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Enterprise AI Analysis: When text is not enough: Data-driven personas to explore crypto education affordances through learning platform analysis and survey insights

Enterprise AI Analysis

When text is not enough: Data-driven personas to explore crypto education affordances through learning platform analysis and survey insights

Authors: Lisa Straub, Christian Zeiß, Justus Pehl, Maximilian Greiner, Axel Winkelmann, Ulrike Lechner

Where established financial literacy initiatives fail to keep pace with rapidly evolving digital asset markets, new customer learning environments emerge. In the context of crypto assets and the blockchain ecosystem, platform providers, ranging from trading platforms to specialized educational portals, have taken on a central role in promoting knowledge-building among users. However, most providers lack educational expertise. In line with affordance theory, which focuses on possibilities for action emerging from the interplay between users and technology, it is not enough for platforms to provide merely learning opportunities. To promote broader crypto adoption, educational offerings should align with users' needs. Therefore, this study employs a data-driven persona development approach and analyzes 20 crypto education platforms concerning their implemented learning components. In addition, we apply topic modeling to explore the educational content. These analyses aim to assess the current state of crypto education platforms and to identify the opportunities (affordances) embedded in the design. Based on the insights and an accompanying user survey, we examine which educational offerings are perceived as valuable by different user groups and derive four distinct types of crypto learners: Cautious Strategist, Critical Observer, Curious Gamified Explorer, and Hands-On Practical Experimenter. Our findings reveal a misalignment between current platform design and learner preferences. Across all types, users tend to favor dynamic formats over static, article-based content. Based on affordance theory, we highlight design implications for crypto learning and present data-supported personas to foster more differentiated and user-centered educational strategies.

Executive Impact Summary

This research addresses the critical gap in crypto education, providing a clear roadmap for platforms to better serve diverse user needs and foster broader adoption.

0 Platforms Analyzed
0 Persona Types Identified
0 Survey Participants
0 Top Content Area Rating

Core Challenge

Established financial literacy initiatives fail to keep pace with rapidly evolving digital asset markets, leading to a substantial lack of knowledge and difficulty in accessing crypto assets. Most platform providers lack educational expertise, resulting in generic, non-adaptive content that overwhelms newcomers and misaligns with user needs. This creates a significant design-reality gap in crypto education.

Our Solution & Approach

This study employs a multi-phase data-driven persona development approach. We analyze 20 crypto education platforms for their learning components and apply topic modeling to content. An online survey (269 participants) further clarifies user preferences. These combined insights identify critical affordances, derive four distinct learner personas, and highlight design implications to tailor crypto education offerings to diverse user needs, bridging the current design-reality gap.

Deep Analysis & Enterprise Applications

Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.

Crypto Ecosystem Trends
Structural Foundations
Emerging Narratives
Technological Background
Trading & Investment
Gamified Campaigns

Crypto Ecosystem Trends

This category covers content clusters about new tools in Decentralized Finance (DeFi), tokens, and platforms, as well as market patterns such as meme coins, GameFi developments, and connections to macroeconomic or policy changes, helping users understand the bigger picture behind crypto movements. Specific topics include meme coin market trends & hype cycles; Web3 gaming & GameFi industry momentum; Intersections of crypto with macro & policy trends; New crypto tools and platforms; Emerging crypto sectors: RWA & AI tokens; AI token sector: weekly performance & market trends; Solana ecosystem growth & weekly market trends.

Structural Foundations and Economic Forces

This category comprises content clusters related to the underlying structures and drivers of the crypto economy, exploring institutional adoption, regulation, central bank digital currencies (CBDC), tokenization, and the role of Bitcoin and stablecoins in global finance to deepen understanding of how crypto markets evolve. Specific topics include crypto market movements: institutions, policies, and trends; Bitcoin's economic role and macroeconomic narratives; Crypto regulation, CBDCs, and state-level adoption; Tokenization, adoption, and the crypto funding landscape; Stablecoins and on-chain representations of value.

Emerging Narratives and Community Trends

This category highlights content clusters that concern new and emerging trends in crypto culture and community activity, including developments in AI, fan tokens, airdrops, Non-Fungible Token (NFT) gaming, and influencer dynamics. The contents show how social movements and innovation beyond technology shape the crypto space. Specific topics include AI narratives & agent-based innovation; Gaming, virtual worlds, & NFT ecosystems; Telegram-driven micro-economies and bot projects; Airdrop Campaigns and participation mechanics; Fan tokens and sports engagement in web3; Ripple ecosystem and legal controversies; Crypto access and fiat onboarding solutions; Crypto market reviews and trading insights; financial literacy and risk in crypto culture; Alternative assets & consumer-focused crypto products; Crypto events, reserve proofs, and regional developments; Legacy altcoins & market movement; Tech frontiers: IoT, quantum, and GPU-driven protocols; Meme coins & cultural token movements; Hardware and experience layers in web3; Crypto identity, influencers, and legacy figures; Next-gen layer 1 blockchains and developer ecosystems; Bitcoin layer innovations: ordinals, runes, and BRC-20s.

Technological Background

This category covers content clusters about smart contracts, multi-chain protocols, technical fundamentals of Web3 platforms, privacy tools, staking mechanisms, wallets, and governance systems. This content helps users understand how the underlying decentralized infrastructure works. Specific topics include Ethereum protocol changes and consensus evolution; Blockchain infrastructure, security, and mining mechanics; Token standards and account abstraction; Scalability, interoperability, and multichain protocols; Privacy, transparency, and transaction layer tools; Smart contracts, middleware, and web3 applications; Decentralized governance and DAO infrastructure; BNB ecosystem and wallet infrastructure; Bitcoin forks and network upgrade mechanisms; Decentralized finance: lending, yield, and liquidity; Wallet security and self-custody solutions; Staking Mechanisms and Yield Strategies in Web3.

Crypto Trading, Investment Behavior, and Market Education

This category addresses a content cluster related to trading strategies, crypto exchange-traded funds (ETFs), sentiment analysis, technical indicators, and tax-related knowledge, promoting informed and responsible investment decisions. Specific topics include altcoin sentiment, risk behavior, and community engagement; Crypto derivatives and leveraged trading instruments; Market psychology and valuation cycles in crypto; Trading strategies & alternative execution models; Exchange infrastructure and peer-to-peer protocols; Technical analysis and trend-based strategies; Chart patterns and visual trading techniques; Crypto ETF markets and institutional onramps; Microstructure mechanics: orders, fees, and execution; Crypto financial literacy and portfolio practices.

Gamified Crypto Campaigns

This category covers content clusters related to learning elements around gamified elements on crypto platforms, including challenges, rewards, and interactive features such as puzzles, mini-games, and streak-based promotions. Specific topics include puzzle challenges with crypto rewards; Mini games with crypto rewards; Play-to-earn games with crypto rewards; Crypto promotions and events.

Enterprise Process Flow

Structured Literature Review
Platform Selection
Learning Components Analysis
Topic Modeling
Online Survey
Cluster Identification
Cluster Extension
Cluster Differentiation
Create Persona Profiles
5.99 Average user rating for 'Wallet Security & Self-Custody Solutions' (Highest rated content area on a 7-point scale)
6.00 Average user rating for 'Educational Videos & Live Streams' (Highest rated learning component on a 7-point scale)
5.70 Average user agreement: 'Cautious with money and avoids risky or unclear investments' (on a 7-point scale)

A direct comparison reveals a significant misalignment between common platform features and user-rated preferences for crypto education.

Platform Offerings vs. User Preferences

Feature Current Platform Presence User Preference (Avg. Rating)
Articles (Static Text) Dominant format (e.g., P5, P6) Least Preferred (5.28 avg, Critical Observer: 4.57)
Educational Videos & Live Streams Implemented but less prominent (e.g., P1, P2, P8) Highly Preferred (6.00 avg)
Discussion Areas/Forums Rarely implemented directly (e.g., P12, P13, P15) Highly Valued (Discussion area: 5.70 avg, Forum: 5.64 avg)
Ask-an-Expert Functions Rarely implemented Highly Valued (5.84 avg)
Gamified Elements (Learn-and-Earn, Quizzes) Few platforms (e.g., P4, P5, P11, P19, P20) Highly Valued (Learn-and-earn: 5.78 avg, Puzzle challenges: 5.69 avg)
Newsletters More common (e.g., P4, P6, P20) Minimal Interest (4.90 avg, Critical Observer: 3.32)

Different persona types demonstrate distinct preferences, highlighting the need for tailored platform designs to improve actualization of affordances.

Persona-Specific Feature Alignment

Persona Type Key Learning Preferences Current Platform Alignment & Misalignment
Critical Observer
  • Trustworthy, visual, structured, non-interactive (pull-based) content
  • Depth & clarity, specific details
  • Demo environments, Q&A/FAQ, structured beginner sections
  • Often Misaligned: Social, gamified, and push-based formats are common but hold little value.
  • Their preferred features are marginally represented on platforms.
Cautious Strategist
  • Analytical, risk-averse, seeks comprehensive understanding (technical/conceptual)
  • Beginner-friendly formats, demo areas, contextualized instructions
  • Audio-based formats, flexible open-learning options
  • Misaligned: Audio formats are rare on platforms.
  • Gamified/socially charged content, which this persona distances from, is often prioritized.
Curious Gamified Explorer
  • Motivated by practical implications, structured/engaging exploration
  • Gamified/reward-based learning (mini-games, puzzles, promotions)
  • Educational videos & live streams, learn-and-earn, discussion areas
  • Often Misaligned: Gamified and interactive features, highly valued by this persona, are underrepresented in current platform designs.
Hands-On Practical Experimenter
  • Digitally confident, active engagement, high self-efficacy
  • Real-world relevance, practical applicability, technical & conceptual clarity
  • Expert interaction, level systems, learn-and-earn, gamified elements, trading insights
  • Misaligned: Article-based content remains dominant.
  • Practical, interactive, and reward-oriented features preferred by this active learner are less prominent.

Understanding the Critical Observer

The most risk-averse and skeptical crypto learner, demonstrating low self-assessed knowledge and minimal interest in digital finance topics.

The Critical Observer represents the most risk-averse persona. This user profile is characterized by a highly reserved approach to financial decisions, particularly concerning unclear or high-risk investment opportunities (5.41). Compared to other clusters, the Critical Observer shows the lowest levels of self-assessed knowledge about cryptocurrencies (3.39) and the least interest in digital finance topics, including crypto, blockchain (4.09), and broader financial themes (3.86). In terms of learning preferences, the Critical Observer favors autonomous self-directed formats. Preferred formats include educational videos & live streams (5.18), demo environments (5.21), and asynchronous formats such as forums (4.96), Q&A and FAQ sections (4.96), especially those following a pull-based logic. Visual clarity and intuitive presentation are the key (5.00). Structured beginner sections (4.96) and open-learning environments (5.20) are appreciated, while interactive formats, such as peer collaboration (3.84), one-on-one mentoring (3.71), or push-based mechanisms such as newsletters (3.32), are of minimal interest. Social sharing features, such as article sharing (3.61) and like buttons (3.89), are considered largely irrelevant. Compared to other personas, the Critical Observer places less emphasis on developing a comprehensive, integrative understanding of the broader ecosystem (big picture) (4.59). Thematically, this persona shows selective interest in technical and infrastructural topics such as new crypto tools and platforms (5.25), financial literacy & crypto-related risk cultures (5.05), blockchain infrastructure and security & mining structures (5.16), privacy and transparency mechanisms (5.14), wallet security & self-custody solutions (5.39). In contrast, they actively distance themselves from trend-driven or socially charged content, including meme coins & market hype cycles (3.89) as well as cultural token movements (3.88), crypto influencers (3.63), Telegram-based micro-economies (4.02), bot-driven projects and crypto events (3.96).

Empowering the Hands-On Practical Experimenter

A confident and active learner demonstrating high self-efficacy in crypto and blockchain topics, driven by real-world relevance.

The Hands-On Practical Experimenter (see Fig. 10) is a confident digital learner (6.31) who actively engages and demonstrates high self-efficacy in topics related to crypto and blockchain (6.19). Among all personas identified, this user type reports the highest comfort with financial and technological complexity (4.27) and finds it easiest to access and understand blockchain-related content (3.85). Their learning behavior is driven by a strong preference for real-world relevance and practical applicability (6.43), paired with a desire for technical and conceptual clarity (6.41). This persona enjoys staying informed, discussing developments, and connecting technical insights with broader systemic implications. They respond especially well to educational videos & live streams (6.68), and formats that enable direct exchange with experts (6.60), as well as Q&A (6.63). Furthermore, level-based systems for tailored learning (6.59) and learn-and-earn mechanisms (6.61) resonate particularly strongly, as they offer both challenge and immediate reward. In contrast, passive or static formats such as glossaries (5.83), like buttons (5.91), weblink managers (5.68), or long-form articles (5.81) are perceived as less engaging and less relevant to their learning style. In terms of content preferences, the Hands-On Practical Experimenter is particularly drawn to applied, interactive, and reward-oriented formats. They are highly motivated by gamified elements such as play-to-earn games (6.57) and puzzle challenges with crypto rewards (6.56), as well as learn-and-earn features (6.61) that combine knowledge acquisition with tangible benefits. Furthermore, they show strong interest in crypto market reviews and trading insights (6.53), technical analysis, and trend-based strategies (6.48), all of which support their desire for hands-on experimentation.

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Your Path to AI Implementation

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Phase 1: Discovery & Strategy

Conduct in-depth analysis of current workflows, identify key pain points, and define strategic AI objectives aligned with business goals.

Phase 2: Pilot & Proof-of-Concept

Develop and implement a pilot AI solution for a specific use case, demonstrating tangible value and refining the approach.

Phase 3: Scaled Deployment

Integrate the AI solution across relevant departments, ensuring robust infrastructure and comprehensive user training.

Phase 4: Optimization & Future Roadmapping

Continuously monitor performance, gather feedback, and identify new opportunities for AI expansion and innovation.

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