1. Two pillars of providing attention information in the crypto market High-quality attention information in the cryptocurrency market plays a key role in supporting decisions ranging from more than just news — it helps form marketing strategies, list new assets, and make multi-billion-dollar investment decisions. Market participants constantly crave 'alpha' — information that gives them an edge in uncertainty. To meet this demand, various Web3 information aggregation and analysis tools have emerged. Currently, there are two major approaches leading the way in capturing and providing measures of attention in the crypto ecosystem. One is social-based cases that display market interest flows intuitively and near real-time, and the other is on-chain data-based cases that precisely track actual behaviors and capital flows through on-chain data. 1.1 Social-based: enables fast trend discovery but information can be distorted Kaito, classified as part of InfoFi, is an information platform that collects and indexes various Web3 content with AI. It automatically extracts narratives, topics, and ticker information from social media, governance forums, research, news, podcasts, and conference presentations that are hard to grasp at a glance with conventional search engines, helping users search and track them. This allows users to quickly understand market narratives and attention flows for specific projects or topics and solves the problem of fragmented information. Kaito also encourages users to share information and produce content through tokenized attention models like Yap-to-Earn. Paradoxically, this reward mechanism can also be the system's greatest vulnerability: information pollution. Kaito’s Yap-to-Earn model can induce indiscriminate AI-generated spam content or meaningless farming behavior by abusers seeking to maximize rewards, which measures artificially inflated attention (manipulated engagement) rather than the community’s genuine interest, causing users to doubt the reliability of the metrics. While Kaito is likely taking steps to address information pollution, the arms race between attack and defense inevitably continues. Therefore, a 'gap with real behavior' can occur: mentions, likes, or the number of pieces of content on social media do not guarantee that users will open wallets, use protocols, and generate on-chain transactions. This shows that "everyone is talking about it" is not the same as "everyone is using it," and decisions based on this can carry risks. 1.2 On-chain data-based: reflects real use but has high barriers to access The on-chain data-based approach is characterized by providing verifiable on-chain data. Records on the blockchain such as transactions, wallet movements, and contract calls are immutable, so these platforms can provide data that reflect users' on-chain activities. For example, Nansen reprocesses on-chain data by labeling blockchain wallet addresses as 'Smart Money,' 'Whale,' 'VC,' 'Exchange,' etc. This allows users to track the capital flows, portfolio changes, and transaction histories of crypto players hidden behind anonymous addresses. Artemis, meanwhile, is a platform focused on fundamental data that analyzes blockchains and dApps like companies, providing metrics similar to those used in traditional finance company valuation: Daily Active Addresses, transaction counts, protocol revenue and fees, and TVL. However, using these tools properly requires a high level of expertise. On-chain analysis tools like Nansen or Artemis demand more than simple use; to accurately interpret raw data and derive meaningful insights, a deep understanding of blockchain structure and market mechanisms is essential. 1.3 The need for 'fast and verifiable' information There is a gap in the current crypto information analysis market between 'fast trend detection' and 'accurate reflection of real usage.' Social-based data are attractive because they quickly show which issues are gaining traction, but they have limits in terms of actual relevance to projects and credibility. Interaction metrics like likes, impressions, and follower counts are superficial numbers that can be distorted at any time. For example, users often exchange 'GM (Good Morning)' greetings or emojis just to earn points, reacting to each other's posts in a quid-pro-quo manner regardless of the information's actual value. Such interaction metrics can be easily inflated and ultimately distort the reading of market flows. On the other hand, on-chain data are difficult to manipulate because they involve signatures, transactions, and fee payments, which require a certain level of cost and effort, so they are evaluated as trustworthy indicators reflecting real actions. However, on-chain information is hard to interpret for average users and can take significant time to produce comprehensive analysis results. In this context, Signal by Layer3 is a product that approaches this gap from a new perspective. It answers questions like "Did explosive social media interest actually translate into on-chain activity?" and "What is the conversion efficiency?" quickly and verifiably based on on-chain data. By quantifying the participation and behavior of users who actively engage in reward-based activities, Signal goes beyond simple trend detection to precisely analyze campaign efficiency and user conversion rates rather than surface-level metrics. 2. Signal: On-chain activity-based Attention Indexer Signal is a new analytics tool that evaluates users' responsiveness to quest-based campaigns based on the vast on-chain activity data Layer3 has accumulated through its quest-based app over the past 3 years. Signal focuses not on merely 'how much participation there was' but on 'how efficiently the project elicited participation.' It provides new on-chain-based insights that existing analytics tools have been missing. 2.1 Based on Layer3’s 3 years of accumulated on-chain activity data Signal is based on the extensive on-chain activity data Layer3 has accumulated over the past 3 years operating as a quest and reward platform: Over 3 million users who paid fees at least once Over 200 million attributed transactions Over 60 million on-chain credentials This data is not mere views or mentions but contains 'intent-driven onchain activity' where users actually connected wallets, paid gas fees, and interacted with specific protocols. Because of these characteristics, users can trust Signal as an analytic tool. Signal aggregates user on-chain activity data generated within Layer3’s action-reward structure to act as a public scoreboard showing which projects, blockchains, and communities are driving real participation. Rather than simply counting events or content, it ranks based on actual participation rates over specific periods. One metric provided is the 'Onchain Relevance Index,' which is differentiated from social metrics like likes or followers because it is based on on-chain traces of user activity such as wallet interactions, quest completions, and on-chain credentials. The Signal app also provides an 'Attention Index' and a 'Trending Board' at the levels of blockchain, community, and campaign, allowing users to check rankings based on actual participation rates within a given time frame. In this regard, Signal is not just an attention measurement tool but a reliable analytic metric rooted in actual on-chain activity. 2.2 Attention Index: measure participation efficiency Signal's core is not simple participation volume but 'Participation Efficiency.' The main metric that measures this is the Attention Index, which is based on CUBE minting records that prove on-chain that users actually completed quests — not just how often a project was mentioned. In other words, the metric shows where genuine momentum is within the Layer3 user base for a given project ecosystem. Ultimately, instead of "How many people talked about it?" it answers "Of the people who saw the message, how many unique users actually opened wallets and acted?" at a glance. The Attention Index is calculated by dividing the share of unique participants a project attracted during a specific period (Share of Unique Participants) by the share of the total activations accounted for by the project's campaigns (Share of Overall Activations). Attention Index = Share of Unique Participants / Share of Overall Activations For example, compare two projects: Project A: If Project A accounted for only 2% of total campaigns but drew 10% of total unique participants, Project A’s Attention Index would score 5.0 (10% / 2%). Project B: If Project B accounted for 10% of total campaigns but only 5% of unique participants, Project B’s Attention Index would be 0.5 (5% / 10%), relatively lower than Project A. As of August 2025, Mantle’s Attention Index ranks first. Mantle achieved this rank by maintaining an average Attention Index of 45 over the month, driving steady on-chain activity from users. Notably, Mantle’s peak Attention Index occurred on January 15, 2025. This was driven by an airdrop campaign that started on Layer3, which resulted in an Attention Index of 352, 33,825 CUBE mintings, and 33,725 unique users — figures reflecting the campaign's explosive response and peak on-chain activity. At that time, many new users actually created wallets and minted CUBEs, causing CUBE mintings and unique users to surge simultaneously on the chart. Like Project A, Mantle achieved high participation efficiency with relatively few campaigns, securing the top spot in the Attention Index. This Attention Index calculation has two effects: Identify cost-effective projects: It clearly highlights projects that attract many unique users through small-scale campaigns and thus hold genuine appeal to users. Deter abuse: By using unique participant counts rather than total participation events, it effectively filters out multi-account abuse that inflates numbers by mobilizing multiple wallets. A high Attention Index for projects like Project A or Mantle indicates that the project can generate strong engagement and participation in the market with minimal resource input. Conversely, a low index like Project B signals that despite large marketing expenditure, actual user response fell short of expectations. This approach creates a fair competitive environment where projects are evaluated by idea and execution regardless of size or marketing budget, allowing smaller projects with focused and creative campaigns to rank higher than large projects with massive capital. On the Layer3 Signal page, users can view Attention Index by blockchain, community, and campaign, and examine trends over various timeframes such as 24 hours, 7 days, 1 month, and 3 months. Short timeframes are useful for capturing the latest trends but may miss the bigger picture, while longer timeframes provide stable analysis but can be insensitive to sudden changes. Therefore, it is important to consider multiple timeframes together for a comprehensive view. 2.3 Additional components available beyond the Attention Index 2.3.1 Chain Distribution Chain Distribution visually shows how Layer3’s total on-chain activity is distributed across multiple blockchain networks. Users can instantly see the share of each blockchain such as Arbitrum and Base, helping them intuitively understand which blockchain ecosystems are attracting the most attention and participation. 2.3.2 Cumulative Cumulative data represents the total number of on-chain activity metrics accumulated so far and helps identify which blockchain networks have accumulated more on-chain activity metrics. This can be used to analyze whether a blockchain is showing steady growth or experienced explosive increases after specific events from a macro perspective. 2.3.3 Total CUBEs Total CUBE issuance represents the total number of CUBEs issued since the Layer3 platform began. CUBEs are proof that a user completed a specific on-chain task, so this number directly shows the overall activity scale of the platform. In other words, it is the most intuitive measure of how many meaningful user interactions Layer3 has generated so far. 2.3.4 Onchain Attention Feed The Onchain Attention Feed is a near real-time log dashboard displaying user activities on Layer3. For example, records like "which wallet just minted a CUBE for which campaign" play in an animated form. It conveys live what is currently happening on the Layer3 platform, and clicking a CUBE in the dashboard links directly to the campaign where the CUBE was issued to view more details. 2.3.5 Trending Projects and Trending Chains Trending Projects ranks projects whose CUBE issuance has rapidly increased over a recent period (7 days). Because it reveals projects that users are suddenly paying intense attention to right now — not simply large-scale ones — investors and users can spot new narratives and promising early-stage projects before others. Trending Chains ranks blockchain networks where user activity and participation have surged. For example, if a large campaign runs on a specific chain or a new killer app appears and CUBE issuance increases, that chain’s ranking can jump. Users can see where liquidity and attention are moving among layer-1 or layer-2 blockchains and gauge ecosystems to watch. 3. Use cases and future roadmap for Signal 3.1 For whom and for what is this tool? How can Signal’s metrics be used effectively? Signal’s value is revealed differently depending on the user. Exchanges, project teams, investors, and communities can use Signal to filter speculative noise and gain data-driven insights. 3.1.1 Exchanges: discover potential projects and strengthen listing reviews CEX and DEX can use Signal to identify projects that show user inflow and traction before token prices or volumes spike. For example, projects newly entering Signal’s top ranks or showing simultaneous improvement in 7-day and 30-day metrics are strong signals that market interest is translating into actual behavior. This can be used as a reference in listing reviews or decisions to introduce liquidity pools. To avoid distortions from short-term incentive campaigns, cross-verification using tools like Nansen or Artemis for liquidity, stablecoin inflows, and net wallet growth is necessary. 3.1.2 Project teams: measure and optimize marketing ROI For project teams, Signal is a tool to directly measure marketing campaign performance. By tracking changes in the Attention Index, they can quantitatively analyze which messages, channels, rewards, or quest difficulty levels drove user behavior most efficiently. For example, chain-specific A/B tests can quantify how gas fees or speed differences affect conversion rates. This helps optimize marketing budgets and adjust strategies based on data. 3.1.3 Investors and VCs: investment based on real growth VCs and individual investors can avoid relying on weak signals like social-media hype or short-term price swings by using Signal’s data on actual user engagement. If a project’s Attention Index consistently rises while on-chain liquidity metrics like LP holding periods or TVL stability improve, investors can make much more refined investment decisions. This provides crucial evidence for evaluating intrinsic value and constructing portfolios with a long-term perspective. 3.1.4 Communities: a tool to prove growth For community members, Signal provides objective evidence to support claims like "our project effectively induces this level of on-chain participation." This can be used to attract new members or persuade partners. However, because metrics vary depending on campaign design, it is important to disclose that and present additional data such as long-term user retention to gain greater trust. 3.2 Caveats when using Signal data Signal is a powerful tool for identifying trends of projects and blockchains using on-chain data, but there are several caveats in interpretation and use: Selection Bias: Signal reflects activities that occurred within the Layer3 platform only. Generalizing Layer3 relevance to the whole ecosystem may be risky. Design Sensitivity: Campaign design elements such as difficulty or reward scale directly affect the Attention Index, so when interpreting the metric, consider whether short-term metrics were inflated by easy quests and strong rewards. Sybil Resistance: Signal defends against Sybil attacks using unique participant criteria, but sophisticated bot involvement is always possible. Although Layer3’s defense logic mitigates some abuse, users should be aware of this when using Signal’s metrics. Cross-Chain Heterogeneity: Differences in fees, speed, and UX across chains affect user behavior, so when directly comparing Attention Indexes of projects on different chains, account for these environmental differences. 3.3 Future direction: premium features and API ecosystem Layer3 plans to gradually enhance Signal and expand it into a more sophisticated premium model. This is also a core B2B business strategy for Signal. 3.3.1 Predictive analytics and campaign benchmarks The upcoming paid version of Signal will offer Predictive Insights that analyze Attention Index trends in more detail to identify projects with high growth potential. It will also include Campaign Benchmarks to compare a company’s campaign performance with competitors or industry averages, and Real-time Analytics for immediate response to rapid market changes. 3.3.2 Ecosystem expansion via data API Signal will provide API access so data teams, funds, and external analytics platforms can directly use Signal data. This will allow Signal to expand beyond Layer3’s platform, enabling external developers to build new analytic tools and investment strategies, broadening the data ecosystem. 3.3.3 Layer3’s sustainable revenue model These premium features and API offerings will become new B2B revenue sources based on Layer3’s proprietary on-chain data assets. This demonstrates Layer3’s diversification from a B2C quest platform into a B2B and B2D (Business to Developer) data platform by assetizing derived data. Quest operation costs can be supplemented by data sales revenue, which can be reinvested in quest development to create a virtuous flywheel. 4. Could Signal become a new standard metric in Web3? Signal’s emergence is meaningful not simply as another analytics tool but because it offers a new perspective on how the crypto market interprets and values attention information. Signal proposes a new standard, 'On-chain Participation Efficiency,' balancing speed and reliability. The Attention Index, which embodies this new standard, has the potential to become a core KPI or standard metric in the crypto market for measuring genuine user participation — similar to TVL in DeFi or DAU for app services. However, several challenges remain before it can be widely trusted across the industry: Define unique participants precisely and develop logic to defend against non-unique users and Sybil attacks. Expand coverage across multiple partners and chains beyond Layer3 to increase representativeness. Build an interoperable API ecosystem that can combine external analytics tools and data. Provide project- and chain-specific benchmark metrics so anyone can perform objective comparisons. Ultimately, Signal is like a mirror that makes projects, investors, and communities reflect on their own activities. It prompts us to ask whether the information we create is mere 'noise' or genuine 'signal' that drives action. Attempts to quantify the intangible value of attention more fairly and meaningfully will help projects be evaluated by real utility and value rather than hype or speculative fervor. This is a necessary shift as the crypto market matures, and if Layer3’s Signal successfully establishes this new perspective, we may be witnessing the birth of an important standard metric for measuring Web3 with on-chain data. Four Pillars is a global blockchain research firm whose team of experienced practitioners provides research services to global clients. Since its founding in 2023, it has conducted research on over 100 protocols and companies across stablecoins, decentralized finance, infrastructure, tokenomics, and more, aiming to reduce information asymmetry across the industry and support real-world adoption and growth of blockchain. Disclaimer This article was prepared based on the author’s independent research sponsored by Stable. It is intended for general informational purposes and does not constitute legal, business, investment, or tax advice. Do not make investment decisions or use this as accounting, legal, or tax guidance. Mentions of specific assets or securities are for informational purposes only and are not investment recommendations. The views expressed are the author’s personal opinions and may not reflect the views of related institutions, organizations, or individuals. Opinions in this article may change without prior notice. This report is independent of media editorial direction, and all responsibility lies with the information providers.
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