A Distributed Streaming Platform

Customer 360°

Customer 360° is a company’s single source of truth for everything about their customers likes and dislikes, behavior patterns and when they’re most likely to do certain actions. However, it is extremely complex to implement in today’s multi-channel, always-connected world. With data flowing in from a variety of sources such as mobile phone applications, websites, partner networks, and so on at a rapid pace from clicks, purchases, interactions and services – the list goes on – companies need to process all of this data in real time to understand trends, behaviors and predict what activity is likely to happen next.

Customer 360 is such a big deal because in today’s world, customers expect the right information at the right time whether online or in stores across all their devices. A business isn’t able to provide this unless it has a holistic, single view of each customer’s profile and activity.

Customer 360°

Effective Customer 360° projects focus on having:

Enter Confluent Platform, a streaming platform upon which you can unite all your systems, data sources, and operationalized your tried-and-true patterns, as well as run new experiments. At scale.

Why implementing Customer 360 is harder than it sounds

Getting a holistic view of the customer is almost impossible: with the growing number of devices and ways of interacting with a brand, getting a single view of a customer’s activity is extremely difficult.

Most business applications have been designed to automate the processing of a handful of particular interactions such as a customer profile update, or processing of an order, or support call tracking, or website clickstream collection. But only by viewing the output of all of these specialized systems can a holistic picture of a customer and her activities be assembled.

Why implementing Customer 360 is harder than it sounds

A central nervous system for customer data

Typically, the data warehouse is a first attempt to solve this problem. However, companies following this path were left with slow, out-of-date data which failed to provide a personalized experience for their end users.

What was missing in the architectural puzzle was a streaming platform. Notably, it’s low-latency performance and ability to consolidate different streams into a single view of customers that is updated continuously in real time. By providing a common standard for organizations to share, process and distribute data, streaming platforms can help to maximize positive customer interaction and engagement.

Placing a streaming platform at the heart of a business enables the discovery of new business opportunities. By both centralizing data across the company, and simultaneously distributing it to every application or system, new insights can reveal unexpected ways to build new revenue sources.

Why a streaming platform helps

Establish a single source of truth: a streaming platform can connect data warehouses, data lakes, applications that are generating data every second to create a single combined view of every individual. This makes it much simpler to leverage the right tool for the task at hand; be it enabling search or identify trends in behaviors and reacting appropriately.

Customer 360 Across Industries

By deploying a streaming platform, enterprises can increase revenue and create brand loyalty, two aspects that are critical to long-term success in today’s digital world. In addition, organizations have the opportunity to detect areas for growth in the future and create new products, as well as identify threats. Customers enjoy a seamless experience with the business no matter what channel they interact on, which makes them want to keep coming back.

Case Study: Fortune 500 Media & Entertainment

A Fortune 500 Media & Entertainment company counts on Confluent Enterprise to power their view of the customer.

To achieve a true 360° view of their customer they required a single source of truth that multiple producers of data can integrate with and rely on. Having a variety of data sources from web, tv, and mobile with a growing volume of data and range of development languages made it apparent that putting Confluent Enterprise at the heart of the infrastructure was the only way to efficiently leverage their organization’s data.

This allows their developers and data engineers to support outside teams with real-time data – powering predictive ad-placements with real-time stream processing data from the Streams API; having their support team pull up-to-date customer info from their data warehouse; and delivering real-time applications to their end users. From this central nervous system of data the media company is able to successfully meet their customer's expectations; cutting down the time to market for key data-driven functionality.

Case Study: Fortune 500 Media & Entertainment

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