Skip to main content

RSS Spending Soars, Despite Low Adoption

JupiterResearch finds that 63 percent of large companies plan to syndicate content via Really Simple Syndication (RSS) by the end of 2006.

According to a new report by JupiterResearch Senior Analyst Greg Dowling, currently only 29 percent of large companies (with more than $50 million in annual revenues) publish content via RSS. The growth of RSS is also highlighted by the fact that 48 percent of current RSS publishers are spending $250,000 or more to deploy and manage syndicated content. However, JupiterResearch has also found that spending at this level is inconsistent with the current rate of adoption.

"Despite low perceived adoption rates and definitive measurement standards, site operators are increasing spending on RSS deployments," said Dowling. "In order to maximize their investment in RSS, site operators should leverage emerging tools and technologies specifically tailored to RSS."

RSS users are heavier consumers of online media than traditional online users, and thus represent a prime demographic for online media publishers. Marketers can either modify their RSS feeds to individual users through individualized RSS (IRSS) or create traditional broadcast feeds. IRSS feeds are subscriber-centric and created in much the same way as targeted e-mail campaigns, including all of the measurement benefits associated with e-mail marketing.

"The primary challenge to greater adoption is a lack of experience with RSS and resources to deploy it," said David Schatsky, President of JupiterKagan. "However, recent offerings from e-mail service providers (ESP) and RSS service providers are lowering the barrier for feed management, deployment and measurement."

Popular posts from this blog

AI Agents Have Memory. Where is The Security?

Enterprise AI adoption keeps running into the same wall: the moment sensitive data, model weights, or agent memory leave a tightly controlled environment, security teams lose visibility into what happens to them while the workload is actually running. Confidential computing exists to close that gap, and new research from ABI Research shows the technology has matured enough, across CPUs, GPUs, containers, and now agentic AI, to become a foundational requirement for enterprises building sovereign AI infrastructure: computing environments they control end to end rather than simply rent. Protection is Moving From CPUs to GPUs ABI Research finds that CPU-based confidential computing is closest to mass-market adoption, the product of years spent hardening chip-level isolation for general workloads. GPU-based confidential computing is now generating the strongest momentum, and for good reason. It addresses one of the largest unresolved gaps in AI security: protecting data and models while inf...