Warren Buffet of Berkshire Hathaway has helped popularize the concept of “economic moats” over the last 20 years. Morningstar, an investment research firm, was amongst the first to formalize and systematically leverage economic moats as an investment strategy (in early 2000s). Based on their research, Morningstar identified five sources of economic moats (in descending order of their importance):
(1) Intangible assets (patents, brands, etc)
(2) Sustainable cost advantage
(3) Switching costs
(4) Network effects
(5) Efficient scale.
Subsequent analysis done by Venture Capital firms (VCs) investing in digital space has, somewhat surprisingly, yielded similar four mechanisms for value creation and defensibility: network effects (the predominant value creator) followed by scale, brand, and lock-in.
These economic moats / value creation mechanisms have been investigated and studied deeply from capital allocation perspective — esp. for investment into mature and late-stage companies. It has been shown that moats-based capital allocation strategy (esp. when combined for stock valuation) provides higher return on invested capital (RoIC). However, it is not clear how these value creation mechanisms can be built in a systematic way. There are no frameworks that can be used by startups to explore and build these value creation mechanisms.
In the rest of the article, we provide an overview of the framework that can be used by startups to build these value creation and defensibility mechanisms. Towards this, we first define two parameters that underlie the value creation drivers in the Internet era. We then use these to outline how startups can build the value creation drivers (we refer to these as “Engagement boosters”) in a systematic manner. Finally, we explain how any company can overlay network effects (over their core products) to amplify value creation and to strengthen the defensibility.
Over the course of working with hundreds of startups, we have found that there are two parameters that underlie value creation engine:
Analogous to the moats and value creation mechanisms mentioned above, we define the value creation drivers to be:
In the following, we first give an overview of the two parameters. Next, for the above value creation drivers, we define “engagement boosters”, which are products/features that help a company create value and build defensibility. Based on these, we present a framework that can be used by entrepreneurs to build the boosters in a systematic manner.
All activities done by people — whether in personal or work context — can be viewed from the perspective of the “Frequency of activity” and “Importance of activity”. Let’s start by defining the scale for “frequency of activity”. Tasks that correspond to daily (or a few times a week) use-cases are considered to have “high” frequency of activity; weekly (or a few times a month) use-cases have “medium” frequency of activity; all other use-cases have “low” frequency of activity. The scale for “importance of activity” can be defined likewise. Tasks that have large implication and, therefore, require consultation with other stakeholders (such as family members or corporate committees) can be classified to have “high” importance of activity; tasks that trigger users to diligently evaluate pros/cons amongst alternatives as “medium” importance; utility-like tasks that can be performed without much thought are “low” importance tasks.
Based on this, we can classify problems that are fairly frequent (with weekly or higher frequency) as “frequent problems” and problems that are important but not as frequent as “important problems”. The following “Engagement Graph” shows these categories of problems:
Engagement Graph below shows various personal activities. First-mile and last-mile commute, food ordering, cab service are amongst the most frequent activities (with more than once-a-day frequency). B2B and SaaS activities and e-commerce have approximately once-a-week frequency and low importance. Education-related activities also have once-a-week frequency but higher importance while activities such as personal finances (including investments and lending), travel for leisure, real-estate transactions, and healthcare-related activities have much lower frequency but high importance. On the top-right, you can notice social media and social networks — these activities are both fairly frequent and fairly important (and, therefore, occupy enviable top-right position in the Engagement Graph):
Based on our experience, we have observed that startups solving frequent problems need to focus on different set of things as compared to startups solving important problems.
Given that the “frequent problems” are not very important (in the sense that there are alternatives — even though inferior — available), startups solving frequent problems often need to focus on acquiring more users and iterating quickly to ensure that the company is able to improve quickly in order to meet their customers’ needs. On the other hand “important problems” — due to their very nature — require more trust to be built with users. Therefore, it is important to focus on activities (such as curation of service providers, emotions-aware design, end-to-end customer experience, etc.) that help build trust with potential users.
Based on our experience, we have observed that it is best to classify customer journey into three distinct phases: Invite, Engage, and Connect.
A company that builds emotional connect with its customers inevitably triggers online and offline word-of-mouth buzz in favor of the company. Digital footprints left by satisfied and happy customers makes it easier for the company to create initial positive outlook towards the product amongst the next of customers. In other words, Connect-triggered activities helps to improve the next round of Invite phase. Since every iteration helps improve subsequent iterations, it will be appropriate to represent customer journey using the “spiral” metaphor (which is intended to be captured by the following figure):
Recall that we mentioned that there are four value creation drivers: Scale, Habit, Brand, and Network effects. It can be noticed that the Scale, Habit, and Brand drivers correspond to the three phases of customer journey (Invite, Engage, and Connect), respectively. In other words, Invite underlies the Scale driver, Engage underlies the Habit driver, and Connect underlies the Brand driver.
With this insight, one can visualize that it is possible to build these four value drivers in a product-led way. (In other words, startups don’t need to run classical brand campaigns in order to build a strong “Brand”.) We refer to the product-led activities that help to build the four value drivers as “engagement boosters”.
Product-led engagement boosters can be built by recognizing that these boosters depend on the Frequency of activity and the Importance of activity.
Following diagram shows the Engagement Graph with these characteristics of these three boosters:
The figure above provides an indicator towards how startups can build these boosters. How can this be done? The easiest way is to build products/features with the right frequency and importance characteristics. A startup can consciously add products/features with the relevant characteristics, companies to build various boosters and, thereby, to strengthen and sustain their growth.
In other words, when Invite, Engage, and Connect phases of customer journey are supported and enriched with products and features with the right characteristics (“engagement boosters”), they help to build and strengthen Scale, Habit, and Brand moats, respectively. These boosters not only help create more value but also help to strengthen defensibility for the startups.
Network effects are also an example of the product-led boosters — but with one important addition: direct user involvement. If product can get users directly involved during Invite, Engage, or Connect phases, it would not only make the three boosters self-sustaining but super-charge them as a result of user growth (since that should increase user involvement automatically). This is the lure and the strength of the network effects: they promise ever-improving product and customer experience!
We represent user’s involvement during the three phases of customer journey separately as the “Involve” phase:
Direct users involvement in the three customer journey phases results in three different kinds of network effects:
We will look at them each of these in more depth subsequently; for the time being, we outline their main characteristics:
Viral networks are built when current users invite new users to join the network. There are two types of viral networks: (1) acquisition-based viral loops and (2) engagement-based viral networks.
Exchange networks are built when current users engage with each other to improve the experience for everyone. There are three types of exchange networks: (1) marketplaces & market networks, (2) platform-based networks (including metadata networks and SaaS-enable Marketplaces — SeMs), and (3) platforms with n-sided network effects (including content & data networks).
Connected networks are built when current users help to build and deepen emotional connect for everyone. There are three types of connected networks: (1) social & collaboration networks, (2) community-based networks, and (3) marketplaces with collaboration & same-side network effects.
Even in the absence of direct user involvement, weaker forms of network effects are possible. For example, users generate valuable metadata during the course of their engagement with products. This metadata (aggregated over current and past users) can be used to provide better experience to new users. For example, based on past buyer journeys, companies can improve Invite for future users by handling visitors and leads more effectively.
Network effects that arise due to indirect involvement of users correspond to the weakest form of network effects and can be referred to as “Indirect Networks” (and referred to as Level 4 in the figure below).
Viral networks, Exchange networks, and Connected networks are progressively stronger forms of network effects (referred to as Level 3, Level 2, and Level 1, respectively, in figure above).
Once again, different types of network effects correspond to three phases of customer journey — each phases with progressively deeper association of users with company’s products. User involvement also, as a result, progressively becomes deeper across these three phases — resulting in increasingly strong network effects.
It is important to emphasize that, historically, it was assumed that network effects are dependent on product’s category in the sense that a company can leverage network effects if and only if the category intrinsically is dependent on marketplace dynamics, community-based interactions, etc. By identifying different types of network effects and their dependence on different types of direct user involvement, we have explained how companies — even those that don’t have natural marketplace mechanics or social networking dynamics — can thoughtfully and systematically craft various types of network effects into their products/services.
We have observed that the three moats/boosters (scale, habit, and brand) are correlated with the three phases of customer journey. We have highlighted that network effects are also an example of the active product-led boosters that can be unlocked via direct users involvement during the three phases of customer journey. In addition, the spiral nature of customer journey gives rise to the implicit network effects.
Product-led user involvement in each of the three phases of customer journey gives rise to three different types of explicit network effects. Direct user involvement helps convert engagement boosters into energized boosters wherein the boosters continually become more energized and stronger with growing number of users.
We have shown that product-led engagement boosters can be built by identifying relevant category-specific tasks (undertaken by target users) with specific frequency and importance of engagement characteristics: high frequency and low importance tasks for scale boosters, medium frequency and medium importance tasks for habit boosters, and high importance and low/medium frequency tasks for brand boosters. Entrepreneurs can use the framework to build these boosters and network effects in a structured way to create more value and to build sustainable competitive advantage in a systematic manner.
Product-led boosters and network effects become stronger with higher product usage and increasing user-base. By continually moving the product into higher orbits, engagement boosters convert customer journey loop into a spiral: a Growth Spiral that helps companies to create increasingly more value and build stronger defensibility in an efficient and sustainable way!