Building Connected Audiences with Disco

Web2 businesses thrive on massive data engines, continuously collecting and analyzing data to thoroughly understand their customers and optimize their business operations. While some of these practices have violated user data privacy rights and explicit laws, the concept of utilizing data to understand customers is not going anywhere. In fact, data-driven customer acquisition is crucial for any business to achieve profitable scale; an ongoing challenge for blockchain businesses and an obvious opportunity for our team at Disco.

Challenges in Onchain Audience Analysis

Traditional web2 applications have long relied on a plethora of data points and sophisticated analytics tools to understand their users. In contrast, the decentralized nature of blockchain technology means that user data is scattered across various chains and platforms, often anonymized by default. The primary challenges include:

  • Data Fragmentation: User data exists across multiple chains, primitives and platforms, making it difficult to aggregate and analyze.

  • Anonymity: Blockchain’s inherent pseudonymity makes it challenging to link activities to a single user.

  • Cleaning and Structure: Interpreting raw blockchain data requires expertise and context.

From Raw Data to Discovering Your Unfair Advantages

Blockchains are touted for immutable, permissionless documentation, yet few resources have gone into building truly scalable audiences, incorporating onchain data to define and organize user segments across data platforms, blockchains, protocols, or data standards.

With Disco, app developers can now:

  • Identify High-Value Users: Recognize users who bring the most value to the platform or similar platforms

  • Tailor User Experiences: Customize interactions to enhance user satisfaction and retention

  • Optimize Marketing Efforts: Target campaigns more effectively to increase user acquisition and engagement

  • Enhance Product Development: Gather insights that inform product improvements and new features

Multichain Data: Audiences across Protocols

Disco aggregates onchain data from multiple major blockchain ecosystems, including Ethereum, Optimism, Arbitrum and more. Uniting multiple sources of data that describe similar, or even the same, users allows developers to view a holistic picture of user activities across different platforms, incorporating offchain data where relevant as well. By logically organizing this data, Disco empowers ecosystem builders as they:

  • Identify User Behavioral Patterns: Understand how users interact with different apps and protocols

  • Analyze Asset Holdings and Transactions: Understand the financial behaviors and transaction strategies of users

  • Assess Risk: Understand the risk profiles of users

Chains where recipients are most active: It shows the %age split of the chains based on their onchain activity.
Chains where recipients are most active: It shows the %age split of the chains based on their onchain activity.

For example, NFT lending platforms (such as NFTFi or Arcade.xyz) can use Disco to aggregate data about users who engage in NFT lending and borrowing across multiple chains. This data can help these platforms understand user preferences for certain types of NFTs, their borrowing habits, and repayment behaviors, enabling them to tailor their offerings to better meet user needs.

Common Defi Transactions: It shows the %age split and volume of different types of Defi transactions which users perform.
Common Defi Transactions: It shows the %age split and volume of different types of Defi transactions which users perform.

Verifiable Credentials and Reputation Scoring

Disco leverages verifiable credentials to provide a more accurate picture of user qualifications and capabilities. Disco’s dashboards make it easy to understand your ecosystem’s:

  • Reputation: Quantitative scores based on user activities, transactions, and engagement within the blockchain ecosystem.

  • Community Participation: Insights into users’ involvement in various blockchain communities.

  • Transaction History: Detailed records of users’ onchain activities.

By aggregating and interpreting more than simple token holdings alone, Disco makes it easy to coordinate more interactions than simple token transfers. These more sophisticated capabilities include:

  • Reputation-based access control allows an app, function or service to permit user access based on multiple data requirements, potentially originating from different sources, taking the form of different file types, and being stored in different locations.

  • Composable trust is when a known, discoverable entity publishes public reputational data about users. Other entities are willing to accept the data at face value because of its origin, unbroken provenance and signature verifiability. Composable trust reduces the cost of coordination among counterparties onchain, and is enabled by Disco’s platform.

Campaign Audience: It shows a single view of a campaign collector’s Risk Level and legitimacy level.
Campaign Audience: It shows a single view of a campaign collector’s Risk Level and legitimacy level.

Disco employs machine learning models that can support partners, such as ecommerce and NFT lending platforms, to analyze user interactions to detect trends, such as increasing demand for certain types of NFTs as collateral. This insight can help them adjust their lending policies and develop new financial products that cater to current market demands. These platforms can also issue credentials to users based on their lending and borrowing history, which enable easy discovery and matching with relevant offers from other brands. These credentials can help service platforms identify trustworthy borrowers with a good repayment track record, allowing them to offer better loan terms or faster approval processes to these users. This data can also act like a universal captcha, illuminating the personhood of the user based on the cost and complexity of their actions over time. Overall, the use of more nuanced data enables services and brands to more easily identify high-value users, offer exclusive benefits, and increase retention and loyalty.

Machine Learning and Advanced Analytics

Disco’s continuously evolving machine learning models help in interpreting complex onchain data. These models can:

  • Detect Patterns and Trends: Identify emerging trends in user behavior.

  • Predict Future Engagement: Forecast how users might interact with dApps based on past behaviors.

  • Segment Users Effectively: Group users into segments based on their behaviors and preferences for targeted engagement

Building For Utility

Understanding your audience through Disco’s tools makes it easier to understand their priorities, interests, decision-making criteria and opportunities for interaction.

What does building utility around user preferences and data really look like? Today at Disco, we support our partners to pursue:

  • Enhanced User Acquisition: By identifying high-value user segments, developers can tailor their acquisition strategies to attract similar users.

  • Improved User Retention: Personalized experiences and targeted incentives can keep users engaged and loyal to the platform.

  • Demand-driven Product Development: Data insights to guide the development based on real utility and business cases

Join the Party

In the competitive landscape of applications and services, understanding your audience is not just beneficial—it’s essential. Disco.xyz equips app developers and ecosystem builders with the tools and insights needed to navigate the complexities of onchain data and gain a comprehensive understanding of their audiences.

To get started with Disco today, say hello to our sales team at tom@disco.xyz.

See you onchain!

-Evin

Founder, Disco.xyz

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