Election betting's $3.6B data surge: why gaming platforms need customer data infrastructure that scales

The recent U.S. presidential election betting markets have revealed an unprecedented scale of digital wagering that's pushing gaming platforms to their technical limits. With Polymarket alone processing over $3.6 billion in election-related bets, including $1.5 billion wagered on a single candidate, the surge highlights a critical challenge facing the gaming industry: how to collect massive volumes of event data efficiently and cost-effectively.

The unprecedented scale of election betting

The numbers are staggering. Beyond the $3.6 billion in total betting volume on Polymarket, we saw another $120 million on their rival app, Kalshi. Individual traders like "Théo" placed up to $28 million in bets across 11 different accounts, demonstrating the complexity of cross-device tracking and the need for sophisticated identity resolution to mitigate fraudulent activity like this.

What makes this particularly challenging is the real-time nature of betting markets. As Dartmouth University economics professor Eric Zitzewitz notes, "markets tend to move immediately as things are reported." This immediate movement requires robust real-time data infrastructure capable of handling sudden surges in activity while maintaining accuracy and compliance.

The data challenge behind the headlines

While these volumes make for impressive headlines, they present serious technical challenges for gaming platforms looking to collect event data to drive the strategic product decisions necessary to engage players:

1. Multi-state legal complexity: The highly dynamic legal environment of digital wagering by state forces teams to constantly shift their data strategies.
2. Real-time processing: Odds adjustments and market movements happen in real time, requiring immediate data processing.
3. Cross-device user tracking: Cases like "Théo" with 11 different betting accounts highlight the need for sophisticated identity resolution and fraud detection systems.

The hidden costs of traditional CDPs

This is where most companies turn to a Customer Data Platform (CDP). CDPs allow teams to streamline first-party data collection, create complete customer profiles, and activate these to deliver engaging experiences for their users. However, traditional CDPs struggle with high-volume scenarios like election betting because they store and persist all customer data within their own infrastructure. Consider the following:

• Each page load, bet placement, and odds check generates a trackable event
• Multi-device tracking multiplies data volume
• Real-time odds adjustments create continuous data streams

The storage costs for this volume of data are astronomical for the CDP provider, and so they pass these on to their customers through higher pricing. Faced with a limited budget, teams are then forced to collect just a fraction of the data they need to fully understand the player journey.

The warehouse-native advantage

At this point, data teams often opt to build a customer data platform in-house, realizing that partnering with a third-party solution is no longer viable from a cost perspective, and limits what they can ultimately do with the player data.

Unfortunately, data leaders realize this approach creates another challenge entirely after spending months pulling already-limited engineering resources from value-additive work to manage integrations, clean data, or resolve identities.

This is where RudderStack's warehouse-native approach to customer data infrastructure provides a unique advantage. By eliminating data persistence on our end and leveraging your existing data warehouse or data lake, we can offer significant cost savings that scale with your volume. Here's how:

• No data storage overhead: Since we don't store your data, we don't pass storage costs on to you.
• Flexible pricing options: Choose between per-event pricing or monthly tracked users (MTUs). Select what works best for your use case.
• Economies of scale: As your event volume grows, your cost per event decreases.
• Infrastructure optimization: Leverage the stack you’ve already invested in.

Future-proofing for the next big surge

With the number of online wagers only growing and events like elections drawing billions in bets, you need to prepare your infrastructure for future surges if you’re looking to make data-driven product decisions. Here's how RudderStack helps:

1. Extreme scalability: Supports peak loads of 1M+ events per second
2. Proven reliability: Processes 100B+ events per month across thousands of customers
3. Real-time performance: Optimized for low latency, even at scale
4. Compliance ready: Centralized data management in your own warehouse simplifies regulatory compliance

Taking Action

As the gaming industry continues to grow, teams need to evaluate their data infrastructure against future needs. Here are key steps to consider:

1. Understand your volume: Calculate your typical event volume (page loads, bets placed, odds checks) and how it fluctuates during peak periods.
2. Assess Infrastructure: Evaluate if your current setup can scale cost-effectively.
3. Compare Pricing Models: Analyze whether per-event or MTU pricing would be more cost-effective for your use case.
4. Plan for Growth: Build a data infrastructure that grows with your product, not against it.

The election betting surge has shown that gaming platforms need robust, cost-effective data infrastructure more than ever. By adopting a warehouse-native approach with flexible pricing options, you can handle massive data volumes while maintaining control over costs.

Ready to learn how RudderStack can future-proof your data stack? Get a demo from our team today.