How do Web3 brands gain recognition and market value when online communities help shape their development? Elissar Toufaily, Associate Professor of Digital Marketing at De Vinci Higher Education, addresses this question in research published in the European Journal of Marketing, examining how social media conversations influence brand awareness, desirability and valuation.
The findings offer a basis for understanding how consumer participation, digital assets and marketplace activity interact, with practical implications for marketing professionals.
How brands emerge in decentralised digital ecosystems
The paper, “Decentralised branding: electronic word-of-mouth (eWOM), market dynamics and brand value in Web3”, examines brands that originate within Web3. These digital environments use blockchain technologies and enable ownership and participation through distributed communities.
In this setting, users contribute to how a brand becomes known, how desirable it appears and how its assets are valued. Discussions on social media become part of the process through which brand value develops.
The research focuses on electronic word-of-mouth, or eWOM: the opinions, comments and exchanges that circulate online about a brand. It considers how these conversations relate to consumer interest and the prices of brand-associated non-fungible tokens (NFTs).
Combining expert interviews and marketplace data
The research combines two studies. An exploratory phase draws on interviews with Web3 experts to investigate how brands emerge in decentralised environments.
A second phase uses econometric analysis to examine 13 million tweets relating to seven Web3-native brands, alongside 315 million NFT transactions on OpenSea.
Combining these sources lets researchers examine relationships between online discourse and marketplace activity. The study considers both the volume of eWOM, meaning the amount of conversation, and its valence, meaning the positive or negative tone of those exchanges.
Three layers of decentralised brand value
The findings identify three layers through which brand value forms: an asset-based layer, a network-based layer and a marketplace-based layer.
Together, these layers provide a framework for examining the digital assets associated with a brand, the networks participating in its development, and the trading activity through which market valuations emerge.
As the abstract states, “decentralised branding empowers users and online communities to shape Web3 brand value.”
For managers, this framework broadens branding analysis to include community behaviour and marketplace signals. A brand’s development depends partly on exchanges and actions undertaken by participants across its ecosystem.
When positive conversations signal hype
The study finds that the volume and tone of eWOM each independently influence consumer awareness, desirability and marketplace value.
Their interaction can nevertheless produce counterproductive effects. Excessively positive discourse may also signal hype, reducing perceived credibility in speculative digital markets.
This finding calls for careful interpretation of social media metrics. A growing number of enthusiastic posts can amplify a brand’s visibility while also raising questions about speculative overvaluation.
A practical implication is to assess conversation volume and sentiment alongside trading activity. For brand managers, interpreting the relationship between these indicators can support more informed judgements about market interest and credibility.
Connecting digital marketing, data and managerial judgement
These questions connect with EMLV’s approach to combining management education with technological knowledge and critical analysis. Understanding digital markets involves assessing how platforms operate, interpreting data and considering how collective behaviour affects business decisions.
The school’s Digital Marketing & Data Analytics specialisation, delivered jointly with IIM Digital School, combines digital strategy with subjects including web analytics, Python, SQL and statistics for marketing. These areas develop skills relevant to analysing relationships between online activity and commercial outcomes.
The study also establishes clear boundaries for interpreting its findings: it covers seven Web3-native brands during a bull market. Testing the framework during falling markets would help assess how these relationships change under different trading conditions.
Learn more about EMLV’s Digital Marketing & Data Analytics specialisation.
