Layer 3 Signal: A Real On-Chain Attention Indicator

The Web3 world's obsession with "buzz" never ceases. Whether a new protocol suddenly becomes popular or an entire sector (such as InfoFi) becomes the focus of capital, "everyone is talking about it" often becomes the reason for entry.
But the problem is: volume ≠ driving force. Mindshare shouldn't just exist in the community; it should be visible on the chain. Truly valuable buzz isn't just about who's talking, but how many people actually do something after the talk—open their wallets, complete tasks, interact with the protocol. This is precisely why Layer3 launched Signal: an on-chain attention metric designed specifically for Web3 that helps you identify which protocols are gaining real user engagement and action, rather than just chatroom topics.

Layer3 Launches Signal: A Real-Time Indicator of On-Chain Attention

In mid-July, Layer3 officially launched its new product, Signal. Rather than a tool, it's a way to re-understand the Web3 world—it's not about how loud you talk, but whether you actually get users to "do something" on the chain. Signal touts itself as an "onchain relevance index," aiming to capture whether a protocol or project truly attracts on-chain participants. This isn't about who's loudest or who's most engaged. Rather, it asks: Are people actually taking action on-chain? What's being accomplished? Are they willing to pay for these interactions with gas or their real identities? This shift in perspective may be a necessary step for an already highly gamified on-chain world. Not starting from scratch, but rather distilling three years of accumulated data. Signal's launch wasn't a clean slate; it builds on the data accumulated over the past three years of Layer 3 development. As one of the most active on-chain task platforms, Layer3 boasts:

• Real interaction records from 3 million active users

• Over 200 million completed tasks

• 60 million verifiable credentials

• Spanning Tracking coverage of over 40 public chain ecosystems

This data isn't just cold, hard numbers; it's a rich, meaningful trace of participation. For example, Signal can identify a task as completed 10,000 times, but if only 100 participants performed the same action 100 times, the "popularity" is questionable.

This kind of judgment was impossible to make based solely on community data in the past.

How is Signal calculated? It's not the number of completions, but the authenticity of the behavior. Signal isn't just a simple leaderboard; it's built on a framework of metrics that focuses on who did what and why.
The main scoring logic combines the following:

• Percentage of independent participants

• Task conversion rate and depth of initiation behavior

• The complexity of the task or interaction (is it a single click? Does it include on-chain signatures or transfers?)

This allows Signal to serve as a proxy for product traction and real traction, rather than a marketing bubble.

It's all about "trends," but what are you looking at? — The fundamental differences between InfoFi, on-chain data tools, and Layer3 Signal

In recent years, a number of products have emerged on the market dedicated to helping users understand what the crypto world is paying attention to. From InfoFi-style projects focused on narrative integration to traditional on-chain data analysis tools, while these tools appear to be tracking trends, their starting points and approaches are actually very different.

InfoFi products focus on understanding what communities are discussing and how public opinion is shifting. Their value proposition is that with so much information, users need a more efficient digest system to organize discussions, news, and sentiment. These tools often rely on AI, keyword and source aggregation, and serve as the "editorial layer of a narrative perspective."

On-chain data analysis tools are centered around open querying. They provide a comprehensive set of on-chain databases and query languages, allowing users to customize conditions and retrieve the data they care about. These tools emphasize flexibility and transparency, but also present a high technical barrier to entry.

Signal doesn't require you to enter search criteria; instead, it directly tells you: how many people are actually participating in the protocol, what interactions have been completed, and what percentage of overall attention they contribute. It's a real-time, behavior-based scoring system, not a data-search tool or information aggregator.

We can understand the division of labor among the three as follows:

• InfoFi products help you understand what everyone is talking about.

• Data analysis tools help you find what you want to know.

• Signal It proactively tells you "what's really happening right now."

None of these three types of tools is best; rather, they correspond to different information needs and decision-making scenarios in Web3. You can first use an information aggregator to understand the prevailing narrative, then use data tools to verify the details, and finally return to Signal to determine whether there's genuine traction, action, and momentum behind these narratives.
Signal aims to address a long-overlooked observational dimension beyond the noise and charts: real on-chain traction.

Next Steps: Prediction, API, and Commercialization Model

Layer3 also acknowledges that Signal won't always be a free version. The Premium Plan will be launched in the coming months and is expected to include:

• Real-time trend forecasting and early warning of potential blockbuster protocols

• On-chain task and campaign performance analysis (campaign benchmarking)

• API access for data teams and funds to build customized strategies

• Customized dashboard and notification module

For a product that already has 1.1 million active users, this expansion is a natural one and signifies that Layer3 is making Signal one of the core engines for its next phase of growth and commercialization.

Conclusion: Attention itself deserves a fairer measurement

The emergence of Signal represents a revision of previous approaches to determining on-chain buzz. It isn't intended to replace the buzz models of Twitter, Discord, and Notion, but rather to provide a more granular measure of behavior. While everyone is speculating about who's making the most noise, Layer3 chooses to observe who's actually making moves. This perspective may be the starting point for the next wave of crypto product design and research. Signal is now available for trial: https://app.layer3.xyz/signal