For the complete documentation index, see llms.txt. This page is also available as Markdown.

5. Data Products

WGA provides three core products.

1) Core Product 1: Behavior Asset Report

Format: PDF Report + On-chain Proof Link

Provided Content:

  • Analysis of verified behavioral data for specific periods, channels, and campaigns

  • Authentic user counts and distribution following the removal of artificial metrics

  • Engagement levels by behavioral category (Exploration, Response, Participation, Diffusion, Retention)

  • Diagnostics of attrition points and friction zones

  • Chronological trend analysis and benchmarking

Operational Objectives:

  • Measurement of marketing campaign efficacy

  • Product UX optimization

  • Investment decision-making support

  • Competitor benchmarking

Target Customers: Web2/Web3 service operators, investment institutions, research organizations

2) Core Product 2: Analytics Dashboard

Format: Web-based real-time dashboard

Provided Content:

  • Real-time verified user behavioral metrics

  • Funnel analysis (Step-by-step attrition and conversion tracking)

  • Cohort tracking (Behavioral shifts over designated timeframes)

  • Behavioral asset distribution (Ratios of Exploration, Response, Participation, Diffusion, and Retention)

  • User distribution by confidence intervals

  • Custom filters and segmentation

Operational Objectives:

  • Daily operational monitoring

  • Real-time campaign performance tracking

  • Proactive anomaly detection

Target Customers: Web2/Web3 service operators, community managers

3) Core Product 3: Behavior Intelligence API

Format: RESTful / GraphQL API

Provided Content:

  • Retrieval of verified behavioral data

  • Retrieval of calculated metric results

  • Filtering, sorting, and aggregation functions

  • Real-time notifications via Webhooks

  • Clean dataset export

Operational Objectives:

  • Integrate your own analytics system

  • Integrate with BI tools

  • Input data for investment models

  • Machine learning training data

  • Integration with proprietary analytical systems

  • BI tool synchronization

  • Input data for investment modeling

  • Machine learning training datasets

  • Target Customers: Enterprise clients, data purchasers, research institutions

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