Companies that build online marketplaces struggle to solve the dreaded chicken and egg problem—how do you get buyers without sellers and sellers without buyers onto the platform? Many of today’s familiar online marketplaces—like Uber, AirBnB, eBay, Xbox Live, PayPal, OpenTable, and Angie’s List—managed to crack this challenge and reach sustainable scales.  In addition to creating useful products for their users, most analysts would agree that these businesses also benefit greatly from positive network effects between their buyers and sellers. That is to say, each additional buyer or seller on the platform generally has a positive effect on his or her counterparty:

  • More sellers à more options for quality, price, and convenience for buyers
  • More buyers à more opportunities to transact for sellers

Many people are ready to give these companies the benefit of having solved for positive network effects on their platform. In fact, I too fell into this trap until Professor Gautam Ahuja of Ross School of Business (visiting at HBS last year) made me re-examine this belief. Rather, there exists an opportunity to more deeply understand these companies by exploring the network effects across all party interactions. We can gain a better idea of the costs involved in growing the business and what valuable follow-on products should be developed. The basis for this company analysis begins by understanding that multi-sided platforms must inevitably also have multiple network effects. To clarify what this means, it might be easier to first understand what network effects look like on a single-sided platform.

A Single-Sided Network Example: Early Facebook

When Facebook first came on the scene in the mid-2000s, it resembled a single-sided platform. In the time before marketers were peppering the site with ads—weren’t those the days!—users basically joined other users in a system where all users were alike. We can think about Facebook’s network effects by looking at what happened when a single new user joined (an increment of +1 new users).

The incremental user’s content provided other users with more to see and explore. This content came in the form of posts, photos, and music preferences and meshed seamlessly into other existing users’ experiences. An existing user now has more to explore and interact with on the site—like seeing pictures of the new user’s trip to Bali or discovering linked articles the new user shared. Existing users’ content might also get more interactions from the new user in the forms of more likes, comments, and tagged photos. These could all be described as positive effects as they generally enhanced the value for Facebook users.

However, the addition of a new user could make the Facebook experience turn negative as well. The new user might constantly post pictures of their cat and make it difficult for existing users to find the content they really wanted to see in their newsfeed. The new user could also be someone existing users didn’t want on the site, like a coworker or boss, which would make them less inclined to share photos or other content. Quite simply, the network effects induced by one new Facebook user could be positive or negative.

The insight into Facebook’s network effects helps us understand a lot about what followed in the company’s history. Because the effects were predominantly positive, people invited their friends and family to the site virally, reducing expensive marketing and growth costs. The site exploded and reached 1.49 billion monthly active users as of June 2015 and saw 1 billion different users log in on the sam day in August 2015. Facebook subsequently developed products like a filterable newsfeed (no more cat pictures from the new user) and privacy tools to reduce users’ pain points (only share photos with friends or make posts visible to friends “except XYZ” people) that resulted from its rapid growth and negative network effects. These developments could have been predicted by our simple analysis of identifying the network and its positive and negative attributes.

A Multi-Sided Network Example: AirBnB

When thinking about multi-sided networks, the model for analyzing network effects grows more complex. Rather than thinking about how an incremental user will affect the entire network, we should scrutinize who the incremental user is and what network is being affected.

To illustrate this more clearly, let’s consider a two-sided platform like AirBnB. When a new user joins the AirBnB site, we should first consider whether the user is a guest or host. Next, we need to explore how that additional guest or host affects other guests and hosts. For this two-sided network example, there exist 4 possible network effect scenarios:

  • How does an incremental guest affect hosts?
  • How does an incremental guest affect other guests?
  • How does an incremental host affect guests?
  • How does an incremental host affect other hosts?

Understanding network effects can quickly get complicated when dealing with multi-sided platform. The number of unique network effects necessary to consider is n2 for each distinct n type of parties on the platform. As we saw with Facebook, network effects can be either positive or negative, complicating our understanding of two-sided platforms even more. When considering positive or negative effects, the interactions that should be examined are 2n2.

Below I’ve illustrated how AirBnB might experience positive and negative network effects across all 4 of its network change scenarios:

AirBnB Network Effects Diagram

 

An Updated Model for Thinking About Network Effects: Uber

The AirBnB analysis is a useful starting point, but I find it easier to simplify each of the distinct networks into a more manageable characterization. This reduction allows us to quickly understand the dynamics in the networks of a company while maintaining an explainable simplicity. I therefore classify interactions into one of three buckets.

  • Collaborators (Positive)—Parties predominantly enhance the experience of other parties in the network. Examples of collaborators include funders on Kickstarter who together to support an idea or product or gamers on xBox live who play together in multiplayer Halo battles.  Such relationships encourage users to invite other users to a site, and can lead to organic site growth and lower user acquisition costs.
  • Counterparties (Positive)—Parties are involved predominantly in a monetary transaction or exchange that satisfies both sides. Examples buyers and sellers transacting for a deal on Groupon or a mother ordering food via delivery service Sprig. Parties exchange clearly identifiable goods and services, which, when priced at a point such that the transaction clears, creates value for both parties that supports repeat usage and high user lifetime value from multiple transactions.
  • Competitors (Negative)—Parties predominantly compete for resources or opportunities. Examples include applicants applying to Y Combinator where only a select number of applicants are accepted or eBay bidders competing against each other for a baseball autographed by Mickey Mantle. In both cases, competition is likely to give users a worse user experience as they might not secure the opportunity or good or end up paying a higher price. This can result in a lowered user experience, unsubscribing, and high sign-up or reactivation expenses.

By using this framework, it helps me understand the operational costs a company is likely facing and what products they might consider developing in the future. For example, if this analysis were applied to ride-sharing start-up Uber, it might look like this:

Uber Network Effect Diagram

For Uber’s two-sided platform, a large part of the company’s value comes from solving the most obvious network dynamic: matching drivers with riders and riders with drivers. The company was able gain a foothold in markets like San Francisco because cab companies were not keeping pace to satisfy this counterparty need. As more drivers joined Uber, riders benefitted with greater ride availability and more riding options (uberPOOL, uberX, uberXL, uberTAXI, UberBLACK, uberSUV, uberSELECT, uberPOP, uberBIKE, etc.). As more riders sign up, drivers are more likely to match with a pick-up request and earn money for their services. These services led to increased usage by both riders and drivers as value was realized.

However, this dynamic doesn’t necessarily lend itself to growth. Drivers aren’t actively inviting or converting new riders, and new riders aren’t energetically recruiting new drivers. The first time they usually encounter each other is during an Uber ride, at which point they’re both already on Uber’s platform. While a positive experience for each party—a clean, convenient ride for the passenger and a profitable transaction for the driver—will influence who how often the other party uses Uber in the future, they’re not actively growing the platform.

The story gets more interesting when you look at the network dynamic across the rider <-> rider and driver <-> driver dimensions. For current riders, each additional rider chiefly means increased competition for resources. In Uber’s case, this manifests itself in surge pricing when many people try and use the app at the same time—such as during a rainstorm or Friday rush hour. The experience is painful, and users are upset by either the wait time to find a rider or the total cost for the trip. Similarly, as more drivers join the platform, existing drivers face both increased competition for riders and reduced chances for earning surge prices. If driver’s aren’t able to find riders and drive around unoccupied, this cuts into the driver’s ability to earn for time worked.

By understanding the interplays occurring across its networks, it’s easier to identify and appreciate Uber’s growth, marketing, and development challenges over the past few years. While Uber has benefitted from word-of-mouth marketing for its remarkable service, much of Uber’s recent growth depends on promotions and discounts rather than virality. Because riders and drivers aren’t actively working to sign up other drivers and riders without an incentive, Uber bears the burden of these growth costs itself.

For example, Uber offers money to users (riders and drivers) who sign up new riders and use a unique promotion code (mine is below—feel free to join using it!). Additionally, Uber will give new riders one or more free rides upon joining. To sign up new drivers, Uber offers drivers a $500 bonus after completing their 20th rider, $500 dollars for signing up a Lyft driver, and fixed hourly income guarantees to ensure new drivers realize monetary gain immediately—with promotions often varying city by city. These acquisition costs can be large for a company looking to scale globally and help explain why Uber has raised massive amounts of cash to grow operations in areas like China, India, and other parts of Asia. In addition to building and operations costs, a lot of that money will likely go to signing up riders and drivers through aggressive promotions and discounts and launching citywide marketing campaigns. Given Uber rider’s lifetime value from its positive counterparty interactions, such costs can likely be easily justified.

Uber Promotion Code

On the product development side of the business, Uber’s network effects can explain a lot of what the company has focused on building. Paramount to the experience is maintaining a positive rider <-> driver and driver <-> dynamic. Anything that facilitates a quality service has taken precedent in the pipeline to protect the company’s advantages and keep users using the app. Such developments include credit card scanning for easier payment, license plate information to help riders identify drivers, written explanations for 3 star or below reviews to protect drivers’ reputations, and optimal route maps to make sure the most cost-effective route is taken.

Uber has worked to tackle negative network effects inherent to its business as well. Uber launched a fare split feature that aims to make the riding experience more collaborative and less competitive, easily allowing users pay each other and receive ride receipts. Additionally, a feature was added to surge that allows users to be notified once surge has dropped below as certain level, decreasing the pain from increased competition over resources. Finally, uberPOOL matches different rider pairs so that a each group receives a lower fare for carpooling with the other party. These features all subtly aim to shift the experience from competitive to collaborative.

Looking Ahead

In this post, I hope that I’ve helped lay out a new model to help understand network effects for multi-sided online marketplaces. By identifying all the distinct networks that exist and then understanding the interplay of people in those networks (collaborators, counterparties, competitors), one can develop a valuable tool for understanding much about an online business. This insight can be used to analyze a company’s growth and marketing costs—will users sign other users up or do they need to deploy resources? It can also give vision into a business’s product development priorities—what networks need to be protected with better products and which networks need pain points addressed?

 By: Ry Sullivan


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Over the past semester we have identified successful mobilization for new lines of business in tech incorporate backwards compatibility, complements that may be generated by third party developers or by the core business itself, and solutions to customer pain points with significant barriers to entry.  At the same time, core product offerings can provide stand-alone value to customers through simply streamlining the interface between software users and the data they use. While many large companies have adopted software to improve productivity of individual enterprise activities, it is the recent push towards integrating business technologies onto one platform in enterprise marketing software suites (EMSS) that unlocks the opportunities inherent in holistic marketing solutions. [1]

The beginning of the twenty-first century witnessed a revolutionary incorporation of the internet with everyday communications and transactions.  This in turn generated an unprecedented volume of information, or “big data”, encompassing how consumers make decisions and how businesses operate more efficiently.   Big data analytics now facilitate myriad entrepreneurial ventures that leverage niche markets and long-tail consumer demand into viable business models.  Consequently, traditional companies in established markets have had to redesign and streamline how they serve their customers to match changes in consumer demand and increased global competition.  Enterprise software has emerged as an answer for these established companies to utilize big data analytics to guide their business strategies.  EMSS  aim to integrate a diverse range of activities including management of ad campaigns, digital assets, web content, marketing and lead resources, as well as predictive modeling. [2]  

The complexity associated with integrating diverse marketing software solutions has left EMSS development to big software players such as Salesforce.com and Adobe. In fact, the magnitude of the opportunity to create value in this space is demonstrated by the “…$3.5 billion shopping bill as it positions Salesforce as a one-stop-shop for all its customers from the sales department to, now even more importantly, the CMO’s office.”[3]   Expected benefits from EMSS consolidation of current disparate marketing and tracking software are improved visibility and collaboration between all marketing channels resulting in clear resource efficiencies and reduced total costs of strategy implementation.  Additionally, strategy development should be of higher quality and larger impact due to improved ability to create holistic solutions aligning company offerings with customer expectations. As of yet, it seems that no one EMSS incorporates both best-in-class software and seamless integration [4].  It will be interesting  to watch how the current digital marketing integration leaders discussed above shape the convergence of real-time data analytics and holistic marketing strategies to transform online and mobile commerce as they further penetrate our global economy.

1. Teradata http://applications.teradata.com/Big-Data-Hero-eBook/Landing/.ashx (October 30, 2014)

2.  Teradata http://applications.teradata.com/Big-Data-Hero-eBook/Landing/.ashx (October 30, 2014)

3. Salagar, Serge, “Salesforce’s Reinvention as a Marketing Behemoth”, http://techcrunch.com/2014/10/29/salesforces-reinvention-as-a-marketing-behemoth/  (October 29, 2014)

4. Munbach and Warner,  “Forrester Wave: Enterprise Marketing Software Suites, Q4 2014” http://www.adobe.com/solutions/digital-marketing.html   (October 21, 2014)


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While we have seen technology disrupt many industries in a relatively short period of time, I wonder if technology can truly disrupt every industry.  Education is one area I believe cannot be disrupted even by the best of technologies, though innovations in technology can certainly enhance the educational experience.  If we can imagine a world in which teachers unions, and not to mention the educational bureaucrats, would even allow technology to take over the classroom I cannot imagine a technology that could fully replace a human being.  There is, however, huge potential for improving the education experience at the K-12 level through technology.

Have you ever tried teaching a group of 30 average American teenagers? Well I haven’t either, but it seems really tough even for the most passionate educator.  Each student has his or her own unique learning style and each is at a different level academically.  Some are math geniuses, but struggle with writing. Others may thrive in History, but just don’t seem to follow your science lesson.  This is the perfect situation in which a school system could introduce technology education programs whereby teachers could assign work to students based on their specific needs.  This would allow teachers to pull out groups of students at similar levels and provide them with more individualized lessons while their peers are working on computer-based assignments.   With more level-appropriate lessons, students would likely feel more engaged in the learning experience.

This may raise the question of whether students can simply complete grade school through online programs and drastically reduce our spending on education.  The answer is no, in my opinion.  While technology can enhance the academic experience as described above, computers cannot replicate the benefits of being in a classroom where one learns from peers, can be assessed by a human being, and develop important cognitive skills.  I think students at all levels would be less likely to complete learning modules if no one was around to monitor them, engage them further in the material, or help answer questions.  Teachers play a critical role in the lives and learning of our students, but they cannot be all things to all students.  Our educators have come under fire many times as inadequate, and I agree that we have allowed some bad teachers to continue educating our kids, but many of them are passionate and capable individuals who are forced to teach one lesson in one way to 30 different minds.  So until we have the ability to clone ourselves or we restructure our education system altogether, technology is a teacher’s best partner in the classroom.

http://thegentlemansarmchair.com/comic/old-comic-the-effect-of-technology-on-modern-education/

http://techcrunch.com/2011/12/18/education-technology-disrupt/

carmenf

 


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At the recent Engadget Live event in Boston I happened to come across the formlabs stand, showing off their high-resolution, stereolithography (SL) 3D printer – as I played with the intricate and delightful objects, which the printer had produced, I could hear much of the same enthusiasm for the printer and the industry that can be found widely on the web.

Formlabs Form 1 3D printer

I welcome the time when instead of waiting 2 days for my Amazon Prime delivery I can be sent the CAD data for that replacement dishwasher component (undoubtedly with secure DRM for one-time use) and print a good-as-new version at home. Or when I can just model and print the architectural design for my new house. But I fear that this is still a long way off.

I was impressed at the resolution of the formlabs Form 1 printer (25-100 microns), made possible by SL process (in which a beam of UV light cures layers of a liquid resin held in a vat) rather than the more common fused deposition modeling (FDM, in which layers of melted thermoplastic are drawn by a mechanically-controlled extrusion nozzle). But the only available material is a proprietary ABS-like resin, sold only formlabs in grey or transparent. Clearly this choice of technology was meant to offer a better product to the user but the material will ensure no price-competition and greatly limit the applications of the printed components (due to the single specification of the resin).

When asked if they had any plans to make a larger machine (currently the build volume is only 125 x 125 x 165 mm – slightly smaller than half a shoebox), I was told that many people had been asking the same question. Presumably because, though excited by the Jar-Jar Binks models, people struggled to see the immediate uses for such a device. At the moment the Form 1 is targeting small businesses for rapid design prototyping and hobbyists but the pricetag of $3299 may not make it an easy purchase decision.

Most of the “affordable” 3D printers use FDM technology and can be found for around $1000, offering far worse performance and slow printing speed. MakerBot produce one of the best known 3D printers (the Replicator) and with their 3D scanner (the Digitizer) they are attempting to create a platform (the “Thingiverse”) that allows users to share either scanned or modeled CAD data for printing. Due to the standard file format of the data (.stl) and open nature of the platform it seems that they are simply trying to grow the overall demand and community rather than create a real ecosystem of their own with direct network effects but minimal multi-homing costs – at least it they are not trying to start a file format war.

A recent report by Gartner estimates that almost 100,000 sub-$100,000 3D printers will be shipped next year, which points to some increasing uptake by medium-sized businesses. Also UPS are conducting a retailer test for in-store 3D printing services – I think this really points to the growing enthusiasm around of 3D printing by for small firms, for which actually buying their own machines is either out of reach or unnecessary. Large companies have been using 3D printers for rapid prototyping for some time and as prices drop and quality improves (and even new metal materials become possible) this is only set to continue with perhaps the possibility of small-scale flexible manufacturing.

Another hurdle that must be overcome for widespread adoption by the casual user is the actual modeling of designs to be printed. The small business or at-home market cannot survive on shared designs, scanned 3D images or multi-thousand dollar CAD software licenses. Let’s see if this generation of printers end up gathering dust in well-off hobbyists’ basements or allow faster innovation in the continuing economic recovery.


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Relaunching America: Innovation, Entrepreneurship, and Disruption

A group of co-founders shut themselves in a sweltering, dimly lit room and were determined not to see the light of day until they had released their new system to the world. The beta system was currently in the market and users were anxious to see their new release. They had spent the entire summer scripting their platform, arguing over precise features to include, and deliberating over the future implications of this version. They were close to a release date, and failure was not an option. The room was in Philadelphia, Pennsylvania, and the year was 1787.

This story may have conjured visions of the Steves, Jobs and Wozniak, toiling in a Los Altos bedroom, Paul Allen and Bill Gates’ scripting marathons in Harvard’s Aiken Lab, or Zuckerberg’s hacking and face mashing in Kirkland House. However, this story refers to a different collection of founders – now we call them the Founding Fathers. The users were the citizens of newly independent United States of America. The beta release – also known as Articles of Confederation – had become insufficient to meet users’ needs. Now the stakes were high. More than their financial futures and reputations were on the line. Their very lives, and the lives of 3 million citizens hung in the balance. They weren’t just innovating a product or service, they were innovating a system of representative governance.

The Founding Fathers followed a proven tech startup model of learning from others’ mistakes, refining the best ideas of early adopters, and creating something familiar, yet completely new and disruptive. Think Google, iPhone, Tesla, etc. The early product launched by the French, Romans, and Greeks provided excellent user testing and case studies, while thought leaders like Montesquieu and Locke provided some key insight for experimentation.

However, just like any high-performing startup, over time this governing system has experienced growing pains. The user base has grown approximately 10,000% since that hot Philadelphian summer, while user satisfaction toward elected representatives – particularly Members of Congress – has remained remarkably low. The executive leadership and board of directors have been able to increase the opportunities for user participation incrementally over the past two centuries; however, as technology has dramatically improved over the past two decades and the ability to send communication has increased exponentially, the elected official’s ability to absorb, respond, and leverage these tools has remained relatively static.

Technology’s rapid development, and Congress’ slow adaptation, has crippled a system that is predicated on the idea of citizen engagement. Thomas Jefferson’s maxim that “eternal vigilance is the price of liberty” illustrates the power of network effects that bolsters online startups. Ultimately, the system functions more effectively as more users join the process.

According to a recent Congressional Management Foundation survey, over one-third of congressional staffers feel their office spends too little time on online communications. At the same time, 64 percent of senior staff believes Facebook is “a somewhat or very important tool for understanding constituents’ views and opinions.” The number is 42 percent for Twitter. Congressional offices seem to understand the importance of using new technologies, but they are unwilling or simply unable to maximize the potential of these innovative technologies. This story becomes even more concerning when looking into the future.

The United States is witnessing a growing disconnect between elected officials and its next generation of citizens. As the number of social technologies continues to grow, the connection between Members of Congress and younger constituents continues to shrink. The 2012 Institute of Politics Survey of Young Americans’ Attitudes toward Politics and Public Service found that “young people of all ages, races and political persuasions care deeply about their community and their country… [However] young people continue to lose faith in the institutions and the leaders elected to govern our country and shape their future. And now, through this project, we have learned that potentially millions of young people will stay home on November 6, not participate in the election — choosing instead other paths of civic engagement, or nothing at all.” These young Americans are living their lives online through technology, and effective engagement depends on the ability to connect in this new digital world. They care about their country and they want to be involved if their elected officials can learn to speak their language.

This year I founded Connected Congress and held a bipartisan tech series for Members of Congress and senior staff on the Hill. The goal was to help Members understand not only what technology is available, but also how they can use technology more effectively. (http://ConnectedCongress.org) With over 20 speakers from Google, Facebook, Twitter, think tanks, House, and Senate, I realized perhaps the future is not so bleak. Not all Members of Congress are opposed to adapting technological advances into their offices. In fact, digital staff, administrators, and a handful of tech-minded Members are trying to influence behavior in the institution.

In a recent interview, Congressman Darrell Issa, Chair of the House Oversight Committee, described this “technology-centered approach” as “disruptive to the government bureaucracy and many in Congress because it demands experimentation, data-driven analysis and actually listening to our users — the American people — about how to make government work better for them. That’s why social media and innovation are so central to my work: we in Congress do not have all the answers, but we can have a relentless drive to adapt technology to let taxpayers re-engage with government on their own terms.”

Now it’s our turn. My goal is to channel some of the innovation our system was founded on over two centuries ago to disrupt this market of representative and participatory democracy.

More Reading

Congress’ Wicked Problem. Lorelei Kelly, New America Foundation
http://oti.newamerica.net/publications/policy/congress_wicked_problem

Can Congress Work Like A Tech Startup?
http://www.techdirt.com/articles/20120509/03041418839/can-congress-work-like-tech-startup.shtml

Does Anyone in Congress Get Technology? Joshua Lamel
http://www.huffingtonpost.com/joshua-lamel/does-anyone-in-congress-get-technology_b_1465743.html

‘Virtual Congress’ Would Weaken Deliberative Process – Rep. David Dreier (R-Calif.)
http://www.congresslink.org/print_expert_virtualcongress.htm

Congressional Management Foundation
http://www.congressfoundation.org/projects

Congressional Management Foundation: Communicating with Congress Project
http://www.congressfoundation.org/projects/communicating-with-congress

Dawn of a revolution (Bill Gates at Harvard)
http://news.harvard.edu/gazette/story/2013/09/dawn-of-a-revolution/

Connected Congress series highlights struggle of digital staffers. Colby Hochmuth
http://fedscoop.com/connected-congress-series-highlights-struggle-of-digital-staffers/

Connected Congress: Tech for Members
http://ConnectedCongress.org

Harvard University Institute of Politics (IOP) Public Opinion Project Survey
http://www.iop.harvard.edu/survey

 


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