP Lou.”

As of 2024, more than $400 million in Pearlman’s Ponzi scheme remains unrecovered, according to Netflix .

Watch the official trailer for Dirty Pop: The Boy Band Scam.

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Characteristics and driving mechanisms of coastal wind speed during the typhoon season: a case study of typhoon lekima.

1. Introduction

2. methodology, 2.1. beast method for mutation detection, 2.2. hurst stationarity analysis of time series, 3. overview of typhoon likima and its data sources, 3.1. overview of typhoon lekima, 3.2. data source, 4.1. characteristics of wind speed change of measuring tower during typhoon influence phase, 4.1.1. breakpoint analysis of wind speed sequence of measuring tower during typhoon influence phase, 4.1.2. analysis of series trend of wind speed of measuring tower during typhoon influence stage, 4.2. hurst index analysis, 4.3. analysis of wind direction change characteristics, 4.4. relationship between wind speed variation characteristics and paths at 10 m and 70 m, 4.5. influence of the cushion on the wind speed of the tower, 4.6. influence of mesoscale system on wind speed of measuring tower before and after typhoon, 5. discussion, 5.1. comparison of beast method with mk and bfast, 5.2. analysis of the influence of typhoon on wind farms and its measures, 5.3. deficiencies and prospects, 6. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Wang, L.; Fu, A.; Bashir, B.; Gu, J.; Sheng, H.; Deng, L.; Deng, W.; Alsafadi, K. Characteristics and Driving Mechanisms of Coastal Wind Speed during the Typhoon Season: A Case Study of Typhoon Lekima. Atmosphere 2024 , 15 , 880. https://doi.org/10.3390/atmos15080880

Wang L, Fu A, Bashir B, Gu J, Sheng H, Deng L, Deng W, Alsafadi K. Characteristics and Driving Mechanisms of Coastal Wind Speed during the Typhoon Season: A Case Study of Typhoon Lekima. Atmosphere . 2024; 15(8):880. https://doi.org/10.3390/atmos15080880

Wang, Lingzi, Aodi Fu, Bashar Bashir, Jinjun Gu, Haibo Sheng, Liyuan Deng, Weisi Deng, and Karam Alsafadi. 2024. "Characteristics and Driving Mechanisms of Coastal Wind Speed during the Typhoon Season: A Case Study of Typhoon Lekima" Atmosphere 15, no. 8: 880. https://doi.org/10.3390/atmos15080880

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