Prediction Market Infrastructure Growth: Scalability and User Acquisition as Long-Term Value Drivers

The prediction market sector is undergoing a transformative phase, driven by advancements in blockchain technology, AI-driven analytics, and evolving regulatory frameworks. As platforms like Kalshi and Polymarket demonstrate explosive growth, early-stage infrastructure scalability and user acquisition strategies are emerging as critical determinants of long-term value. This analysis explores how these factors shape the trajectory of prediction markets and their potential to redefine risk management, forecasting, and financial innovation.

Scalability Challenges: Blockchain Limitations and Infrastructure Innovations

Prediction market platforms face inherent scalability challenges due to the limitations of blockchain consensus mechanisms. High-frequency trading and large user bases strain networks reliant on energy-intensive Proof-of-Work (PoW) or slower consensus models, leading to congestion, elevated transaction fees, and reduced efficiency, as noted in a Medium analysis. For instance, platforms like Augur and Omen, which prioritize trustless on-chain execution, struggle with high gas fees and limited throughput, deterring mainstream adoption, according to CoinDesk.

To address these issues, developers are adopting Layer 2 solutions (e.g., Ethereum 2.0, sidechains) and sharding techniques to partition blockchains into smaller, independent segments, improving throughput while maintaining decentralization, per the Blockchain Council. Hybrid models, such as Polymarket's integration of on-chain smart contracts with off-chain liquidity solutions, balance scalability with user experience, as reported by CoinDesk. Additionally, advancements in oracle systems-such as cross-verification among multiple data sources-are enhancing the accuracy and robustness of market resolution, as described in a Johal guide.

The global data center infrastructure ecosystem further supports scalability, with AI-driven workloads demanding specialized hardware like high-end GPUs and liquid cooling solutions. By 2025, over 35% of AI-centric data centers are expected to adopt liquid cooling, enabling efficient heat management for high-density computing, the Medium analysis predicts. Edge computing is also reducing latency for real-time applications, with 50% of data now processed outside traditional data centers, the same Medium analysis notes.

User Acquisition: AI-Driven Strategies and Regulatory Adaptability

User acquisition in prediction markets has evolved beyond traditional marketing, leveraging AI-driven methods to optimize onboarding, compliance, and engagement. Platforms like Kalshi and Polymarket have adopted automated AI systems for compliance checks, risk profiling, and document verification, streamlining customer onboarding, as a Johal guide explains. For example, Polymarket's wallet-less signup process and fiat-to-crypto integrations reduced barriers to entry, enabling viral growth during events like the 2023 Titan submersible incident, the Medium analysis observed.

Regulatory adaptability is another key driver. Kalshi's CFTC-regulated framework provides U.S. users with a familiar trading experience, while Polymarket's decentralized model on Polygon offers global accessibility but faces U.S. restrictions, according to a BetMetricsLab review. The integration of traditional finance mechanisms-such as time and price priority-has also enhanced trust, with platforms like PredictIt and ForecastEx operating within structured regulatory environments, as highlighted by the Medium analysis.

Mobile app strategies further underscore the importance of precision targeting. Diversification of ad networks (e.g., using six or more platforms) has boosted ROI by 3X compared to fewer networks, as noted in a Singular post. Privacy-first regulations, such as Apple's SKAdNetwork, have necessitated contextual targeting and predictive modeling, while AI-powered bidding algorithms analyze user behavior to identify high-value prospects, the Singular post explains.

Case Studies: Kalshi and Polymarket as Scalability and Acquisition Benchmarks

Kalshi and Polymarket exemplify how scalability and user acquisition strategies drive long-term value. Kalshi's $300 million funding round at a $5 billion valuation enabled expansion into 140 countries, with annualized trading volume reaching $50 billion, as detailed in the Johal guide. Its regulated U.S. model, combined with partnerships like Robinhood and a viral NBA Finals commercial, boosted app store rankings to No. 54, the BetMetricsLab review reports. However, Kalshi's DAU dropped from 400,000 during the 2024 election to 27,000–32,000 by mid-2025, highlighting the need for sustained engagement, the Medium analysis notes.

Polymarket, on the other hand, leveraged blockchain's global reach and acquired QCEX to re-enter the U.S. market in 2025 after a $2 billion investment from Intercontinental Exchange (ICE), the Medium analysis documents. Its $8 billion valuation and ICE's distribution network underscore the value of institutional backing. Despite a 90% drop in DAU post-election, Polymarket maintained a 37% share of on-chain trading volume in September 2025, with an open interest-to-volume ratio of 0.38, indicating longer-term user retention, CoinDesk reported.

Investment Implications and Future Outlook

The long-term value of prediction market platforms hinges on overcoming scalability bottlenecks and refining user acquisition. Key metrics like LTV-to-CAC ratio (ideally 3:1) and churn rate will determine sustainability, according to the Blockchain Council. For instance, Kalshi's lower open interest-to-volume ratio (0.29) suggests frequent trading, while Polymarket's higher ratio (0.38) indicates longer-term user engagement, CoinDesk analysis shows.

Future growth will depend on interoperability between blockchain networks, regulatory clarity, and AI-driven liquidity solutions. Platforms that integrate renewable energy for data centers, adopt circular economy models, and prioritize energy efficiency will gain competitive advantages, the BetMetricsLab review argues. Additionally, the expansion of prediction markets beyond politics-into tech, culture, and climate-will sustain user interest, CoinDesk suggests.

Conclusion

Prediction market infrastructure is at a pivotal juncture, with scalability and user acquisition strategies defining its trajectory. As platforms navigate regulatory landscapes and technological constraints, those that innovate in blockchain scalability, AI-driven onboarding, and global accessibility will emerge as leaders. For investors, the sector offers a unique opportunity to capitalize on the convergence of decentralized finance, AI, and real-world forecasting-provided they prioritize platforms with robust infrastructure and sustainable user growth.