Web3 Analytics: challenges, use cases & opportunities

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26 May 2024

Web3 Analytics: challenges, use cases & opportunities

Web3 Analytics: challenges, use cases & opportunities

Web3 Analytics: challenges, use cases & opportunities

For startups, Web3 analytics is essential for informed decision-making and product success. Leveraging onchain data is critical to thriving in this growing ecosystem. Let's dive deeper into Web3 analytics in this blog post.

Web3 analytics enables product and marketing teams to acquire actionable insights about web3 users

Web3 analytics enables product and marketing teams to acquire actionable insights about web3 users

What is Web3 Analytics?

Web3 Analytics is a critical tool in the distributed economy that helps developers, creators, and marketers understand and optimize various aspects of Web3 applications. It involves collecting and analyzing data from various Web3 platforms, transactions, and user interactions to gain valuable insights that can drive innovation and growth.

The data fragmentation challenge

In Web2, teams use IP addresses, cookies, and device IDs to collect data that enables personalized experiences and targeted promotions. However, there are no cookies or IP addresses in web3, only wallet addresses. Blockchains are a pseudonymous and privacy-centric environment where we don’t know who the users are.  That's why Web3 complicates the capture of consumer behavior, making attribution and personalization more difficult for product and marketing teams.

Compare and contrast between web2 and web3 data collection

Compare and contrast between web2 and web3 data collection

Amazon uses cookies to track clicks on its websites and device IDs for clicks on its apps, linking them to unique user IDs associated with Amazon accounts. This enables the collection of behavioral data for personalized recommendations and product decisions.

Example Web2 user flow analytics

Example Web2 user flow analytics

When purchasing NFTs on OpenSea or swapping tokens on UniSwap, attributing user behavior is challenging due to identity and data fragmentation. This hinders the ability of product teams to understand behavioral data in web3.

Example Web3 user flow analytics

Example Web3 user flow analytics 

Fragmentation of identity

In Web3, transaction data is public on the blockchain while identity can be kept private, unlike Web2 where user identifiers are public while transaction data is private. Most decentralized applications including OpenSea and UniSwap do not require Know Your Customer (KYC), preserving the ethos of ownership and privacy. As a result, wallet addresses in Web3 reveal only behavioral data. Users may have multiple wallets for different purposes, making associating wallets with a single identity difficult. 

Web3 analytics moves away from personal identity-based metrics to new pseudonymous indicators such as community engagement, NFT ownership, and wallet balances.

Why is Web3 Analytics important?

Web3 Analytics is a strategic necessity for project teams seeking to thrive in the Web3 ecosystem. Understanding onchain data helps you make informed decisions, build deep customer relationships, optimize operations, and reduce risk. With Web3 Analytics, product teams can gain insight into user behavior, product performance, and market trends. 

Examining wallet activity and the NFTs held by users, Web3 Analytics can identify high-net-worth users

Examining wallet activity and the NFTs held by users, Web3 Analytics can identify high-net-worth users

You can get started with Web3 analytics with these common metrics: 

  • Total Users: Monitor the number of unique wallet sign-ups to evaluate user growth and marketing campaigns. 

  • Active Users: Track hourly, daily, weekly, and monthly interactions to measure engagement and retention. 

  • New Users: Measure new wallet connections to track user acquisition and growth. 

  • Bots: Use sybil lists to Identify and filter out bots and airdrop hunters. Sybil resistance helps to ensure fairness and accurate user numbers. 

  • Localization: Use offchain data to target marketing initiatives to specific locations and languages. 

  • User Segments: Group users into segments and engage them with targeted messaging. 

  • Account Balances: Target high-value users with special deals and rewards. 

  • Risk Scoring: Identify and block problem users with a history of fraud or bad behavior. 

  • Transactions: Analyze in-dapp transactions to measure conversions and optimize marketing strategies.

Web3 Analytics action plan

Web3 Analytics Action Plan consists of these key steps:

Step 1: Define your goals and metrics

When implementing Web3 Analytics, clearly define your business goals and KPIs: 

  • Identify business goals: Improve market presence, Increase retention rate, or acquire users.

  • Define KPIs: Specify metrics to track progress, such as TVL, transaction volumes, wallet growth, conversion rates, asset valuations, etc.

Step 2: Choose the right tools and platforms

Select tools that match your goals, expertise, and budget: 

  • Blockchain Explorers: Basic insights into transactions, addresses, and smart contracts (e.g., Etherscan, BscScan, PolygonScan). 

  • Specialized Analytics Platforms: Advanced querying, data visualization, and customizable dashboards for Web3 data (e.g., Dune, Nansen, or Formo). 

  • Data Warehousing and Integration: Combine onchain data with offchain zero-party and first-party data in a data warehouse for advanced analytics.

Selecting the right Web3 analytics tool helps teams with data-driven decision-making and strategic planning

Selecting the right Web3 analytics tool helps teams with data-driven decision-making and strategic planning

Step 3: Build or Outsource Expertise

Effective use of Web3 data requires specialized skills. Options include:

  • Upskill in-house teams: Train analysts in blockchain fundamentals, data extraction, and onchain metrics. 

  • Partner with Web3 consultants: Leverage the expertise of specialized vendors for faster results and strategic guidance.

Step 4: Prioritize data integrity

Even on-chain data can contain errors. Implement robust data quality safeguards: 

  • Data validation processes: Establish rigorous checks for consistency, completeness, and accuracy before making critical decisions. 

  • Source verification: Ensure that data from APIs comes from reliable blockchain sources and follows proper extraction methods.

Step 5: Balance Transparency with Privacy

Web3 analytics shouldn't compromise user privacy and compliance. Develop responsible data handling practices: 

  • Anonymization and Aggregation: Anonymize or aggregate sensitive data to protect privacy while preserving analytical value. 

  • Respect user consent: Obtain explicit consent before collecting and analyzing personally identifiable information. 

  • Stay compliant: Monitor the evolving regulatory landscape and ensure compliance.

Deeper onchain insight with Formo 

Formo enables companies to understand and use onchain data to deliver engaging, personalized experiences in web3. Formo provides actionable insights into user acquisition, engagement, retention, and conversion for onchain apps. With Formo’s onchain product analytics platform, teams can optimize the customer journey and maximize ROI in web3.

Uncover actionable on-chain insights with Formo

Uncover actionable on-chain insights with Formo

Understanding onchain data puts project teams at the forefront of the web3 revolution. Web3 data analytics is critical for user growth and seizing opportunities onchain.

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