Real-time insights has become a powerful differentiator for companies across many industries.
In partnership withStarTree
During Black Friday in 2024, Stripe processed more than $31 billion in transactions, with processing rates peaking at 137,000 transactions per minute, the highest in the company’s history. The financial-services firm had to analyze every transaction in real time to prevent nearly 21 million fraud attempts that could have siphoned more than $910 million from its merchant customers.
Yet, fraud protection is only one reason that Stripe embraced real-time data analytics. Evaluating trends in massive data flows is essential for the company’s services, such as allowing businesses to bill based on usage and monitor orders and inventory. In fact, many of Stripe’s services would not be possible without real-time analytics, says Avinash Bhat, head of data infrastructure at Stripe. “We have certain products that require real-time analytics, like usage-based billing and fraud detection,” he says. “Without our real-time analytics, we would not have a few of our products and that’s why it’s super important.”
Stripe is not alone. In today’s digital world, data analysis is increasingly delivered directly to business customers and individual users, allowing real-time, continuous insights to shape user experiences. Ride-hailing apps calculate prices and estimate times of arrival (ETAs) in near-real time. Financial platforms deliver real-time cash-flow analysis. Customers expect and reward data-driven services that reflect what is happening now.
