Blue Triangle introduced VitalScope™, a tool for improving Core Web Vitals (CWV), Google user experience and organic site traffic.
The VitalScope™ feature within Blue Triangle's Continuous Experience Optimization platform helps online and omnichannel businesses turn their real user digital experience data and Google's CWV recommendations into actionable fixes.
Blue Triangle followed the published guidance of the Google Developer Relations team to develop a tool to quickly improve CWV scores to achieve consistent results. VitalScope™ provides a debugging blueprint for correcting hidden problems compromising performance that have the largest impact on your site, so teams can effectively optimize scores and user experience.
"We took the guidance from Google and built it into a tool that, in effect, puts your Core Web Vitals under a microscope to discover why scores are dropping and tells you exactly how to fix them for greater bottom-line results," said Blue Triangle CEO Lance Ullom. "Our customers are always looking for ways to reduce friction and provide a better experience. So, VitalScope was a lightbulb moment to get even more actionable insights from their RUM (Real User Monitoring) data."
VitalScope™ allows product teams to take deep dives beneath CWV scores, providing detailed information for each metric. It identifies every element contributing to a bad score, so DevOps knows what to fix. This new feature within Blue Triangle's platform helps websites capture and analyze this specific data in the context of what Google is looking at.
"Every marketer knows it's a big deal if any of your Core Web Vitals drop. The challenge has been understanding why and how to partner with dev resources to fix problems," said Chuck Moxley, global head of marketing at Blue Triangle. "VitalScope provides the missing piece that enables marketing, digital business teams and DevOps to work together to maintain healthy scores and Google search ranking."
VitalScope is available now to Blue Triangle customers.
The Latest
Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...
While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...
A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...