The article in a nutshell
The application of blockchain technology has to be understood by a much larger and diverse audience before it can realize its potential. One aspect is to make sense of how the blockchain landscape is shaping up – what are the value vectors, “industries” and players in each one. The Crypto Assets Map aims to provide an overview of this landscape, clustering the top 100 assets per market capitalization in three key value vectors: Currency, Platform and Vertical application. Use it to improve your understanding of the blockchain landscape or to educate others about blockchain and related crypto assets. Use it to scout players in the industries you are most interested in or to assess your portfolio. Feel free to share The Crypto Assets Map – but remember: this is not investment advice and is provided as-is, without any guarantee about its correctness nor its adequacy to make investment decisions
Disclaimer: this is not investment advice and I am not your financial advisor. You are the only responsible for making the due diligence of any asset you are interested in investing and the only responsible for this decision. In no event I hold any accountability for your own investment decisions. This information is provided as-is, without any guarantee about its correctness nor its adequacy to make investment decisions.
Introducing The Crypto Assets Map
I have been a distant observer of Bitcoin and blockchain in general for a long time. It has been only about 1 year ago though that I started studying and investing seriously. If you are reading this, chances are that you also believe – or at least suspect – that this technology and these newly created crypto-based assets (which I will call crypto assets for now on) have the potential to make profound changes to entire industries.
This process will take time though and requires an active effort from early adopters to propagate the technology and help others make sense of it. Many of them write about the technical aspects of blockchain; there is an at least equal number of influencers discussing investment opportunities represented by these crypto assets. You can even find authors focusing on the more philosophical aspects of decentralized versus centralized systems or the politics driving these decentralized systems. My humble contribution will focus on another, complementary perspective – the intersection of this technology and how / where it is finding applications in the real world.
The first product of this contribution is The Crypto Assets Map you can see here. Why we need something like this? As per the CoinMarketCap website, there are 1,153 crypto assets available. The sheer number of assets makes it difficult for anyone but the most involved person to grasp what is the raison d'être of each crypto asset – at least at any level more specific than the “digital cash” analogy.
The Crypto Assets Map represents which clusters these blockchain-based assets are forming – which organizations / teams are working on which challenges and opportunities and how market capitalization splits across these clusters.
A brief note about terminology – for the sake of simplicity I refer to the underlying technology of these assets as “blockchain” even though “distributed ledger technology” is probably a more accurate term. And as mentioned before I am giving preference to “crypto assets” rather than the most commonly used “crypto currencies” because it more accurately expresses the idea that these assets are in fact a new (and still largely unrecognized as such) asset class.
The development process
I must admit that when I committed myself to complete this first version of The Crypto Assets Map I did not fully anticipate its complexity.
Every attempt to create a taxonomy requires some decisions that will not be supported by 100% of users of this taxonomy. This case is not different - I am sure that people would add, remove or name differently some clusters; similarly, I am sure that some assets would be re-classified depending on one’s perspective and understanding of the underlying value driver for a particular asset. To be clear: I do not claim to have perfected all clusters and where each asset should be placed - without a doubt improvement will take place now that this first version is out. I will be listening to the feedback and incorporating it to the extent that it is logically sound and advances the understanding of the crypto assets landscape.
A second aspect is that classifying many of these assets in a cluster is not as clear-cut as one might like it to be. This poses multiple interesting challenges. One case relates to assets enabling Dapps (decentralized applications). Often they have an initial use case lined up, which immediately raises the question of whether it makes more sense to classify it under the immediate use case being developed or under a more general, encompassing cluster.
Just as an illustration of this case, let’s take the case of GXShares. It puts itself forward as “the data trading network” with “plentiful of business application scenarios to release data’s due (true?) value”. It then describes its first Dapp, focused on facilitating credit verification. A decision has to be made: is GXShares a player in the broader (and less defined) business of “data trading” or in the narrower (and more tangible) business of credit scoring? The rule of thumb adopted was to pick the broader business cluster, for a number of reasons. First, many of these projects are at early stages and we should expect a good number of them to pivot as they mature. Second, using the narrower business might adversely affect the understanding of the potential represented by the project - it is natural to pursue a narrow use case to demonstrate new technology, but this is far from being the end point of the technology.
It goes without saying that having an asset allocated to a particular category is not a confirmation of its quality, fit for purpose or ability to delivery. It only represents what seems to be the main value vector of the asset. A very illustrative case can be found in the privacy-oriented cryptocurrencies cluster. The extent that each of these coins are effectively “private” is cause for heated debates. I do not make any qualification about the effectiveness of the underlying technology of any of these coins - The Crypto Assets Map only highlights that these coins have “privacy” as a key element in how they communicate value.
It is also important to stress that being in the top 100 is no guarantee that these assets will be successful in the future. We should err on the side of caution and assume that being in the top 100 tells one nothing about the relevance of the use case, its market potential, competence of the team behind the project, quality of the code developed, maturity of the technology adopted or the community’s ability to steer decisions. Let me emphasize this point with data: during the research to create The Crypto Assets Map I came across multiple coins that lost 75%+ of their market value, which made them fall off the top 100 list in just a few weeks. Given that the 100th largest asset has only 0.05% of the market cap of the largest asset, we should expect a significant rotation in assets listed to continue for the time being.
One last aspect worth mentioning relates to how to present such an enormous amount of information and details. I have opted for circles proportional to market cap but other visualizations were considered. The acid test lies on whether it triggers the reader’s interest to explore the data points and gain new insights.
This was a long post; I wanted to be sure that The Crypto Assets Map and the ideas behind it were properly introduced. In a next post I will discuss some of the insights that I gained in the process of creating this first version. In the meantime, let me know your thoughts and which insights you have gotten from it.
As I mentioned earlier, completing The Crypto Assets Map took a significant effort. I would like to know whether you found it valuable - so please upvote in case you got value from it and would be interested in updates and other analyses.