Report by:

Samuel Doyle (11975385)

Samuel.r.doyle@gmail.com

University of Amsterdam, MBA Fulltime 2017-2018

Supervisor: Dr. Martijn Rademakers

Date of submission: Aug. 15th, 2018

Case Company of RLY Technologies

Optimal Business Model Design

for Internet-Native Start-ups

For Internet-Native Start-ups

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Contents 1. Abstract .......................................................................................................................... 3

2. Introduction .................................................................................................................. 4

3. Literature Review/Underlying Theory ........................................................... 5

4. The Frameworks/Tools + Application ........................................................... 8

5. Managerial Recommendations/Implications ............................................. 26

6. Limitations and Conclusion ............................................................................... 35

7. Appendix ..................................................................................................................... 37

8. Bibliography: ............................................................................................................. 40

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1. Abstract

Start-ups are becoming an increasingly important source for overall economic growth, but

the concept of business model generation in the start-up context has not been explored in depth

until relatively recently. This paper sets out to answer the underlying research question of: How

does one design an optimal business model for an internet-native startup business? In order to

do so, this paper will drive a dual-faceted strategy that is part theoretical, and part practical. On

the theoretical side, the paper seeks to be novel in its marriage of generally later stage business

model innovation frameworks, such as Kim & Mauborgne’s (2004) Blue Ocean Strategy, with

that of early stage business model generation frameworks, such as Ries’s (2011) ‘Lean Start-

up’. Before delving into the frameworks, the paper will survey pertinent academic literature on

the core topics of business models, value propositions, and platform monetization strategies.

Following from the literature review and frameworks, the paper will synthesize and build upon

the commonalities between the articles to create an actionable theoretical framework for

startups looking to craft and refine their value propositions in a quest to design the optimal

business model.

The practical part of this paper will be a detailed exploration of the case study of the start-

up social network platform RLY Technologies. RLY is an entrepreneurial application-based

startup that is trying to become the dominant Generation-Z social media platform. They are

going through the arduous process of business model generation & refinement and are currently

experiencing difficulties in articulating their core value proposition and revenue model to

potential investors. Given the pressing need to craft a compelling value proposition in an

industry awash with well-funded and dominant incumbent competitors, RLY provides an

especially interesting case for both testing this paper’s custom theoretical framework as well

as answering the overarching research question on optimal business model design for start-ups.

Drawing from my experiences working at RLY in tandem with the classroom learnings from

my UvA MBA, this paper concludes by providing actionable recommendations that can be

implemented to help RLY setup processes to continuously improve and refine their business

model.

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2. Introduction

In today’s world, Mobile Applications (Apps) have become fundamentally interwoven into

the fabric of our daily lives. For many, including this paper’s author, it’s almost unthinkable to

go an entire day without opening the Spotify app (music), WhatsApp (communication), or

Instagram (entertainment). With an ever-widening breadth of services and utility offered by

apps, it’s no wonder to see global app downloads topping 175 billion and consumer spending

ballooning to $86 billion, with AppAnnie pointing to continued >20% growth for the global

application market after 20171. Yet despite these rising tides of increasing smartphone

penetration and increasing advertising & consumer spending on mobile, there are clear winners

and losers emerging within this mix. It is often the app’s business model that ends up being the

deciding factor. Without a well-developed business model, businesses will tend to fail to

deliver or to capture value from their operations. This is particularly true of Internet and mobile

application businesses, where the creation of revenue streams can be perplexing due to

customer expectations that many services should be free (Teece 2010).

The focus of this report is on business model generation for mobile-first start-up businesses,

with special thought given on how to build a revenue model and the corresponding

monetization strategy. This paper centers around the case of RLY Technologies (Appendix A),

a female-founded iOS platform startup business, that is trying to create a wholly new social

media platform focused on authentic and moving content (videos/GIFs/iPhone Live Photos).

Their aim is to understand how to craft a business model that can ultimately monetize its rapidly

increasing user base in non-privacy intrusive ways. Given the recent public outcry2 surrounding

privacy concerns on social networks, RLY is looking to avoid building their business model

based on monetization strategies that rely on unscrupulous data collection and privacy-intrusive

advertising. With RLY’s situation kept in mind, the key question this paper sets out to answer

is: How does one design an optimal business model for an internet-native startup business?

In the next few sections, I will review the meaning and importance of business models, how

to define one’s value proposition in a startup and internet/mobile context, and how a mobile-

first business should go about choosing their revenue model and monetization strategies. The

1 https://techcrunch.com/2018/01/17/global-app-downloads-topped-175-billion-in-2017-revenue-surpassed-86-

billion/ 2 http://news.abs-cbn.com/overseas/03/29/18/facebook-overhauls-privacy-settings-amid-data-breach-outcry

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first part of this paper surveys the major literature surrounding the topic. Specifically, it delves

deep into understanding what constitutes a business model and the role they have on ultimate

business success, with specific attention paid to the discussion of value propositions and value

capture. Building on that discussion, the paper looks at business model designs within multi-

sided platforms. Thereafter, Osterwalder (2010)’s business model framework will be

introduced to sketch the basic elements that comprise a business model. This framework

section will weigh the discussion of revenue model and value proposition more heavily than

other elements. I then will build on the business model framework with that of Ries’s (2011)

Lean Start-up to create a more detailed framework for the process of business model generation

at a startup. Given both Ries and Osterwalder’s emphasis on understanding a business’s value

proposition, this paper will also utilize Kim’s (2004) Blue Ocean Strategy Framework to more

fully flesh out the process of crafting a differentiated value proposition. This custom framework

will be further augmented by Eisenmann’s (2006) and Parker’s (2016) strategies for multi-

sided platforms to ultimately set the stage for a more focused discussion for RLY where I will

outline some key insights and actions that can be implemented to build an authentic business

model that can become a source of competitive advantage in of itself. Lastly, this paper will

end with a review of the limitations of this custom framework and a brief conclusion.

3. Literature Review/Underlying Theory

Within this section, I aim to describe the meaning and importance of business models as

relevant to the underlying research question on optimum business model generation for an

internet-native business. To begin, with an understanding of what exactly constitutes a business

model is required as this initial literature survey helps to bring clarity to an otherwise loosely-

defined concept that is very fundamental to business success. From the review of the pertinent

literature on business model definition, the importance of value propositions and value capture

becomes clear. I then explore how value propositions can be defined and validated through

grounded real-world continuous learning. Finally, I conclude this section by surveying how

traditional management theory has evolved in the context of internet-native and platform-based

business models.

A. What is a Business Model?

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While the phrase “business model” has become popularized in management jargon and

seen in pop culture on shows such as HBO’s “Silicon Valley”, there is still some academic

disagreement on the scope of what constitutes a business model. Shafer et. All (2005) cross-

sectional literature analysis found a whopping 42 different components present in academic

definitions of what is a business model. Compare that to other side of the spectrum,

Christensen’s (2008) oft -cited work found business model to be simply be the combination of

4 key elements of Customer Value Proposition, Profit Formula, Key Processes, and Key

Resources. Magretta (2002), see’s business model’s as parts of a broader narrative and defines

them as “stories that explain how enterprises work”.

There also exists the question of how a business model is created, with Casedeus et. All

(2010) seeing it as the byproduct of a firm realized strategy and Shafer (2005) seeing it similarly

as the sum of the strategic choices that have been made thus far. Some academics, such as

Porter (2001), have even referred to the phrase as simply part of the “Internet’s destructive

lexicon”. Within all these competing and diverse definitions, there emerges a general theme

around the importance of value, namely how does one create value, how does one deliver value,

and how does an enterprise capture that value. For simplicity’s sake and to more closely align

with the case company, this paper will use Tecee’s definition of a business model as the

baseline for further analysis, which he sees as “how the enterprise creates and delivers value

to customers, and then converts payments received to profits” (2010).

B. Importance of the Value Proposition

Important to Tecee’s definition, is the discussion of creating value for customers, which

represents an integral part of pretty much all the literature surveyed on business model

definitions. In fact, Seddon et. All (2004), sees the business model simply as simply the

outlining of the essential details of a firm’s value proposition for its various stakeholders. Value

proposition is defined simply by Franca (2017) as the combination of products and services

that create value for an enterprise’s customer. Franca’s simplistic definition opens the broader

question of what it is exactly that creates value for the end customer, and Franca offers aspects

such as newness, cost reduction, convenience, usability, performance, and ‘getting the job

done’ as various avenues for value proposition creation.

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Building on the ‘getting the job done’ aspect of a value proposition, I find Christensen’s

(2008) layman’s explanation of this element of a business model to be very helpful in

conceptualizing an otherwise rather amorphous and broadly-defined concept. He views value

propositions as the ‘job to be done’ that solves a big problem or fulfils an important need for

the target audience. Within that view, Christensen postulates that the single most important

attribute of a customer value proposition will be its precision: how neatly and completely it

solves the target customer job to be done (and nothing else). While Christensen’s ‘jobs to be

done’ framework is a useful lens to view the concept of value proposition in, this framework

requires management to have a deep understanding of the customer’s pain points, which is a

tall order for a start-up application-based business that has had limited face-to-face interaction

with their end customer. The question of how an enterprise validates its customer problem and

proposed value proposition for will be addressed in more detail in the frameworks section. This

paper will look to utilize Ries’ (2011) method of validated learning as the core mechanism for

gaining a deeper understanding of the customer problem and ones proposed solution.

In addition to the importance of understanding the customer, the management literature

surveyed also stressed the importance about having a unique value proposition. Uniqueness, or

‘inimitability’ as Barney (1991) named it, is widely viewed by management literature as one

of the key building blocks of a competitive advantage. Porter (2001) sees the uniqueness of

value propositions as the result of forced trade-offs between quality and cost, whereas other

academics such as Kim & Mauborgne (2014) see uniqueness as not bounded by trade-offs but

rather the product of innovation on multiple aspects at once. In the coming framework section,

this paper will introduce the Blue Ocean Strategy from Kim & Mauborgne (2014) as part the

broader discussion on the concept of value proposition innovation in the context of continuous

business model generation and improvement.

C. Internet-Native and Platform-Based Business Model

Much of the literature surveyed thus far has been grounded in the traditional economic

theory based on 20th century business models. The discussions of customer problems, value

proposition and value capture get blurred when shifting focus to internet-native businesses such

as RLY. The increasing proliferation of the internet has turned many longstanding business

models on their head. Tecee (2010) asked fundamental questions about how businesses can

continue deliver value to their customer, and how they can possibly capture value from new

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information services that customers increasingly expect to receive without charge.

Furthermore, building on Tecee’s work, Wirtz (2010) pushes for a deeper understanding of

internet-native business. His resultant framework describes and breaks out four basic types of

prototypical Internet business models: Content, Commerce, Context and Connection, with

which one can begin to classify insurgent internet business models such as that of RLY. Parker

(2016) dives into a specific breed of internet-enabled business models, the multi-sided

platform. Within this mode of analysis, the topic of network effects becomes exceptionally

important as they turn traditional economic thinking on their head. Parker sees that multiple

sides’ participation in successful models generates cross-group network effects, or in other

words, that each side benefits not only from its own supply-side increasing but also from that

of the other side of the platform. These cross-group network effects work to create a virtuous

cycle where more users on the platform add incremental value to all participants on the

platform. It is then no surprise that Casedeus et. All (2010) see that successful platform-based

business models work to generate a virtuous cycles of feedback loops that strengthen

components of the model with each iteration. This paper will go into more detail in the

framework section on how RLY and other platform-based businesses can look to harness

network effects to drive an ever-improving value proposition for all their potential platform

constituents.

4. The Frameworks

A. Business Model Canvas Framework

To begin the discussion of the major tools and frameworks surrounding optimum business

model generation, it is the papers intention to lay the groundwork with a detailed analysis of

what exactly constitutes a business model. This paper uses Osterwalder (2011)’s basic

definition of the business model as “the rationale of how an organization creates, delivers, and

captures value”, with the operative word being the value that is created, delivered, and captured

by a start-up. Osterwalder’s Business Model Canvas (Appendix B) provides a visual

representation of the 9 basic building blocks that form the system of how an enterprise looks

to make money. His nine key elements cover the four-broad reaching categories of customers,

offer, infrastructure, and financials. To explain his business model components, I will use the

explanatory case of a successful mobile-first platform: Snapchat.

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First and foremost, in Osterwalder’s Canvas, sits the Customer Segments, which make up

the heart of the model. Without a customer, there is no real reason to exist as a business. One

of the first decisions that needs to be made by a start-up in defining their model is to decide

which customer segment they are going to serve and those that they are going ignore. In the

case of Snapchat, due its status as a multi-sided platform, there are multiple groups of

customers they must address in their business model definition. Snapchat requires both a large

active user base as well as advertisers and content creators. On one side, it needs advertisers to

fund the platforms operations, while on the other, the advertisers require a certain number of

eyeballs to make it worth their while to advertise on the platform. Snapchat decided early on

to specifically target the younger internet-native generation as their core customer base, which

ultimately led to their advertising client selection being heavily overweight to consumer facing

product companies and brands that were trying to engage with a younger audience.

The second building block is that of the Value Proposition, which is the solution to a

customer problem or pain point. Importantly, Osterwalder makes the distinction that it’s not

one single attribute but rather the aggregation of benefits that are being offered to customers.

It is also important that the value proposition resonates with one’s proposed customer segment

otherwise there will be a mismatch within the proposed business model. In the case of

Snapchat, they helped their users communicate with each other in a manner that better reflects

who they are. Their main tool they used to communicate their value proposition was their

distinctive private message service that auto-deleted messages which empowered users with to

engage with each other with a level of authenticity and playfulness that could not be found in

other social networks at the time. Given the relative importance of value proposition to optimal

business model selection, this paper will go more into depth in the following sections on the

topic.

Thirdly, a start-up must consider their Channel choice when building a business model.

Channels are the key the customer touchpoints that work to shape customer experiences and

ultimate perceptions of the brand. Channels are all about delivering the value proposition to

the right customer segment. For Snapchat, their early focus was on viral user acquisition

channels. Any messaging app is naturally more fun when your friends are on it, and Snapchat

worked to both minimize friction for inviting friends and to encourage users to invite as many

of their friends as possible. Later in the company’s history, they began to try and broaden their

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consumer touchpoints using physical channels such as the distribution of Snapchat spectacles

and through their own branded content creation delivered via the app.

Fourth, comes the topic of Customer Relationship, which is about choosing the type of

relationship it wants to build with their target customers. There exists a relationship spectrum

of how personal or automated one wants the relationship to be. Importantly, this relationship

choice is not static and should evolve over time as the business matures. For Snapchat, what

started as a small-scale support network with live support operators quickly turned into a highly

automated support system with only minimal company/customer interaction on most kind of

service requests. This decision was mainly due to the increased scope of the customer segment

and the resulting movement towards a more of a mass-market type of relationship.

Next, comes a discussion of the Revenue Stream, which is where a start-up needs to

understand how they will generate cash from their customers. Much analytical thought is

required here as the company must ascertain what value their customers segments are willing

to pay and in what manner are they most willing to pay. Monetization strategies have long been

one of the hardest things to figure out for otherwise highly successful app and internet-based

companies, which can spell trouble when investor funding finally dries up because the business

can’t self-fund its own operations. Given the importance of this topic, a more detailed

examination of platform monetization strategies will come later in the paper. For Snapchat, this

is still a major point of contention, as they have chosen to utilize an advertising-based revenue

model, where they collect fees from those advertisers that wish to market to their users. The

heavy-handedness of the advertiser intrusion into the in-app experience has arguably eroded

the value proposition to users somewhat and illustrates the careful balance that must be walked

when deciding on a revenue model.

Sixth on Osterwalder’s list is the topic of Key Resources, which are the key assets that

enable a business model to function. They can take the form of tangible, financial, intellectual,

or human capital. Depending on the other elements of the business model canvas, one type of

resource may be most fruitful to focus on. In the case of Snapchat, it is not really their financial

or physical resources that matter in the business model, but rather it is their intangible resources

of brand, key partnerships, and strong app-developer human capital that make up the backbone

of this value element. Following from key resources comes the seventh element of Key

Activities, which comprise the most important processes and operations a company must

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undertake to be successful. Just as some resources are more important for reaching markets,

maintaining customer relationships, or earning revenues, the same can be said of defining one’s

key activities. Often there is little valued added or strategic significance from retaining a

process in-house, and management time and effort can be freed up through out-sourcing the

process to a more specialized provider who has the economies of scale to deliver it more

cheaply as a service than possible in-house. For Snapchat, the key activities engaged are

generally focused around driving user growth and keeping those users engaged, as user growth

is the fuel that their business model runs on.

The eighth block of the Business Model Canvas is the Key Partnership block. This

describes the network of partners and suppliers that form the broader environment where the

company operates. Osterwalder’s model distinguishes four key buckets of potential

partnerships, namely strategic alliances, strategic partnerships (between competitors), joint

ventures to develop new businesses, and buyer-supplier relationship. For Snapchat, they choose

to deepen their relationship with existing advertising partner NBC Universal, through the

creation of jointly run studio3. What was once a simple buyer-seller relationship, has evolved

into that of a co-operative joint venture that is attempting to re-write the way that scripted

content is delivered on mobile screens, potentially creating a win-win for both partners.

Cost Structure makes up the 9th and final element of the Business Model Canvas. While

seemingly a simple function of the other 8 elements, cost structure decisions can make or break

a start-up, especially in the early days. Broadly speaking there are two main buckets of cost

structures, either a cost-driven model or a value-driven model and choosing one often must

align with the other elements or will spell financial doom. Snapchat, with its large base of VC

investors and easy access to equity funding, has seen itself tend towards a much more value-

driven model when it comes to a discussion of cost centres. Snapchat views user growth as the

ultimate driver of its business model, so within that lens it’s only natural to see them make

large cost outlays on things surrounding content, user acquisition, and user retention. Cost

structure normally becomes an element of higher importance later in a company’s lifecycle or

if there is an internal liquidity crunch.

3 http://variety.com/2017/digital/news/snap-nbcuniversal-studio-venture-duplass-brothers-shows-1202591040/

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So, with the 9 key elements examined through the lens of Snapchat, it’s very important to

emphasize that there is a certain level of cohesion that must be achieved between these building

blocks. They should not be viewed as discrete building blocks but rather part of an inter-

connected web of value creation, capture, and delivery. In the Snapchat example, it’s easy to

see how cohesive the customer segments, value proposition, channels, and key activities all so

closely intertwined to create what has been one of the most highly successful viral-growth

based mobile applications of all time. The close-knit and deliberate interlinking between those

elements enable Snapchat to build a better mousetrap. But if they are not vigilant, there are

ominous dark clouds on the horizon in their business model elements of revenue and cost

structure. The push for monetization has already begun to affect user growth and engagement,

which has been accompanied by a rising costs in customer retention and decreasing efficacy of

marketing spend. Ignoring those two elements could be the beginning of the end for what has

been incredibly successful growth-oriented business model.

In addition to exploring Snapchat as a case study, it’s also important to ask the question of

“are all aspects of a business model are equally important?” Ladd’s (2016) studies with early

stage entrepreneurs, found that his start-up teams, who focused their efforts on target customer

segments and value proposition, performed nearly twice as well as teams that did not spend a

commensurate amount of time on those elements. This would suggest that RLY or any other

aspiring platform spend its efforts on really understanding the customers pain and their

proposed value proposition before delving into defining the rest of its business model.

B. Lean Start Up

While Osterwalder’s framework generally works to shed light on the topic of business

model definition, a deep dive into Ries (2011) “Lean Startup” yields a more in-depth discussion

of how one goes about getting to their desired business model. At the core of the Lean Startup

model sits the central idea that a manager, instead of spending lots of time planning around

assumptions, can work to drive constant adjustments through steering process called “build-

measure-learn”. His framework encourages start-ups to use their amount learned as the

measuring stick for progress in early days. But this learning needs to be validated and

demonstrated empirically before a team can hope to discover valuable truths about their

startups business prospects. Through empirical testing, startups can track and measure any

positive improvements in their core metrics and eliminate any management efforts that are not

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directed (and measured) at learning more about what customers really want. It is important to

caveat that all validated learning should be backed up by measurable input collected from real

customers.

Over multiple feedback loop cycles, it becomes clear what the customer values and the

startup can work to better tailor their business operations to formulate a value proposition that

resonates with the customer. To help speed up these cycles, Ries advocates for the use of

Minimum Viable Product (MVP) to ensure short time between cycles with minimal efforts.

MVP’s within this framework are designed not just to answer product design or technical

questions, but mainly to test fundamental hypotheses about the business model. Using this

framework, Ries sees MVP’s and validated learning as not only a more accurate approach, but

also a faster one when compared to market forecasting or other classical business planning

techniques.

While this paper agrees that speed is an undeniably important concept for start-ups to

consider in their learning decisions, I would argue that there are significant risks associated

with such a reckless focus on feedback loop iteration. Inherent in the definition of MVP are the

terms “minimum viable”, which leads developers to generally skimp on architecture. From a

Lean perspective, this makes sense as if one doesn’t have the time to build a full product, then

one also doesn’t have the time to invest in architecture. But decisions about architecture can be

especially important in determining the long-run success or failure of a business. This paper

takes the case study of Evernote to illustrate the point. In its infancy, Evernote had many note-

taking app-based competitors, some of which had all the latest UX/UI bells and whistles that

were the result of faster time-to-market and build-measure-learn feedback loops. Evernote,

instead of focusing on incremental customer improvements, chose to take a whole product

architecture focus where they scrutinized their architecture with the goal of scaling into

multiple products. Ultimately this deliberate focus resulted in a more vibrant ecosystem that

enabled independent software vendors to build on top of their platform and thus unlocking

positive network effects and is an effective example of Sheehan’s (2009) “Network Services

Logic” for creating incremental value.

While the Lean Startup framework’s focus on speed may have some negative side-effects

such as employee burnout, hasty rejections of good ideas, and the limited thought available for

product architecture and longer-term business strategy, the framework still serves as an

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excellent roadmap for a prospective startup to gain insight into refining their business model

and ultimate value proposition. Importantly, this emphasis on speed enables startups to rapidly

test their key assumptions for the business. Ries (2011) divides assumptions into two key

buckets, “The value hypothesis” and “The growth hypothesis”. Utilizing this framework, a

startup would want to both focus on testing whether its service or product delivers real value

to customers while using it and focus on testing how new customers will discover their

products.

In the case of RLY, the testing growth and value hypotheses unveils the key variables that

ultimately control growth. On the value hypothesis, RLY should test the leap of faith value

assumption that “social media super users have the free time to use another social network”.

This assumption is key because social media super users are the engine of growth for content

creation, which is the main reason people engage with the platform. Using the Lean Startup

framework of validated learning would require empirical data to validate this assumption. In

this example, we would argue RLY should look at user engagement metrics (average time of

sessions, # of content created, app opens, # of friend invited, etc.…) for heavy users of Snapchat

and Instagram, which will help to validate the key assumption that there is room for another

social network in the lives of social medias heaviest users. To test a key growth hypothesis,

such as “influencer marketing is the fastest way to attract new users”, RLY would then follow

a similar procedure of examining its user acquisition process through validated learning. The

empirical data collected in this case would then be on things such as signs by attributed channel,

cost per acquisition, and the number of friends invited by those users brought in through

influencer marketing. And it is through these repeated build-measure-learn cycles that RLY, or

any startup in general, can uncover what customers want and how to craft the best possible

engine of growth.

It is important to note that when validated learning points out that startup is headed for a

dead-end, that the Lean framework does not advocate for completely abandoning the project.

Rather it is about repurposing the learnings that have been done and finding a more positive

direction to continue with. Ries (2011) names this repurposing as a “Pivot strategy” where he

argues for structured course corrections that position the company to test new fundamental

hypotheses about their product or strategy. He provides a catalog of potential pivot strategies

that a startup could seamlessly utilize to shift direction mid-course. RLY, with its roots in

Virtual Reality and now an aspiring social media network, has already undergone its own major

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pivot. The scope of RLY’s past pivot is well beyond what Ries (2011) would advocate for

given the lack of opportunity to utilize the learning of a B2B virtual reality services business

in their now more B2C platform-centric model. Ries (2011) would instead argue that pivot

requires one foot rooted in the organizations past learnings, while seeking even greater

validated learning in a fundamentally new direction. That said, Ries would cheer RLY’s timing

of the pivot decision as the framework advocates for pivoting sooner rather than later and tends

to define a startups true runway as simply the number of pivots they have left in the tank.

Utilizing Ries’s typology of pivot strategies on a go forward basis, would potentially involve

RLY engaging in strategies such as a customer segment pivot (currently focused on female

teenager market) or potentially an engine of growth pivot (currently focused on organic/viral

user acquisition). But within all potential pivot options, it is important to remember to continue

the process of validated learning about what customers want.

While this paper asserts that validated learning is the bedrock for business model creation

and refinement, in the lens of a consumer-centric app business it also important that a startup

produces high-quality experiences for customers as a primary goal. Ladd (2016) sees that too

many build-measure-learn loops can result in diminishing or even negative return from

customer interaction. He sees this coming from an erosion of confidence, on both sides, where

too much feedback from customers leads management to so frequently change their ideas that

they become disheartened and legacy consumers are not sure what the company stands for.

This, like the Evernote case, would argue for a more deliberate and thoughtful pace of build-

measure-learn feedback loops to craft those higher-quality consumer experiences. That said, I

would argue that if one doesn’t know who the customer is and what they value, then one does

not know what quality is, and the best way to gain true customer understanding is through

repeated build-measure-learn cycles, albeit done in a more deliberate and thoughtful manner.

C. Blue Ocean Strategy & Value Proposition Innovation

One of the key linkages between both the Business Model Canvas and the Lean Start Up

frameworks is the concept of a differentiated value proposition. While Ries’s (2011) work sees

a tailored value proposition as the result of repeated “Build, Measure, Learn” cycles, and

Osterwalder (2011) sees it in simple terms as simply the bundle of attributes in products or

services that create some value for a customer, both stress the critical importance of the concept

as a key to business success. Further building upon their frameworks with the goal of choosing

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the optimal business model in mind, requires a deeper understanding of what exactly

constitutes a value proposition, before understanding how a startup can design and ultimately

innovate one. Traditional strategists such as Porter (2001) sees the uniqueness of value

propositions as the result of forced trade-offs in the product and value chain. While there is

extensive management literature on managing the strategic tension from trade-offs in value

proposition design, it is this paper view that an aspiring social network or mobile application

not look to bound itself to the classical view on value proposition design. Instead, this paper

will introduce the multi-faceted Blue Ocean Strategy from Kim & Mauborgne (2014) as

guidelines for value proposition innovation.

While the term “Blue Ocean” may adorn the headlines of Kim & Mauborgne’s (2014) oft-

cited work, the framework actually begins with a required understanding of their so called “Red

Oceans”. The authors characterize Red Oceans as maturing industries where the market has

gotten incrementally crowded, and potential profits and growth have been reduced by an influx

of entrants. The naming of those industries as “Red Oceans” comes from the resultant

commoditization of that industry’s product and the cutthroat competition that then turns the

ocean bloody. Within this Red Ocean context, management teams utilizing a structuralist or

trade-off-based framework only can see two potential options for survival, namely a low-cost

positioning or a high-quality differentiation strategy. Kim & Mauborgne stand opposed to that

view as they write that “In contrast [to value-cost trade-off models], those that seek to create

blue oceans pursue differentiation and low cost simultaneously” (Kim & Maurborgne 2004,

p13). Blue Oceans in their eyes are the uncharted waters where a company can capture new

demand that is free from traditional competition. This enviable position affords those

companies in the Blue Ocean the prospects for profits and growth, but it also begs the question

of how a startup can create or enter its own Blue Ocean, which this paper will touch on later.

While admittedly Kim & Maurborgne’s work is generally thought to be utilized in the

context of managerial advice for those companies in maturing or dying industries, these “Blue

vs Red Ocean” viewpoints in the context of an aspiring social media network paints an

interesting picture. With 2.2 billion monthly active users4, and its suite of other highly used

connectivity apps, Facebook is in a position of immense power when it comes to the broader

social networking industry. Given its massive user base, Facebook captures the lion’s share of

4 https://newsroom.fb.com/company-info/

17

the global marketing budget spent on social networks, which leads to a highly competitive red

ocean for those left that stand to do battle in a market with such high-power concentration in a

competitor. The cut-throatedness of this Red Ocean can be illustrated through the Snapchat

Stories versus Instagram Stories analogy. Stories, which are public exhibitions of temporary

content, were first a differentiated piece of product innovation wielded by Snapchat, and they

were often credited with Snapchats share gains in the social media sphere. But Facebook

quickly imitated the same product innovation, rolling out their own Instagram Stories which

led to decreases in Snapchat’s Stories engagement of ~40 percent since the release of Instagram

stories. Top creators on Snapchat used to get around 330,000 views per day until June 2016,

whereas they now only get around 205,000 to 250,000 views per day5. Facebook using simple

imitation was quickly able to turn what had been a leading point of differentiation for Snapchat

into a highly contested red ocean. And if Snapchat, with its multi-billion-dollar market cap and

high-profile board struggles in an increasingly red-ocean, how can an aspiring social network

think to compete in such a red ocean? Through that lens, it becomes increasingly obvious that

if a social media startup wishes to succeed in crafting a unique and innovative value

proposition, they will need to consider a Blue Ocean strategy.

One basic framework put forward by Kim & Maurborgne (2004) for managers was their

“Four Actions Framework” (Figure 1), which they intended to break the structuralist view of

simple trade-offs between differentiation and low cost, and ultimately work to create a new

perception of value. Utilizing this framework, enables a management team to break from the

orthodoxy and identify attributes that could be eliminated, reduced, raised, or created. But just

identifying the attributes that should be altered is not enough to create a unique value

proposition. There is also the question of how one charts a path to its own Blue Ocean following

the identification of the key attributes it wishes to change.

5 https://www.socialreport.com/insights/article/115005343286-Instagram-Stories-Vs-Snapchat-Stories-2017-

Statistics

18

Figure 1: Four Action Framework

Blue Oceans, according to Kim & Maurborgne (2004) come about in one of two major

ways, either through the founding a completely new industry or when a company alters the

boundaries of an existing industry. This paper will largely examine the second route given its

pertinence to the overarching research question. Within the lens of the second route, Kim &

Maurborgne postulate that there are 6 generic ways to redefining market boundaries, which

they named their “Six Paths Framework”. Namely they see that firms can: 1) Look across

alternative industries, 2) Look across strategic groups within industries, 3) Look across the

chain of buyers, 4) Look across complementary service offerings, 5) Look across emotional or

functional appeal to buyers, 6) Look across time. Within these generic strategies it’s important

to keep the focus on the fact that a startup needs to look systematically outside of its current

red ocean that it intends to do business in. When utilized properly, their Six Paths framework

can delivery key insight into how to possibly reconstruct market dynamics in their favor.

Building on Kim & Maurborgne’s framework for discovering Blue Oceans, Sheehan

(2009) adds 3 more pathways, namely “Network Services Logic, Industrial Efficiency Logic,

and Knowledge Intensive Logic”. Amongst Sheehan’s 3 incremental value creation logics,

where managers could combine innovative bundles of ‘standard’ attributes to design wholly

new offerings, we found the Network Services Logic most compelling for an app-based

business such as RLY. Sheehan’s Network Service Logic at its core is about the creation of

incremental value through connections with other constituents in the network. Take the

example of Amazon, where they encourage buyers to connect to with both brands and other

buyers through their reviews platform. An increase in the number of positive reviews gives

consumers a better gauge of the quality of a vendor and they are more apt to purchase as such.

19

On the other hand, vendors benefit from honest consumer feedback and from a virtuous positive

feedback loop in demand if their reviews are positive and large in numbers. Taking a systems-

view as such and working to create network effects can help a start-up to find their own Blue

Ocean. Sheehan (2009) recommends that to utilize this value creation logic efficiently, that

start-ups should look to ensure after-sale services are available, other entities are encouraged

to participate in the network, as well as work to create virtual communities within all sides of

a platform model.

D. Monetization Strategies for Platforms

Monetizing a social network or other platform-based business provides for a unique

managerial challenge. Academics and strategist tend to agree that the inherent value of any

platform is derived largely due to the network effects it creates (Parker 2016; Eisenmann 2006).

As already touched upon in the value proposition section, network efforts are what drives the

positive feedback loops that accelerate user growth with minimal additional effort required by

the platform operator. But despite being powerful engines of growth, network effects are

relatively fragile and can easily be destroyed by premature or reckless monetization plans. As

in the case of Myspace, Guardian (2015) writes that last nail in the coffin for the company was

when chief Rupert Murdoch pushed them to make one billion dollars in revenue a year when

they only doing 1/10th that amount, which led to ill-advised monetization strategies that

destroyed the user experience. Parker (2016) agrees as he sees that any charge levied on users

makes them less likely to use the platform, which erodes the positive network effects that built

the platform in the first place. This tension and tight-rope walk between growth and

profitability makes monetization a key concept that must be considered in every platform or

business model design decision, regardless of where the company sits in its lifecycle of

development.

Parker’s (2016) framework for platform monetization provides a strong base to understand

how an aspiring platform business can wade into this issue and navigate the strategic cross-

currents. Firstly, along the lines of this paper’s early outline of value proposition, he proposes

that a platform needs to identify the excess value it creates for their participants. According to

Parker (2016), value creation can be characterized in 4 large categories: 1) Value provided to

consumers through access to content created on the platform; 2) Value provided to third-parties

through providing access to a community; 3) Value provided to both consumers & producers

20

through providing tools that facilitate connection; 4) Value provided to both consumers &

producers through curation to ensure higher quality of interactions. It is these papers view that

these excess value creation buckets must align with the core customer value proposition as

detailed earlier.

To bring real world examples into the discussion of this framework, one can simply look

to Facebook, which I like to fondly think of as the ‘mother of all’ platform businesses. In the

case of Parkers first value creation bucket, Facebook clearly provides a tremendous amount of

value to the consumer through its news feed and profile system, but despite the incredible

amount of utility those functions bring to an individual user, Facebook smartly does not attempt

to directly monetize that by charging for access to the content for a consumer. In terms of the

second value creation bucket, Facebook provides an amazingly detailed picture of its members

and boasts the ability to create custom niche segments for its third-party providers. For the third

bucket, Facebook works to remove the distance between producers and consumers by allowing

big brands to create pages and profiles to engage with consumers. And lastly, Facebook works

significantly to curate its platform, censoring that content which is hurtful or intentionally

deceitful, which makes it easy for genuine interactions to take place. While Facebook serves

as a great example to explain these concepts, it is also important to note that Facebook is a

relative unicorn in that it generates significant value across all four of Parker’s (2016) value

creation buckets, whereas most aspiring apps or social networks would only likely self-identify

their excess value creation as falling into one or two of the buckets.

Following from an understanding of where excess value can be created, comes the

discussion of how a start-up platform can look to monetize that platform-created value. A smart

monetization strategy starts with looking at all four buckets of value in their entirety and

figuring out which one can be most easily be re-captured by the platform without damaging

their precious positive feedback loops of viral growth and platform-participant engagement.

As in the case of Myspace, it’s almost always a mistake to try everything at once when it comes

to monetization or do overly simplistic things like charging all participants for access to the

platform. To begin with, Parker’s (2016) framework sees four overarching revenue models for

an aspiring platform. Firstly, one can simply charge a transaction fee. Second, one can charge

for access. Third, one can charge for improved or enhanced access. Lastly, a platform can

charge for enhanced curation. When examining those broad models, it’s very important for a

21

start-up to keep in mind the ultimate goal of generating profits without reducing the platforms

virtuous positive feedback loops.

To better understand how these broad-based monetization strategies work, it’s helpful to

relate them to real life examples. A simple transaction fee model could look like eBay’s basic

charges for listing an item for sale and then a simple percentage of the final sale value as

commission. It is this papers belief that eBay’s initial listing fee actually goes against traditional

monetization logic (which they get away with due to their size and reputation), as when one

considers levying a transaction fee, they should wait until a transaction has closed (i.e. value

has been created by those participating in the transaction), as an upfront listing fee may work

to discourage users from engaging in the listing in the first place, which limits growth and

achieving positive network effects.

In terms of a monetization model based on charging for access, Brazil’s Roomgo

(EasyQuarto) provides an interesting example. The roommate finding service charges for those

who wish to gain access to the platform to see available rooms in large cities like Rio de

Janeiro6. The service does not charge those that post room listings, as the platform made a

strategic choice to subsidize the supply side of their two-sided marketplace, but only those

seeking accommodation. While this model works well in supply-constrained or high demand

areas, their monetization strategy choice makes expanding coverage to cities characterized by

an over-supply of rooms difficult as in those cases the scarcity in the marketplace sits on the

demand side (and charging for access would only increase the demand shortage by deterring

new signups). Eisenmann (2006) on the other hand argues that one should subsidize the

network’s more price sensitive side and to charge more to those that are more responsive to the

other platform participants growth. Either way, it’s important that platforms consider both

supply/demand scarcity and the amount of platform-value created when making any decision

regarding charging for access.

Parker’s (2016) third avenue for monetization involving charging for enhanced access is

best illustrated by dating apps. This monetization strategy also works to minimize frictions

around a negate impact to user growth as it allows for viral growth to drive increased sign-ups

with no initial fee for access. Dating apps such as Happn or Tinder take care to preserve their

6 https://www.roomgo.com.br/

22

positive network effects as they make sure that all parties can participate and operate at a

relatively high level. Their monetization strategy comes from the demand from some users for

incremental services and utility offered to their users. This freemium and enhanced-access

paradigm is widely used by many aspiring platform businesses, but when choosing this model

one needs to stay vigilant that they aren’t seen as throttling user access through the division

between services offered on one side of a pay-wall or the other.

The fourth platform monetization strategy involves charging for enhanced curation can be

examined through the lens of Angie’s List. When platforms get to a certain scale, there comes

a time when the quality of offerings begin to slip or when consumers struggle to parse through

the sheer number of offerings. While that can spell untimely doom for a platform, it also

provides an avenue for monetization if a platform can provide the tools to cut through the noise.

In the case of Angie’s List, they recognized that customers were willing to pay for higher

quality reviews. While other review aggregators allowed for all submissions, Angie’s list saw

a monetization opportunity in prioritizing quality of content over the quantity. Funnily enough,

Angie’s list originally charged an access fee to consumers wishing to view their database of

higher-quality user reviews (Monetization Model #2) before introducing free and premium

access7 (Monetization Model #3) which shows that a platform business operator needs to be

flexible as they balance the tight-rope act between monetization and platform growth.

While Parker’s (2016) revenue models appear relatively straightforward and simplistic, this

paper preaches caution and to tread lightly when making the transition out of a strictly user-

growth oriented phase. A platform needs to be especially careful to avoid charging for services

that they have been providing for free, as this can create resentment in its existing user base

who have grown accustomed to these services being delivered for free (Tecee 2010).

Additionally, some newer monetization techniques such native advertising (paid content that

resembles unpaid) run the risk of turning users off to the platform as Wojdynski (2016) sees

that when users find out native ads are “sponsored” or “advertising that they generally then

lead to more negative evaluations of the poster. For example, much of Facebooks value

proposition is based on how relevant it’s feed is for its users, and lots of advertisements could

ultimately erode the underlying value proposition for the end users.

7 http://fortune.com/2016/07/13/angies-list-reviews-free/

23

5. Continuous Platform Value Proposition Refinement Framework

With the relevant literature and academic frameworks now surveyed, it is important to

perform a synthesis of the pertinent materials with the goal of the research question of ‘what is

the optimum business model design for RLY and other internet-native platform start-ups’ in

mind. While the authors of the aforementioned frameworks may attack the same problems from

different angles and have varied preferences in terms of methods of execution, one theme

whose importance is universally shared, is the concept of the value proposition. To address the

research question, I initially wanted to first wade into a discussion of revenue models, but it

became abundantly clear that without a requisite understanding of one’s underlying value

proposition, that such discussions were misguided as they missed the elemental core of all

business models. Ladd’s (2016) study again reminds us that business success is often a function

of how carefully management pays attention to crafting its value proposition. To that end, I

propose below a custom framework for how to identify, craft, and build a differentiated value

proposition that represents the cornerstone of any business model formation plan. To do this in

the context of an internet-native start-up, I will use the building blocks of Osterwalder’s (2011)

business model canvas as the base, with Ries’s (2011) validated learning approach as the

preferred method of execution for crafting the value proposition in the real world. Parker’s

(2016) framework augments this custom methodology through his “excess value” creation

typology, which I then look to improve via Kim & Mauborgne’s (2014) “Four Action

Framework”. To summarize all these competing frameworks and deliver the best possible

recommendations for an internet native platform business, I present this custom framework

below (Figure 2):

24

Figure 2: Continuous Platform Value Proposition Refinement Framework

Within Figure 2, its important to first observe the mechanism by which the entire apparatus

is run. This model uses Ries’ (2011) emphasis on validated learning as the core engine for

value proposition and business model design. Why? Because quite simply the “build-measure-

learn” loop cycle is the best way to continuously refine the value proposition of a company. I

would stress that this custom framework is not something to be done once by a start-up but

rather should be used as a framework for continuous learning to work to craft and refine the

core of one’s business model. This model should be viewed in a dynamic sense, with the goal

being incremental improvements and learnings with each iteration through the cycle. It is also

important to remember that validated learning is grounded in real data and real customer

feedback, and not only just a product of internal whiteboard sessions. This framework

emphasizes the use of real world customer data as the guiding inputs for navigating these

continuous cycles of validated learning.

With the motor of the engine being validated learning and the fuel being real world

customer feedback, it’s time to talk about the other apparatuses needed to turn this framework

into a fully functioning value proposition machine. To begin with, a deep and true

Val

idat

ed L

earn

ig

(Met

od

of

Exec

uti

on

)Identify Customer

Needs

Identify Potential Value Creation Buckets

Differentiate Value Proposition

- Ostewalder’s (2011)

customer segments; know

your customer

- Identify customer problem

- Solve job to be done

(Christensen 2016)

- Identify potential value

creation buckets on all sides

of platform

- Choose value creation

methodology/(ies)

- Network Effects

- Kim & Mauborgne (2014)

Four Actions Framework

- Sustainable differentiation

- Inimitability

25

understanding of the end customer is required. A start-up should first identify their core

customer segment and map out their wants, needs, and desires through things such as customer

empathy maps, personas, and survey work. Osterwalder’s (2011) canvas demonstrated that it’s

important to be able to identify your core customer segment as one’s product offering may

satisfy different needs for different sets of customers, and it becomes important to understand

how to understand how customers intend to use your offering. Christensen (2016) characterizes

this phenomenon as customers having “jobs to be done”, and they hire your product to fulfil a

specific job to be done. While Christensen is all for customer empathy and understanding, he

goes so far as to caution that a lot of customer research methods employed by today’s firms are

taking them in the wrong direction as they fundamentally forget about what job the customer

is hiring the product for. My custom framework argues to keep this “jobs to be done” principle

in mind as a start-up looks to undergo the process of customer (and their problems)

identification.

After successfully identifying customer segments, this framework then directs

management’s attention to identifying the interplay between the various sides of the platform

business. Should stakeholders have been properly categorized by management, it will become

clear the competing needs of the various players on the platform. While it goes without saying

that every need of every partner will not be met, the trick is finding symbiotic wants/needs/’jobs

to be done’ between the platform parties that can be aligned through use in the platform. Using

Parker’s (2016) typology, this framework sees value creation characterized across 4 general

buckets: 1) Grant access to content created on the platform; 2) Give access to a specific

community; 3) Facilitate connection; 4) Value provided through curation. With these

typologies in mind, a start-up can look to find intersecting needs between its prospective

platform participants and work to create a lasting value proposition that not only meshes with

both parties’ desires but also creates excess value that can be captured by the platform and

monetized later.

With a value proposition identified and a value capture methodology selected, the

framework turns its attention to making one’s value proposition differentiated with the ultimate

goal of building a competitive advantage. Part and parcel of this discussion of differentiation,

is that of inimitability, which Barney (1991) saw as one of the four key ingredients sustained

competitive advantage. Crafting a compelling value proposition is a difficult feat in of itself

but crafting a unique and inimitable one is the true way to sustained business success if you

26

buy into the traditional competitive advantage logic of Barney and Porter. To create

differentiation, this framework utilizes Kim & Mauborgne’s (2014) “Four Action Framework”

& “6 Pathways” to help think about supercharging their underlying value proposition and

distancing itself from the competition. This part of the framework is especially important to

consider in the case of RLY given the strength of the incumbent firm’s (Instagram/Facebook)

competitive position and their ability to quickly imitate and integrate ancillary product features.

Taken all together, these elements of the custom framework provide a solid initial roadmap

for a start-up to engage in beginning to craft and refine their value proposition. I propose this

framework as a way for a start-up to get the ball rolling but would advise that this framework

be used in a dynamic and working context that requires customer feedback as inputs to further

refine and develop one’s value proposition. It’s also important to again notice Ries’s (2011)

concept of a pivot in respect to this custom framework. Should a cycle of iteration lead to a

dead-end in terms of product acceptance, management should waste no time in pivoting their

value proposition to more offer that more closely matches with their customer’s desires and

jobs to be done. And it is through this use of continued validated learning that a start-up will

be able to ultimately craft their most compelling value proposition that can become the bedrock

for their sustainable competitive advantage. In the following section, I will utilize this custom

framework in the lens of the RLY and their quest to design their optimum business model and

will deliver recommendations to help generate an optimal business model.

6. Managerial Recommendations/Implications

RLY clearly is taking on a big challenge in trying to upend the status quo in the social

media given the massive balance sheets and user bases of the incumbent players in the space.

What should their value proposition be? How can they provide a compelling and differentiated

experience to users? How will they be able to make money off their platform given the

pushback on traditional privacy-intrusive advertising-based revenue models? These are

questions I will attempt to address as I look to answer the overarching research question on

business model selection for a startup platform business. I will first review the current

definition of RLY’s business model in the lens of Osterwalder’s (2011) business model canvas.

With the starting point mapped, I will then spell out actionable recommendations for the

implementation of this paper’s Continuous Platform Value Proposition Refinement

Framework. Following from that I will survey potential long-term monetization paths that mesh

27

with the rest of the proposed business model design. I will then conclude this section with a list

of potential challenges and a timeline for implementation of the proposed recommendations.

A. RLY: Initial Business Model Canvas

RLY has both the blessing and the curse of being a rather early stage company, with only

5 full-time employees; while they have the flexibility to quickly adopt customer preferences

and engage in build-measure-learn loops, they also lack the financial and human capital

resources that larger firms can take for granted. Part and parcel of that lack of human capital is

the limited thought that has been paid to business model selection given the bandwidth capacity

limits of the existing team. While the team has a strong background in marketing and

engineering, there was no single person responsible for designing & driving strategy and

tackling bigger picture items like business model definition and value proposition refinement.

Of course, much of this work is accomplished via RLY’s terrific product management team

and ongoing customer validation work, but there was still a lack of a coherent and consistent

understanding of what constitutes RLY’s business model. To best formulate recommendations,

it is first to quickly clarify the current understanding of RLY’s business model according to the

management as according to Osterwalder’s (2011) business model canvas (Table 1).

Canvas Element Definition to Date

Customer Segments Social Media Users in Generation Z (Age 13-24) in US;

Mass market appeal; iPhone owners

Value Proposition Undefined; Newness and novelty aspects of having only

looping/moving content in a platform format

Channels Mobile application-based delivery model; Only available

in the United States iOS App Store; Marketing largely

done through Apple Search Ads and Instagram

Customer Relationships High-touch model with active team curation of content on

the platform; questions on scalability of level of dedicated

personal attention required for curation

Revenue Streams None

Key Resources Team’s human capital; Two Sigma Ventures backing;

intellectual property; RLY’s quirky brand

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Key Activities Problem solving; product development; Platform

activities such as user discovery and content curation

Key Partnerships None

Cost Structure Value driven cost model; High fixed cost business with

negligible variable costs as business scales;

Table 1: Current Definition of RLY Business Model using Osterwalder’s Canvas

Quickly scanning this initial mapping of the business model canvas yields a couple of

interesting insights. First, given this paper and the aforementioned authors’ focus on the

importance of designing a compelling value proposition, there is a relative lack of clarity

around what constitutes the value proposition of RLY. Secondly, there has been limited thought

given to the non-end user side of the platform business. While clearly one side of a platform

needs to be built to attract the other, thinking about the any future evolution of a multi-sided

platform requires a deeper understanding of both sides of the platform. And lastly, there has

been no work done to date on potential revenue streams, which ultimately will be required if

the company wants to self-fund its growth and operations. The recommendations as spelled out

in the remainder of this section hope to address some of these key gaps in the current business

model definition through actionable and implementable recommendation.

B. Identify Job to Be Done

The first step suggested by this paper’s Continuous Platform Value Proposition Refinement

Framework was to identify your customer and to understand their wants/desires/jobs to be

done. This paper commends much of the work done so far as RLY has already engaged in

significant work to gain a deeper understanding of their proposed customer base and has

worked closely with their target market to co-develop their product with participation from

end-users in all steps of the creation process. Additionally, RLY has made strides in terms of

customer identification from a demographics perspective as they have narrowed their target

customer segment (albeit still a relatively mass-market audience) to a specific age and

geographic and have worked on building their product set around the wishes and desires of that

specific audience. While all these customer identification efforts are in-line with Osterwalder’s

(2011) business model canvas, there still is the matter of understanding the job to be done that

those customers are hiring RLY to do.

29

To the end of better understanding how and why RLY users use the platform, we

commissioned a user survey to explore several key questions that were integral to business

model definition and selection. While the highlights of the survey are viewable in the

Appendix, the chief reason that users opened RLY daily was essentially look at other people’s

content (Appendix C). This suggests that users are using the service as a means of content

discovery. This is a meaningful revelation, as understanding the core job that users are hiring

RLY to do, helps the RLY team to understand where it should be investing the bulk of its time

innovating. It also distinguishes who is the competition as RLY is not going after the same

target market as social messaging services like Snapchat or WhatsApp, rather discovery

platforms like Instagram or Pinterest. Going one step further, it is also important to understand

they “why” of why a customer is using the app in a specific way. To explore that, I rely on

Voss’s (2014) use of laddering and a means-ends-chain to arrive at the terminal values

associated with social media use. He found that the most significant attributes are

chat/pictures/mobile application, were very closely linked to terminal values such as fun/well-

being/hedonism (Figure 3). While the research was done largely on the millennial population,

it does still hold some explanatory value for why RLY users use the app; chiefly of which being

the terminal value of just having fun.

Figure 3: Voss’s Means-End Chain for Social Media Usage

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The sum of these two key revelations – that people are hiring RLY to discover new content

and that people have a terminal goal of fun – drives this paper’s first recommendation. I

recommend that RLY should reformat its product roadmap to focus on features that are focused

on fun and content discovery. This could take the form of improved categories, the introduction

of searchable hashtags, and the creation of sub-communities based on interests. Additionally,

holding content creation contests would be a quick way to boost fun, engagement, and user

interaction in a manner consistent with the underlying job that users are hiring RLY to do.

C. Identify Value Creation Bucket

With a strong understanding of the customer job to be done, comes the framework’s

recommended next step of identifying opportunities for value creation that could be captured

by the platform. This paper’s framework utilizes Parker’s (2016) typology, where he broke out

four buckets of excess value creation opportunities. It is this paper’s view that RLY is in a

unique position to be able to pursue all 4 of the possible paths here, which is in-line with Kim

& Mauborgne’s (2014) view on Blue Oceans and breaking from the traditional trade-off

mindset that dominates traditional management thinking. Table 2 demonstrates the scope of

opportunities for RLY in table format.

Value Creation Bucket RLY’s Opportunity

Give third parties access to a specific

community

Work to develop active sub-communities

based on specific interests; Example of

partnering with services like TripAdvisor’s

to have a book now feature under pictures

of specific locations in the travel oriented

interested groups

Grant access to content created on platform Become a portal of discovery for people

seeking to view and enjoy all types of

moving content (videos/gifs/live photos);

Network effects create excess value as the

quantity of user-created & RLY specific

content grows

Facilitate connection Launch micro-influencer platform where

influential users can connect with brands

who wish to connect with their audiences in

31

an authentic and transparent manner;

Matchmaking creates excess value for

platform

Value provided through curation Allow for community curation, like a

Reddit trending page tab; This will work to

increase engagement and identification

with the platform as users feel like they

have a say in what the app displays on its

home page and in the trending section

Table 2: RLY’s Value Creation Opportunities

While this paper recommends simultaneous pursuit of these value creation strategies in

parallel, RLY needs to make sure that their core value proposition remains intact for the end

users, i.e. the app must work to offer users a compelling and fun way to discover and consumer

content in a meticulously curated environment. Aggressive pursuit of value capture of these

value creation opportunities could ultimately erode the magic that keeps bringing users back,

so careful thought should be applied to the implementation of these value creation strategies.

This paper recommends to continuously monitor things such as uninstall rates, push

notification toggling, retention, and engagement to ensure that incremental value capture

efforts do not detract from the experience. In similar vein, things should be A/B tested with

smaller segment population to minimize the negative impact on consumer experience as these

value creation and capture strategies are played out.

D. Differentiate Value Proposition

This paper’s custom framework suggests utilizing Kim & Mauborgne (2014) Blue Ocean

strategy piece when it comes to the topic of the execution of differentiating one’s value

proposition. While somewhat generic, Kim & Mauborgne’s “Six Paths Framework” helps for

how to think about redefining a firm’s market boundaries. In terms of high-emotionally charged

application-based businesses like RLY, focused on social media, dating apps, or beauty etc.…,

there is a deeper examination of the 5th path required: the need to look across functional or

emotional value to customers. Often, customers measure and rate competitors based on either

their functional or emotional value depending on the way in which they have been conditioned

to process products from a given industry. In the example of dating apps, people tend to value

the emotional aspects of the service (finding a partner, feeling loved/wanted) higher relative to

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the functional attributes brought by a snazzy UX/UI or similar product-level innovation. Due

to consumer conditioning on how to evaluate competitors in that realm, a new dating app would

likely have a hard time marketing its value proposition around functional attributes like

processing speed or in-app technical bells and whistles. Kim & Mauborgne (2004) argue that

because industries have trained their customers in what to expect from a specific industry, that

there is significant opportunity to create a Blue Ocean if a company is willing to break from

competing on their industries chosen dimension of either functional or emotional attributes.

For an insurgent aspiring social network such as RLY, this would suggest that there is

opportunity in prioritizing some functional attributes in designing its business model despite

consumers largely tending to have been conditioned to value largely more emotional content

from other photo-sharing social networks. In fact, adding functional benefits to the app design

could be the viral hook that drives increased user engagement. This paper recommends then

adding technical features that increase value on both the functional and emotional level. Take

for example the idea of adding an app feature such as an algorithm suggesting songs based on

the content uploaded by a user on a day; The user comes for the emotional connection of

sharing her content and then is followed up with the functional benefit of receiving tailored

music recommendations, which, being a product that is evaluated on emotional basis, can

further improve the emotional value derived by the end-user. And partnering with a service

such as Spotify would further amplify benefits as there is opportunity to draw cross-application

referral traffic between the two services. And while that’s just one interesting example of one

of six possible pathways to blue ocean creation, it’s important to note that value was created

for the buyer on both the emotional and functional levels, which comes, rather paradoxically,

despite the strategic decision to move away from an overt-focus on the emotional side.

E. Monetize

While beyond the scope of this paper’s attempt at synthesis through the Continuous

Platform Value Proposition Refinement Model, the discussion of monetization plays a key role

in business model formation, especially in the case of RLY where they are actively raising

Venture Capital money (and Venture Capitalists have a vested interest in understanding how

they will make their investment back). How will RLY ultimately make money is a key question

that venture capitalists have of RLY’s management despite it being early days for a user-growth

oriented B2C app. It is this paper’s recommendation to try and align the revenue model with

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the underlying value proposition, which I believe has an emphasis on fun and discovery.

Viewing proposed monetization strategies in this light, leads one back to consider Parker’s

(2016) second generic route for platform monetization in charging one-side of the platform for

access.

In the case of RLY, it’s clear that while content creators and end users value their time

spent on the platform, they would likely not pay for such an experience and any attempt to

charge for access would destroy positive network effects. On the flip side, there is significant

room to monetize the excess value created to third parties by providing access to content

creators to those brands that want to engage in a unique and participatory way. RLY should

come up with creative ways to charge for access to third-parties for their growing and vibrant

user base, that does so in a non-privacy intrusive way. Given the core value proposition of RLY

is built around fun, discovery, and Generation Z values such as inclusiveness & positive vibes,

RLY could work with brands and publishers to think of innovative new content that RLY end-

users would want to engage with in a natural way. It could be in the form product giveaways,

starting content campaigns around a new product, or creating brand personas on RLY to

participate in content creation with users. In a similar vein, I see significant scope for adding

functionality to the travel or action categories with book now buttons under content based

around specific locations, artists, or sporting events, and charging those third parties for access

to the communities on a cost-per-click basis. Additionally, allowing brands access to micro-

influencers to conduct product polls on a much smaller and targeted scale also allows for value

to be captured by the platform on a by campaign basis.

F. Challenges

While all the recommendations proposed so far would certainly help to flush out RLY’s

business model definition with the end goal of building a differentiated value proposition that

can provide the bedrock for a sustainable competitive advantage, it’s important to note that

RLY operates in a very dynamic space within social media; customer preferences can change

seemingly overnight in a space wrought by intense competition from both incumbents and well-

funded new interests. Take for example the recent usage declines in TBH, the anonymous

compliment app, that recently was shut down by Facebook after having been purchased only 9

34

months ago8. RLY faces a significant uphill battle in being able to continuously meet changing

customer demands, which is only compounded by the resource constraints that RLY has being

an early stage start-up with only 5 full-time employees.

There also is the difficulty of facilitating the growth of the second side of the platform.

There is an implicit assumption in the proposed business model that brands and publishers will

want to engage with RLY’s end users on these terms. The fact of the matter is that many of

these brands will not engage with network until there is a critical mass of eyeballs to make it

worth their while to invest a portion of their advertising budget into a fledgling platform. This

reluctance to participate from one side of the platform makes it especially hard to grow the

overall platform if one side is waiting for a critical mass while the other side is somewhat reliant

on the facilitated interaction, increased functionality and utility that the other side brings to the

table.

In addition, native advertising, as suggested in the monetization recommendation section,

does carry its on specific breed of risks as Wojdynski’s (2016) work saw that when users find

out native advertisements are in fact sponsored, that they have generally more negative

evaluations of the ad. This could lead to a destruction of the positive feedback loop cycles that

power the platforms growth as organic growth may slow as the result of less word of mouth

referrals due to the hit to the user experience.

8 https://techcrunch.com/2018/07/02/facebook-is-shutting-down-hello-moves-and-the-anonymous-teen-app-tbh-

due-to-low-usage/

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G. Timeline

Figure 4: Timeline of Proposed Recommendations

7. Limitations and Conclusion

Throughout this paper, I have surveyed relevant literature and explored the key concepts of

business model, value proposition, and revenue model design. Within those topics, special

attention was paid to the methodology and processes for constructing the optimal business

model for an internet native business model. This paper utilized Osterwalder (2010) business

model canvas as the starting point for business model definition. With a thorough

understanding of those elements in hand, it zoomed in on the element of value proposition

through the lens of Kim & Mauborgne (2014) with a focus on breaking free from the traditional

Porterian logic of cost/value trade-offs. Key to the discussion on value propositions was the

need for both inimitability and precision in satisfying the customer’s ‘job to be done’ for an

enterprise to use their value proposition as the bedrock for creating a sustainable competitive

advantage. I also then explored the revenue models and monetization strategies in detail

through Parker’s (2016) 4 path analysis. Adding all these together, I then attempted a synthesis

to provide a framework on which recommendations could be made to solve RLY’s issue of

business model generation. That said, while highly applicable to the case company, there are

some key limitations of the framework that deserve to be addressed, which I will touch on in

the following paragraphs.

Continous

- User surveys

- A/B Testing

- Validated Learning

- Value proposition refinement

- Embrace pivots when data points to dead end

Near Term

- Reformat product roadmap to focus on fun & discovery features

- Launch community curated pages to improve user ownershp and identificaiton with teh platfomr

-Encourage sub-communtity formation based on interest to stimulate network effects on a smaller scale

Long Term

- Explore partnerships with the likes of TripAdvisor to capture value created through providing access to specific sub communities

- Pursue blue ocean through looking across funcitonal & emotional appeal (adding bots to focus on positive interaction)

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Magretta (2002) once wrote that a “business model’s great strength as a planning tool is

that it focuses attention on how all the elements of the system fit into a working whole”. Against

that standard, the Continuous Platform Value Proposition Refinement Model custom

framework admittedly falls short of the task of helping to describe the entire system given its

overt focus on the value proposition and methods of value capture/delivery. Thinking in terms

of Osterwalder’s (2010) business model canvas, the custom framework is relatively light on

the business model elements of channels/cost structure/resources to name a few. The

framework is instead focused on getting start-ups to think about not only their value proposition

but also the processes the will employ to validate and refine that core business model element.

That said, the model is not meant to be utilized in the same fashion as the business model

canvas (custom framework argues for an emergent strategic execution versus a more deliberate

and pre-planned strategy) but more of a working framework to help continuously refine,

through validated learning, the core of any business model in its value proposition.

In addition to limitations to the scope of its descriptive power, the fundamental method of

validated learning has its own set of intricacies and limitations. Namely, the process of

validated learning requires that management be able to identify and select the best KPIs on

which to measure themselves. For a start-up without a fully-baked business model, identifying

the most pertinent KPIs is somewhat of a ‘chicken and the egg’ dilemma as one doesn’t know

what the best measures of success are going to be. Choosing the wrong metrics to drive the

process of validated learning can be a deadly sin, especially considering start-ups have a limited

financial runway. In addition, there is also the question of how actionable KPIs are, that is to

see is it demonstrated that there is a clear cause & effect or is it simply correlation without

causation. In fairness, this topic of pertinent KPI selection is a rather universal one that plagues

even mature public companies (just look at the degree of difficulty involved in getting boards

to agree on the right metrics to gauge executive success and pay) but is exceedingly important

for start-ups to be able to be confident their iterative build-measure-learn loops are pushing

them towards business success rather than towards a vanity metric without much true business

worth.

In sum, this report worked to provide a broad overview on the overarching research

question of how to design the optimum business model for an internet-native start-up. The

custom framework, despite the aforementioned limitations, provides a relevant synthesis that

works to define a clear and practical methodology for value proposition design and refinement

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for an aspiring platform business such as the case company RLY. From this framework, I was

able to draw actionable recommendations such as use reformatting the product roadmap to

focus on fun and product discovery features given it not only most closely aligns with the ‘job

to be done’ users are using the app for, but it also provides an opportunity for excess value

creation that can be captured by the platform. In terms of value capture and ultimate

monetization of that bucket of excess platform value, this paper recommended the most logical

monetization route for RLY as Parker’s (2016) second path of charging one-side (advertisers)

of the platform for access. In a similar vein, I also recommended that RLY increase its business

development efforts to explore partnerships with outside partners in order create more excess

value for the platform to capture through ultimately providing access to sub-communities built

around specific interests. In short, these recommendations provide a solid base for RLY in their

quest to design and build the optimal business model for their internet-native platform business.

8. Appendix

A. RLY Brand

38

B. Osterwalder’s Business Model Canvas Template

C. RLY Product Survey Highlights

39

D. RLY Competitor Survey Highlights

40

9. Bibliography:

• Anderson, J. C., Narus, J. A., & Van Rossum, W. (2006). Customer value propositions

in business markets. Harvard business review, 84, 1-4.

• Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of

management, 17(1), 99-120.

• Casadesus-Masanell, R., & Ricart, J. E. (2010). From strategy to business models and

onto tactics. Long range planning, 43(2-3), 195-215.

• Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). Know your

customers'" jobs to be done". Harvard Business Review, 94(9), 14.

• Eisenmann, T., Parker, G. and Alstyen, M. (2006) Strategies for two-sided markets.

Harvard Business Review, October 2006.

• França, C. L., Broman, G., Robèrt, K. H., Basile, G., & Trygg, L. (2017). An approach

to business model innovation and design for strategic sustainable development. Journal

of Cleaner Production, 140, 155-166.

• Kim, W.C., & Mauborgne, R. (2004). Blue ocean strategy. Harvard business review,

82(10).

• Kim, W. C., & Mauborgne, R. A. (2014). Blue ocean strategy, expanded edition: How

to create uncontested market space and make the competition irrelevant. Harvard

business review Press.

• Ladd, T. (2016). The limits of the Lean Startup Method. Harvard Business Review.

41

• Magretta, J. (2002). Why business models matter.

• Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for

visionaries, game changers, and challengers. John Wiley & Sons.

• Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform Revolution:

How Networked Markets Are Transforming the Economy and How to Make Them

Work for You. WW Norton & Company.

• Porter, M. E., & Michael; ilustraciones Gibbs. (2001). Strategy and the Internet.

• Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation

to create radically successful businesses. Crown Books.

• Seddon, P. B., Lewis, G. P., Freeman, P., & Shanks, G. (2004). The case for viewing

business models as abstractions of strategy. Communications of the Association for

Information Systems, 13(1), 25.

• Shafer, S. M., Smith, H. J., & Linder, J. C. (2005). The power of business models.

Business horizons, 48(3), 199-207.

• Sheehan, N. T., & Vaidyanathan, G. (2009). Using a value creation compass to discover

“Blue Oceans”. Strategy & Leadership, 37(2), 13-20.

• Teece, D. J. (2010). Business models, business strategy and innovation. Long range

planning, 43(2-3), 172-194.

• Voss, R., & Schneider, V. (2014). Using laddering to understand the social media

network Google+. European Journal of Business and Management, 6(10), 121-130.

• Wirtz, B. W., Schilke, O., & Ullrich, S. (2010). Strategic development of business

models: implications of the Web 2.0 for creating value on the internet. Long range

planning, 43(2-3), 272-290.

• Wojdynski, B. W., & Evans, N. J. (2016). Going native: Effects of disclosure position

and language on the recognition and evaluation of online native advertising. Journal of

Advertising, 45(2), 157-168.

• Zhu, F. and Iansiti, M. (2012) Entry into Platform-based Markets. Strategic

Management Journal, 33, 88 - 106