Switching costs are another aspect of a startup’s business model that I pay attention to. Together with Network Effect, Intangibles, Cost Advantages, and Efficient Scale they form the source of economic moats.¹ In this post I will discuss switching costs; what they are, how they develop and evolve, and how switching costs can help or hurt a startup.

To ensure we are on the same page, I will start with some definitions. In the rest of this discussion I am primarily focused on early stage technology startups. Also, the customer I have in mind is one whose present known needs are adequately served by the current product. Finally, I assume government intervention is not a significant factor.

Definition #1: What is a startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model.²

Definition #2: What is an economic moat? An economic moat is a structural barrier that protects a company from competition.³

Definition #3: What are switching costs? Switching costs refer to the expense in cash, time, convenience, risk, and process disruption that a customer of one product or service must incur if they change from one product from an incumbent Producer A to another product from Producer B. Switching costs can be explicit or implicit, and confer the benefit of customer lock-in to incumbent suppliers if the customer perceives the cost of switching to outweigh the benefits that would be obtained by making the switch.⁴

How do switching costs develop? 

Switching costs develop and become stronger when an incumbent product becomes “mission-critical” for the purpose for which the customer acquired the product in the first place. An incumbent that combines network effects with high switching costs in the same product line is well positioned to build a durable moat around its business. Economists describe at least three main assumptions about switching costs. Exogenous switching costs are believed to evolve without any intentional influence from the incumbent producer – for example; customers independently create or enhance switching costs by becoming more skilled and experienced in applying and adapting the incumbent product towards solving a wider variety of problems than the producer had originally envisioned. Endogenous switching costs evolve through deliberate actions by the incumbent – for example; volume discounts to encourage wide adoption within a company of a new software product, coupled with long-lived license agreements and punitive charges if the license is terminated between license renewal dates. Also, deeply entrenched incumbents will typically opt for incompatibility with competing products while new entrants will prefer to build in compatibility with the incumbent product that they seek to displace. Lastly, switching costs are symmetrical between all the producers competing within a given market.⁵

What are the types of switching costs that lead to buyer lock-in? 

One might consider switching costs to exist along a continuum that is characterised most distinctly by how intertwined each of the categories identified by economists is tightly intertwined with nearly every other category below.⁶

Compatibility Requirements make it difficult and expensive to switch between products. Consider an individual or organization running MS Windows contemplating a decision to switch to Linux. The implications of this choice are generally non-trivial. Compatibility requirements are largely an implicit cost that is borne by the customer.

Transaction Costs impose an explicit cost on customers who decide to switch from one product to another. For example, cable-tv subscription agreements typically impose a high penalty on subscribers who decide to terminate their agreement before it has run its full course. Any cost than can be measured explicitly and that has to be considered in switching between products falls under this category.

Cognitive Costs are the perceived hurdles customers feel they will have to overcome when they switch from one product to another. One example is the dichotomy between people who prefer Mac OS and those who prefer MS Windows. I understand the practical reasons one might have for preferring one operating system over the other; for example, one platform is more compatible with a wider variety of products in a certain category of software applications than the other. What often surprises me is the speed with which conversations between those two groups quickly devolve past anything one might consider rational, logical or practical to become an exercise in name-calling and ad-hominem attacks. Such episodes suggest that in some situations there are significant psychological issues at play that have nothing to do with the reality one might face if one tried to switch products.⁷

Uncertainty is the apprehension that the customer has to face regarding the quality of the new product. Uncertainty is minimized only if the customer believes that, at a minimum, the new product will match the old product in quality. As an example, consider a small business that is trying to decide if it should migrate from MS Exchange Server to Google Apps for Business at a time when its license for the former is up for renewal. Uncertainty works in favor of the incumbent product when customers have very little information about the relative performance characteristics of the new product.⁸

Learning Costs are the known hurdles that a customer must overcome in order to attain mastery of the new product that is at par with that customer’s mastery of the incumbent product required to accomplish the tasks the customer needs to complete. Learning costs need to be considered on their own, independent of other categories of switching costs. High learning costs tied to adopting a new product increase switching costs in favor of the incumbent. Minimal learning costs tied to the adoption of a new product lower switching costs in favor of the new product. On one hand, an individual customer might be willing to face high learning costs in situations where the consequence if things go wrong is non-fatal; for example switching from one messaging app to another. On the other hand, enterprise or small business customers who face loss of business and revenue if things go wrong will exhibit high levels of inertia in the face of high learning costs; for example switching from one company-wide CRM system to another.

Lost-Benefit Costs are costs suffered by the customer because certain benefits that have been earned but not yet consumed by the customer as a result of its historical relationship with the incumbent are non-transferrable in nature – the customer who decides to make a switch suffers a significant loss and must start to earn such benefits from scratch with the new provider. An example of this is found in the various loyalty programs that are used to induce customers from switching from one product to another; airline travel points, for instance. Mobile phone subscription roll-over minutes are another example – my roll-over minutes accumulated on AT&T’s cell phone network are not transferrable to another carrier if I choose to switch.⁹

How might switching costs become a disadvantage? 

Switching costs lock in customers who face the highest opportunity costs of switching from an incumbent product to another product offered by a rival. It is often the case that these customers comprise the most profitable segment of customers for the incumbent, and it is not uncommon for the incumbent to continue optimizing the product to meet their requirements, with each improvement in the incumbent product being reflected in an across-the-board increase in prices for all the incumbent producer’s customers. This iterative cycle of feature upgrades and attendant price increases will continue until it gets to a point at which the following things happen; first the product becomes too advanced for a large number of customers with “only moderate” needs and therefore, commensurately moderate switching costs. Second, at this point the medium- to long-term cost of switching is perceived by this group of customers to be less than the commensurate benefit of remaining locked into the incumbent product. Last, the rival product has matured such that it satisfactorily meets the needs of customers considered to be low-margin customers based on the business model implemented by the incumbent producer. However, these same customers comprise an attractive, high-margin customer cohort for the rival product because the rival producer is pursuing a business model that features significantly lower overhead costs than the comparable costs reflected in the incumbent’s existing business model.¹⁰

As a result the incumbent producer faces a dilemma; stay and fight for low-margin customers, or cede that ground to the rival product? The most typical response from incumbents is to cede the unprofitable customers to the rival. This gives the rival a toe-hold in the market, a position from which the rival can gradually strengthen its position and eventually migrate upstream until it poses a direct and powerful threat to the incumbent. The effect high customer switching costs have on an incumbent producer is that they lock the incumbent into a pattern of sustaining innovation. Sustaining innovation improves on already existing products, and focuses on squeezing more out of a large base of existing and and a comparatively small base of new customers. An example of sustaining innovation is Microsoft’s line of Windows and Office products; annual sales to new customers is small compared to sales generated from the installed base of Windows and Office users. Disruptive innovation seeks to satisfy non-consumption by developing products with features so simple and inexpensive in comparison to the status quo that a disproportionately large number of new customers enter the market.¹¹ The key is that the customers that flock to the disruptive product are very unattractive to established incumbents. With time, the disruptive innovation matures to the extent that it becomes a viable substitute for the incumbent’s most profitable customers at a price point that is extremely hard for them to resist. It is at this tipping point that the incumbent’s fight for its survival begins. It is easy to dismiss disruptive innovations at the outset because the performance measurements that have become customary for the market in question do not apply in the same way for the new wave of consumption that the disruptive innovation enables. For example, consider an investor trying to decide if an investment in Facebook was a good idea in 2006. On the basis of CPMs this investor would probably have decided to pass on the opportunity to invest in Facebook, reasoning that it did not have the qualities necessary to build a highly valuable business. Except, CPMs were the wrong metric by which to judge Facebook at that point.¹²

What are the competitive strategies at play in markets in which switching costs matter. 

It is important for technology startups and early stage technology startups to understand the dynamic that might evolve as they seek entry into a market characterized by an incumbent who benefits from customer lock-in. Fortunately, substantial economic research exists on that topic.¹³

The incumbent sells to existing customers, rival new-entrant serves new buyers. This happens in markets that are relatively mature. The incumbent focuses its efforts on its existing customer base, with growth in revenues arising from endogenous growth within that customer base – e.g. Bloomberg revenues increasing because the average number of employees of each of its existing customers is increasing with time. New entrants meanwhile utilize new technology to serve new customers, initially ignoring the incumbents existing customer base. This is especially true in markets in which the incumbent producer has a high level of power relative to customers in that market – typified by dominant market share, giving it pricing power over its existing customer base. To use the parlance of Farrell and Shapiro (1998) the incumbent sells to the oldsters while the entrant sells to the youngsters.¹⁴

The incumbent excludes the new entrant. This happens when the incumbent’s fixed costs per customer are greater than the switching costs per customer. The strategy works under conditions in which the incumbent is in a position to set a price that makes it unattractive for any new entrant to enter the market. Where this is not possible the incumbent will choose to set a price that allows the market to be shared between the incumbent and the new entrant. This is why freemium business models are so powerful, especially when a freemium business model is coupled with a product that embodies network effects and switching costs. For example, think about how dominant Facebook has become because it gives its product away to users for free. Clearly, it not possible to compete with Facebook on the basis of the price users pay in exchange for the value they derive from it. The startups that will ultimately compete with Facebook do not have a cost-leadership strategy available to them, and so must instead seek an alternate path.¹⁵

New customers are won with bargains, then they are “ripped off”. This happens when customers are offered low “introductory offers” in order to entice them to adopt a product. Prices increase once lock-in has been established. As an example, consider a product that is free up to a certain usage threshold but for which continued use beyond the set threshold requires customers to pay. In this scenario, various mechanisms might be used to ensure the onset of customer lock-in, and improvements in the product’s features and capabilities are designed to nudge users over the threshold beyond which they have to become paying customers.¹⁶ This tactic is common among cable TV and satellite TV providers, and also among internet service providers.

Customers are paid to switch. Consider three segments of an incumbent producer’s customers; Existing locked-in customers, unattached or new customers, and customers locked into a rival. In this situation, rival producers will implement price discrimination. Existing locked-in customers get one set of prices, new or unattached customers get another set of prices, while customers locked into rivals are paid to switch.¹⁷ Recent reports of the battle for market share between Uber and Lyft are a great example of this tactic being applied in the real world.¹⁸ This tactic is common with cellular phone service providers and credit card issuers.

A portfolio of products is bundled together in order to increase total switching costs. This tactic is especially effective because in order to make a switch, the customer must deal with nearly all the switching costs we have previously considered at the same time and it works especially when the incumbent producer offers a product line that is so broad that most customers simply deal with the incumbent as their single supplier for the entire line of products that they use.¹⁹ For example, Microsoft’s strategy of giving away Internet Explorer in a bundle with Microsoft Windows reportedly led to the demise of Netscape Navigator. I would guess that beyond merely bundling Explorer with Windows, Microsoft built-in a number of features that made Navigator less compatible with the Windows operating system than Explorer.²⁰

Switching costs play an important role in retaining customers, and motivating repeat purchases in the future. Technology startups can’t survive without user lock-in and incumbent suppliers with strong customer lock-in typically earn monopoly profits. Early stage startups thinking about spend some time understanding the features that create value for the customer while building customer lock-in for the startup early in product design process. The existence, or lack thereof, of switching costs amongst the incumbent’s customers will play an important role in determining the competitive response that is likely to occur once the new-entrant’s intentions become undeniable. In which case speed of market entry is critical for the new-entrant. In a market with low switching costs, one might expect vicious price wars to ensue. Generally, such price wars will always favor the presumably better capitalised incumbent. Moreover, price wars are a bad idea for the incumbent as well as the new entrants. In a market where the incumbent enjoys significant customer lock-in with ensuing monopoly profits, one generally expects new entrants to find a foothold from which they can eventually migrate up-market.

1. Any errors in appropriately citing my sources are entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained them. ?
2. I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports. ?
3. Heather Brilliant, Elizabeth Collins, et al. Why Moats Matter: The Morningstar Approach to Stock Investing. Wiley. Hoboken, NJ. 2014; p. 1 ?
4. In economics switching costs are defined as the disutility that a customer experiences in switching between products. ?
5. Pei-yu Chen and Lorin M. Hitt. Information Technology and Switching Costs. September 2005; p.9. Accessed online on Oct. 19, 2014. ?
6. The following discussion is based largely on; Paul Klemperer. Competition When Consumers Have Switching Costs: An Overview With Applications to Industrial Organization, Macroeconomics, and International Trade. Review of Economic Studies, 1995; p. 515 – 539. Accessed online on Oct. 19, 2014. ?
7. Klemperer calls these psychological costs. ?
8. Ibid. Pei-yu Chen and Lorin M. Hitt. p. 4. ?
9. Klemperer calls these discount coupons and other devices. ?
10. This is the process described by Clayton Christensen in The Innovator’s Dilemma. ?
11. Or, a large number of “unprofitable customers” abandon the incumbent product for the new, disruptive product. ?
12. Read: Andrew Chen. Why I Doubted Facebook Could Build A Billion Dollar Business, and What I learned From Being Horribly Wrong. Accessed online on Oct. 19, 2014. ?
13. Joseph Farrell, Carl Shapiro. Dynamic Competition With Switching Costs. RAND Journal of Economics; Vol. 19, No. 1, Spring 1988. and Joseph Farrell, Paul Klemperer. Coordination and Lock-in: Competition With Switching Costs and Network Effects; Handbook of Industrial Organization, Volume 3. Ed. M. Armstrong, R. Porter. Copyright 2007, Elsevier B.V. Accessed online on Oct. 23, 2014. ?
14. See for example; Aaron Timms. The Race To Topple Bloomberg; Institutional Investor, Jan. 30, 2014 and Startups Estimize and Kensho Take Aim at Bloomberg; Institutional Investor, Jan. 30, 2014. ?
15. Examples; Whatsapp, Instagram, Pinterest, Snapchat, Line, Kik etc. Most recently Ello has tried to carve a niche for itself by emphasizing privacy. It is too early to tell if that tactic will work. ?
16. Examples; Google Apps for Business, now renamed Google Apps for Work started used this tactic to build a beach-head in a market dominated by Microsoft. This scenario excludes predatory pricing practices. ?
17. Ibid; Farrell and Klemperer. ?
18. See for example; Alison Grisworld, Uber Rival Gett is Making a Risky, Clever Play in The Ride-Sharing Game, Oct 15, 2014. and Avi Asher-Schapiro, Is Uber’s Business Model Screwing Its Workers?, Oct 1, 2014. ?
19. Ibid; Farrell and Klemperer. ?
20. Wikipedia; United States v. Microsoft Corp. Accessed online, Oct 23rd, 2014. ?

Started From the Bottom Now They’re Here: Why Startups Are Racing to Build Operations Teams http://t.co/o2kMPA966I [new blog post]

— Hunter Walk (@hunterwalk) August 8, 2014

Hunter Walk’s blog post serves as the inspiration for this one. He points out that operations is key for startups operating in the on-demand economy. I want to pick up where he left off, and attempt to connect the dots. This post will answer the question “Why is operations important for tech startups?”

All else equal, and I know that is rarely true, operations marks the difference between an unsustainable competitive advantage and a sustainable competitive advantage.¹ In order to understand the role of operations in determining the success or failure of a startup we must start with some definitions.

Definition #1: What is a startup? When I think of a startup I prefer to paraphrase the definition provided by Steve Blank and Bob Dorf in their book The Startup Owner’s Manual; A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model. The defining characteristic of a startup is that of experimentation – to have a chance at survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model.

Definition #3: What is strategy? According to Fred Nickols, strategy is the accumulation of perspectives, positions, plans, patterns, tactics, choices, policies, concrete actions, decisions, thoughts, ideas, insights, experiences, goals, memories, perceptions and expectations that enable a company bridge the gap between the factors of production that the company controls and the output that it wishes to create and deliver to its customers.² More succinctly, strategy is the qualitative essence of how a company does what it says it will do for its current and prospective customers. At a high level, strategy gives broad, abstract and general answers to the question; In what direction should we travel?

Definition#4: What is marketing? Marketing is the process by which the producer of a product or service creates demand for its output. It involves various modes of communication aimed at helping consumers interpret the value that the producer hopes to deliver to each consumer that buys the product or service. Marketing includes sales, advertising, public relations, and any other practice or activity whose ultimate goal is to build awareness in order to directly or indirectly facilitate sales. Marketing is what makes operations necessary. Without marketing, there would be no demand to satisfy.

Definition #5: What is operations? Operations is the set of activities in a startup or a company that takes inputs and turns them into the final product or service through which the value proposition is delivered to the market. Operations is focused on the process of transformation – transforming tangible and intangible inputs into something that the market is willing to pay for, at a cost level that enables the producer to earn a profit consistent with the accompanying strategy. Operations seeks to answer the question; How do we implement strategy?

In a fine dining restaurant operations is the process of transforming the knowledge and experience of every member of the restaurant’s staff into a consistently enjoyable and memorable dining experience. This process has to deliver results in tangible and intangible ways. Dishes have to be executed to a high degree of excellence, and the atmosphere, decor and service have to evoke emotions of pleasure, satisfaction and joy that meet or exceed diners’ expectations and cause them to dine at the restaurant as frequently as the restaurant’s operators wish. Each time a diner has a meal at the restaurant it must be memorable, in a good way.

In a general aviation company operations is the process that begins with finding out the traveler’s needs, matching those needs with a specific aircraft, and then safely transporting the traveler from the point of departure to the desired destination within a period of time acceptable to the traveler. Each time a traveler is transported from one place to another, that passenger must arrive safely. Also, the passenger should have enjoyed the trip enough to choose that charter company as frequently as its operators wish.

In a software startup operations is the process that begins with designing and creating the software, delivering it to users, and then ensuring that it is available whenever users or customers wish to use it. The experience of using the software has to be such that it is the first choice that users think of when they consider using software to facilitate that specific set of activities.

Once a strategic choice has been made, the process of transforming inputs into outputs is accomplished through capabilities within the organization. The diagram below shows the connection.

Strategy is concerned with answering the question; Where should we go? Operations is concerned with answering the question; How will we get there? The question around capabilities is; What do we have to be good at to get there? While all this is happening, processes that determine how a startup does its work are being developed. Processes matter because eventually a set of processes will lead to the development of a certain set of capabilities. As a result, it is essential to think about which capabilities are most critical to the startup’s survival before adopting one process over another. Eventually, as the startup matures it builds up a legacy of past choices that may limit or enhance the strategic options it can pursue in the future. Faced with a period of dramatic change in consumer or customer preferences, market structure, technological innovation, or regulations, flexibility is what separates winners from losers. The key attributes of a successful operations organization are:

1. 1. It must work hand in hand with strategy, marketing, finance, human resources, and every other area within the company.
   2. It must implement procedures and processes that lead to the right blend of capabilities within the company – for exploiting current opportunities, or resolving future threats.
   3. It must make infrastructure choices that protect the startup’s strategic flexibility to deal with current and unforeseen developments in the market.

Here are a few examples of how strategic and operational flexibility made the difference between startups that otherwise were neck-and-neck at some point in time – Friendster, Myspace, and Facebook.

What do you do when your users adopt your product for uses you did not intend or foresee? Facebook and Friendster were founded roughly around the same time. Friendster was founded in 2002, Facebook in 2004. Friendster reportedly grew to 3 million users within 3 months after it became generally available to the public in the United States. It soon became obvious that users were using Friendster for purposes its creators did not intend. For example they started creating various types of profile pages that were not tied to a real person – these became known as Fakesters. Friendster’s founders decided to prevent users from creating such profiles. Facebook experienced a similar behavior from its users. However, it took a different approach. It observed such behavior, learned from it and eventually enabled the behavior it observed. For example, users’ habit of creating profile pages for parties on college campuses eventually led to the development of the events feature on Facebook. In effect;

Facebook continuously watched how users used, and of course misused, their products by gathering usage data. These data guided their product development roadmap and helped ensure they were building features or making changes to their services that would encourage users to recommend the service to others (fan-out) and continue using it themselves (retention).³

While we can not say precisely what motivations drove the opposite reactions Friendster and Facebook had to observed user behavior, we can guess that a need for operational simplicity motivated Friendster’s response. Locking down and restricting the number of ways in which its users could engage with its product made operations easier to manage. On the other hand, Facebook’s approach seems to reflect a philosophy that is more outward looking and user-centric. In other words, operations would adapt to ensure that Facebook’s product evolved to reflect the desires and wants expressed by its users in their day to day interaction with the product. In the process, Facebook developed capabilities that strengthened its strategy and so on and so forth.⁴

What do you do when your technology infrastructure appears to be unable to keep up with growth, and the accompanying demands? ¹ Sometimes things change in a really big way as a startup makes the transition from searching for a business model to scaling. Maybe its marketing and its product are so successful that existing infrastructure proves to be inadequate to meet the demands that the startup’s customers and users place on it. The startups that thrive and go on to become transformative companies adapt operations to deal with this reality. To do so they call on new capabilities that they have developed over the course of time. Google⁵ and Facebook⁶ provide examples. They both realized that the off-the-shelf server hardware that they were relying on to run their operations were not necessarily designed to handle the massive amounts of data that their unique business models require them to each deliver to their users and customers daily. As a result they have modified their operations so that they now develop, design and build their own server infrastructure.⁷ There are many benefits to be derived from this. For example; First, this practice saves them money by optimizing energy usage. Second, it ensures that their business runs smoothly and efficiently so that users and customers have an experience that is commensurate with the value propositions that Facebook and Google have made and the experience users and customers have come to expect. Third, this makes it more difficult for new competitors to compete directly with Facebook or Google in the core areas of their business. As a testament to the soundness of this approach, many other companies that rely on technology as a cornerstone of their business operations are moving towards the practice of building their own custom server and networking hardware and software.⁸

Contrast the fate of Facebook with that of Myspace and Friendster. Remember that Friendster, Myspace and Facebook were founded in 2002, 2003, and 2004 respectively. At one point Myspace was the most visited social networking site in the world. It briefly overtook Google as the most visited website in the world. So What happened to Friendster and Myspace? I am certain there is more than one reason for their failure. However, reports in the press suggest that their inability to adapt the technology that was core to running their business played an important role in their loss of market leadership to Facebook, and their subsequent failure – they continued to rely on server hardware and software from original equipment manufacturers who build off-the shelf servers. Friendster reportedly slowed down as traffic to its website grew.⁹ Similar observations are made about Myspace.¹⁰ While we do not know the full details, we can deduce that operations at Friendster and Myspace did not mature to the the same extent that operations at Facebook had matured.

As these examples suggest, operations is critical to the survival of any entity that intends to grow to any substantial size by satisfying demand from a large number of customers or users. To succeed technology startups cannot make the mistake of treating operations like an unwanted orphan stepchild. Rather, operations must have a seat at the table, and it must participate in a healthy exchange of ideas, information and opinions with strategy, marketing, finance and accounting, and HR about how each of those functions can work, individually and in concert, to accomplish the goal that the startup wishes to set for itself. Tech startups can ill afford to have operations start from the bottom.

1. Any errors in appropriately citing my sources is entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained them. ?
2. Fred Nickols, Strategy: Definitions & Meanings, 5/24/2012. Accessed online on Aug. 10th, 2014
3. Fisher, Michael; Abbott, Martin; Lyytinen, Kalle (2013-11-01). The Power of Customer Misbehavior: Drive Growth and Innovation by Learning from Your Customers (p. 103). Palgrave Macmillan. Kindle Edition. ?
4. Twitter and Zynga are two more examples of cases in which product features, and operations have been adapted and modified on the basis of observed user behavior. Pinterest just updated its web and mobile apps with a messaging feature. From the outside it appears this update is a response to the observed behavior of its users.
5. Jeff Dean(2008 Google I/O Session Videos and Slides); Underneath The Covers at Google: Current Systems and Future Directions. Accessed online, Aug. 15th 2014.
6. Jonathan Helliger; Building Efficient Data Centers with The Open Compute Project, Apr. 7th, 2011. Accessed online, Aug. 15th, 2014.
7. Jon Brodkin; Who Needs HP and Dell. Facebook Now Designs All Its Own Servers, Feb. 14, 2013. Accessed online, Aug. 16, 2014.
8. Netflix, Amazon and RackSpace are each reported to have adapted their operations to rely on custom designed server hardware. I assume there are others we do not yet know about. At one point SingTel, the huge Asian telecommunications company was thinking of building its own CDN instead of relying on providers like Akamai.
9. Gary Rivlin; Wallflower at The Web Party, Oct. 15th, 2006. Accessed online, Aug. 16th, 2014.
10. Abel Avram; Debate: What’s The Reason for MySpace’s Decline?, Mar. 30, 2011. Accessed online, Aug. 16th, 2014.