Startups in the non-fungible token (NFT) industry utilize distributed ledger technology to develop products, which aim at creating an immutable link between digital or digitized objects (e.g., art, music, etc.), creators and potential buyers. Based on an analysis of industry-agnostic and industry-specific startup evaluation literature, semi-structured interviews and digital trace data sources, an initial set of 35 unique evaluation aspects for NFT startups was collected. The list covers aspects of the individual, organizational and environmental dimension. Intersections between different information streams imply that existing literature contains relevant evaluation aspects. For example, product innovativeness, and structure and quality of the founders’ professional network were identified in all information streams. Interestingly, 17 aspects are not literature based, which implies two things: First, from a practical perspective NFT startups share evaluation aspects, which have not been covered by research papers yet. Second, sources of digital trace have the potential to enrich industry-agnostic and NFT-related startup evaluation literature. In addition, the findings emphasize the need for researching aspects and frameworks specifically targeting business models of information economies. Especially in context of B2C NFT business models, this article suggests to use data-driven aspects e.g., based on Discord or on-chain metrics, to extend and enrich traditional company data.

Infographic

Beyond the NFT hype - Evaluation aspects for startups in the non-fungible token industry

What is an NFT?

In its most common form, an NFT is a unique, digital record in a distributed ledger representing digital or digitized objects, such as art, music or in-game items. This digital representation of shared value, its transaction history and the account assigned to it are cryptographically secured and stored on a blockchain. Because of their characteristics, they are being praised to be the solution for “the inherent problem digital content has: The link between content and its original author is very difficult to keep” (Pérez‐Solà & Herrera‐Joancomartí, 2020, p. 1).

Figure 1: Difference between fungible and non-fungible¹

Fungibility is the major difference between NFTs and fungible tokens like Bitcoin or Ether. For example, an account can exchange five arbitrary Bitcoin for five other arbitrary Bitcoin like it would exchange a €5 bill for five €1 coins. In financial terms the outcome is fungible as an account stores five arbitrary Bitcoin or five Euro before and after the transaction. Because every NFT has its own unique identifier, one cannot exchange one NFT for another and keep the exact same representation of value, even if the financial value before the transaction would be the same. For example, one cannot exchange a painting worth €500 on the market for another painting worth €500 on the market and keep the exact same representation of value (see Figure 1).

NFT startup use cases experiencing already adoption

As of 2022, NFT startups target products at the intersection of human urges i.e., gaming, collecting and signaling (see Figure 2).

Figure 2: NFT startup business cases

1. NFT projects in the art and collectibles category aim to create and preserve scarcity of digital assets and enable users to track ownership on the respective blockchain (A. Park et al., 2022; Rehman et al., 2021). An example is Dapper Labs’s collectible product “NBA Top Shot”. The product allows users to collect, buy and sell tokenized basketball highlights (Dapper Labs, n.d.).
2. With regards to gaming and metaverse, developers follow the idea of creating, enhancing or extending virtual worlds. They utilize NFT technology to e.g., build in-game items or virtual real estate, whereby ownership is tracked on a blockchain and peer-to-peer transactions are enabled (A. Park et al., 2022; Rehman et al., 2021). Examples are gaming ecosystem Axie Infinity (Sky Mavis, n.d.) or metaverse Decentraland (Ordano et al., 2017).
3. Last, utility and DeFi use cases aim at offering alternative solutions to existing services (A. Park et al., 2022; Rehman et al., 2021). For example, True Names (n.d.) offers unique user names, which are stored on the Ethereum blockchain and through which decentralized websites can be accessed. Another example is Drops, a lending protocol that provides users with NFT-backed loans (Drops DAO, n.d.).

Challenges with respect to NFT startup evaluations

In general, startups are difficult to evaluate because of three main reasons: First, due to the young age of startups, little or no business activities from the past are available (Fenwick & Vermeulen, 2015). Second, startups usually develop new products, which makes it difficult to estimate a startup’s success (Freeman & Engel, 2007*).* Third, private businesses are not obliged to report company data (e.g., financial reports) as detailed and as frequently as publicly traded firms (Miloud et al., 2012).

Venture capital investors have paid multiple billion U.S. dollar valuations to enter into the NFT market. However, evaluating NFT companies is even more complicated due to the following difficulties (see Figure 3).

Figure 3: Challenges with respect to NFT startup evaluations

1. Controversies associated with token-based products e.g., the Instagram account of Bored Ape Yacht Club (BAYC) was hacked and abused to steal NFTs worth $3 million from user accounts.
2. NFT market shows characteristics of a bubble e.g., Maouchi et al. (in press) found an explosion of NFT prices using COVID-19 cases, internal and external factors, as well as investor and user sentiment as predictors.
3. Lack of public market valuations: As of November 10th, 2021, no NFT-related project is publicly listed on a regulated stock exchange.
4. Difficulties in aligning incentives of ecosystem members: Venture capitalists often hold a double digit share in NFT-related companies, which claim to contribute to a decentralized web. For example, early backers of Yuga Labs, the developer of BAYC, hold 14% of ApeCoin DAO.

Applied research methodology

The research area of NFT startup evaluation aspects has received almost no attention by researchers compared to areas covering e.g., technical development of NFT use cases. Therefore, initial findings and best practice frameworks do not exist. In addition, a purely quantitative study could not be justified due to the young age of the NFT startup ecosystem and frictions in existing centralized databases. For those reasons, a three-fold research approach was decided to be most useful to exploratively research NFT startup evaluation aspects and to gain insights from different perspectives. It covered three different information streams i.e., literature, expert interviews and digital trace data, but its complexity was limited due to its predefined scope. It is illustrated in Figure 4.

Figure 4: Applied research methodology

The review scope was extended by two research areas: research covering industry-agnostic startup evaluation aspects, and studies investigating either evaluation aspects of so-called initial coin offerings (ICOs) or evaluation aspects of startups offering a blockchain-based product. This was justified by the fact that NFT startups offer a blockchain-based product and have used ICOs to raise funds in the past (Miller & Bloomberg, 2022).

Results

The collected aspects from different information streams are separated into the aforementioned three dimensions: individual, organizational, and environmental. Figure 5 lists the findings.

Figure 5: Collected aspects per information stream and dimension

Sources of digital trace to enrich NFT startup data

In general, there are two different ways of accessing digital trace data: First, people can either collect the data themselves through an automated (e.g., web scraping, APIs, etc.) or manual approach, or rely on solutions of specialized service providers. Based on the aforementioned approach, 15 unique trace data sources were identified. Figure 6 shows the clusters they have been separated into.

Figure 6: Identified clusters of digital trace data sources

Intersections between information streams

After merging the insights from different information streams, 35 unique aspects were added to the results table. Seventeen aspects are based on intersections of at least two different information streams as shown in Figure 7. Two evaluation factors were found in all information streams: structure and quality of founders’ professional network, and product innovativeness.

Figure 7: Intersections between different information streams

Highlights

Figure 8 describes the highlights after comparing the results of different information streams.

Figure 8: Highlights of identified evaluation aspects

Final checklists for evaluating NFT startups

After discussing the relevance of identified aspects in the context of NFT startups, the individual dimension should cover three categories: experience and skills of the employees with a focus on founders, structure and quality of the founders’ professional network, and technology expertise in the management team.

On the organizational level, eight categories are considered relevant: legal form, product innovativeness, product attributes and utility, team diversity, ability to acquire and manage financial resources, prior investors, network effects, and differentiation between B2C and B2B business model.

Last, in the environmental dimension, product perception, market potential, and competition have to be evaluated. If the evaluation object develops an B2C product, user communities, transaction history, and transaction volume are particularly relevant.

In addition, the process is enriched by digital trace data sources. On the one hand digital trace data are used to express evaluation aspects through proxies, on the other hand they can also be used to calculate a sentiment score from users and investors. This is especially important for B2C NFT startups. Figure 9 provides an overview.

Figure 9: Overview and final checklists for evaluating NFT startups

Conclusion

This article does not aspire to determine an exact valuation, but rather inspire practitioners and researchers in investigating certain areas of NFT startups and evaluation in more detail, such as frameworks to measure and evaluate the health status and dynamics of NFT startup communities. In addition, it provides an overview of digital trace data sources, which can be further developed and utilized in the context of quantitative and qualitative studies. This forms a starting point and aims at connecting related research with practice-oriented insights.

Overall, the topic is still young and poorly researched, and there are many open questions with respect to NFT startup evaluations, which have to be addressed in the future. Nevertheless, it is interesting to think about the subjective value theory: What does value mean? Humans assign value to objects they think that have value. This is also the case for NFT products and startups developing them. The probability is high that many NFT projects might fail eventually. However, it is important to understand that it is not the best technological setup that wins the market. It is the setup, which acquires most of the users. Therefore, product perception, innovativeness and laws of information markets, such as Metcalfe’s law, should be in the focus of NFT startup evaluations.

In addition, entrepreneurs and community managers have to convince user and investor communities that they can execute their strategy and deliver an NFT product with long-term success and utility. In that case, rule-of-thumb valuations e.g., based on the number of Twitter followers or Discord members, and the founders’ professional network might give a better understanding of an NFT startup’s value than comparing technical details between NFT products. In information economies it is all about “winner-takes-all” markets, and finding trade-offs between risk and opportunity.

References

Dapper Labs. (n.d.). NBA Top Shot introduction. Dapper Labs, Inc. Retrieved May 01, 2022, from https://nbatopshot.com/infographic

Drops DAO. (n.d.). Drops introduction. Drops DAO. Retrieved May 01, 2022, from https://docs.drops.co/dropsdao/introduction

Fenwick, M., & Vermeulen, E. P. M. (2015). The new firm: Staying relevant, unique and competitive. European Business Organization Law Review, 16(4), 595–623. https://doi.org/10.1007/s40804-016-0040-4

Freeman, J., & Engel, J. S. (2007). Models of innovation: Startups and mature corporations. California Management Review, 50(1), 94–119. https://doi.org/10.2307/41166418

Maouchi, Y., Charfeddine, L., & El Montasser, G. (in press). Understanding digital bubbles amidst the COVID-19 pandemic: Evidence from DeFi and NFTs. Finance Research Letters, Article 102584. Advance online publication. https://doi.org/10.1016/j.frl.2021.102584

Miller, H., & Bloomberg. (2022, March 20). Bored Ape’s new ApeCoin puts NFTs’ power problem on display. Fortune Media. https://fortune.com/2022/03/20/bored-apes-new-apecoin-puts-nfts-power-problem-on-display-andreessen-horowitz-animoca-brands/

Miloud, T., Aspelund, A., & Cabrol, M. (2012). Startup valuation by venture capitalists: An empirical study. Venture Capital, 14(2–3), 151–174. https://doi.org/10.1080/13691066.2012.667907

Ordano, E., Meilich, A., Jardi, Y., & Araoz, M. (2017). Decentraland white paper [White paper]. Decentraland Foundation. https://decentraland.org/whitepaper.pdf

Park, A., Kietzmann, J., Pitt, L., & Dabirian, A. (2022). The evolution of nonfungible tokens: Complexity and novelty of NFT use-cases. IT Professional, 24(1), 9–14. https://doi.org/10.1109/MITP.2021.3136055

Pérez‐Solà, C., & Herrera‐Joancomartí, J. (2020). BArt: Trading digital contents through digital assets. Concurrency and Computation: Practice and Experience, 32(12), 1–24. https://doi.org/10.1002/cpe.5490

Rehman, W., Zainab, H. e., Imran, J., & Bawany, N. Z. (2021). NFTs: Applications and challenges. In Y. Al-Laham, A. Shaout, E. Abuelrub, G. E. Ibrahim, M. Elammari, M. Odeh, O. Badaway, T. Taha, M. Ayashe, & M. Kheralllah (Eds.), Proceedings of the 22nd International Arab Conference on Information Technology (ACIT 2021) (pp. 566–572). IEEE. https://doi.org/10.1109/ACIT53391.2021.9677260

Sky Mavis. (n.d.). Axie Infinity introduction. Sky Mavis PTE. LTD. Retrieved May 01, 2022, from https://whitepaper.axieinfinity.com/

True Names. (n.d.). Ethereum Name Services introduction. True Names Ltd. Retrieved May 01, 2022, from https://docs.ens.domains/

[1]: Dmytro Synelnychenko from https://stock.adobe.com, mpanch from https://stock.adobe.com, https://www.guyhepner.com/product/cineol-by-damien-hirst/