If you’ve ever checked online to see whether your local big box store has the item you need in stock or ordered a product you saw on social media straight through the app, you’re already aware of how technology is shaping the customer experience.

We’re in an age where people expect fast and simple service—but not all businesses know how to meet that demand effectively. In fact, 80 percent of companies believe they deliver a superior experience to customers, while only eight percent of customers agree, according to a survey by management consulting firm Bain and Company. This perception gap is partly thanks to how difficult it can be for companies to track customers’ shifting preferences and understand what they want right now.

Many of the companies that succeed in meeting their customers’ expectations are using the cloud to stream, store, and analyze data from multiple sources in real time. Streaming data analytics, when performed with data generated continuously by multiple sources, is a powerful tool for understanding conditions in constant change. In contrast, traditional batch data analytics uses datasets that have been stored over a period of time, providing insight into past events but giving little information on what is happening right now.

“Real-time data unlocks possibilities, enabling organizations to gain immediate insights and take action based on up-to-date information,” says Mindy Ferguson, VP, AWS Streaming and Messaging Services. “It allows for real-time analytics, anomaly detection, pattern recognition, and other techniques to identify trends and respond to events as they happen.”

Poshmark, a leading social marketplace for new and second-hand apparel, improved its online shopping experience and boosted sales after working with AWS to build a real-time data analytics platform. By gathering data from customer interactions with the Poshmark app or website, analyzing that data, using machine learning to generate personalized search recommendations based on customer preferences, and providing those to the customer—all in near-real time, Poshmark has made shopping easier for its customers. As a result, they've achieved an 8 percent improvement in clickthrough rates for customers using the search function, increasing its overall search conversions and sales.

The company also uses this platform to detect and stop, in real time, illegitimate sign-up and sign-in events from bots and other non-human traffic and to prevent account takeovers. “Poshmark can take in a large number of different kinds of data and, with stream processing, analyze that data to understand if there is an anomaly and detect fraud as a transaction is occurring in real time,” Ferguson says. “Poshmark can now prevent 80 percent of account takeovers compared with 45 percent before implementing its streaming data analytics platform.”

Using Real-Time Data to Drive Updates

The gaming industry has always been at the forefront of adopting new technologies, especially when it can be used to deliver a better experience for players. Gaming companies rely on real-time data streaming and analytics to understand how players are interacting with their games—then use that information to continuously make changes, push upgrades, and fix bugs.

"Game companies want to give each player a customized experience based on what they know about them as a user," Ferguson says. “This in-game experience requires data to understand how a player is reacting to changes made in the moment. The games we see coming out of the industry are more advanced and better because of real-time data.”

Players today expect new content and updates to roll out on a regular basis. With real-time data analytics, gaming companies can see how players are interacting with the game as they play, then quickly deliver content that keeps them coming back—from new skins for characters, to new tools, or even new areas to explore.

How Real-Time Data Can Improve Equipment Performance

While it may seem obvious that online retailers and gaming companies can benefit from real-time data analytics, it can be useful for a wide range of industries—including agriculture, where changing conditions can impact everything from crop yields to animal health.

On a farm, speed and efficiency matters. To help its customers run their farms more sustainably, AGCO Corporation, a global provider of industrial farming equipment and digital agricultural solutions, ingests and stores data from its smart farming equipment using a real-time data streaming and analytics service, built on AWS. This service continuously captures gigabytes of data per second from hundreds of thousands of sources to provide insights and real-time machine diagnostics. By connecting its smart equipment—handling functions like ventilation, lighting, and heating—to a building controller, AGCO can use the cloud to collect and analyze equipment data in real time. The service then sends the results back to the building, which uses machine learning and AI to adjust the equipment as needed.

This automated process saves time for the farmer and helps ensure that temperature, humidity, and other parameters are always set at the optimal levels, encouraging crop growth without wasting electricity. 

“By leveraging real-time streaming data, organizations can further harness the power of AI and machine learning to drive predictive analytics, capitalize on new opportunities, and build competitive advantage,” says Ferguson.

The ability to act on data in near real time through streaming data services is already making people’s lives easier, and the two will likely be more synonymous in years to come.

To find out more about how you can make better, faster decisions, create new experiences, and optimize your business with the power of data and machine learning, explore AWS for Data.

This story was produced by AWS and edited by WIRED Brand Lab.