Keynote is helping retailers get ready for the coming mobile holiday shopping season with a free offer for mobile testing on its DeviceAnywhere platform.
Keynote is launching "Mobile Ready for the Holidays 2012" for qualified retailers, a 10 hour free trial on the DeviceAnywhere platform and a free assessment of their mobile implementation. Offer is valid until Black Friday.
As smartphones and tablets become ever more central to consumers and businesses, many companies - including many large retailers - are still leaving themselves much exposed through a lack of proper mobile testing.
45% of American adults now own smartphones, spurring a fundamental shift in browsing and buying habits in an increasingly three-screen world (desktops, smartphones, and tablets). Retailers, in particular, have no time to waste to prepare for this coming holiday shopping season, which will be the biggest test yet for retailers using mobile channels as a serious source of online business.
Mobile is expected to be responsible for over 20% of retail site visits during the 2012 holiday season. The mobile retail channel is currently the fastest-growing form of mobile commerce, which will experience a quadrupling of current 2012 revenues, accounting for approximately $25 billion by 2017.
Despite this fundamental shift toward mobile in a three screen world, many retailers and other US businesses are unaware of the roadblocks they are putting in the way of realizing greater revenues and productivity due to software bugs that are the result of inadequate internal Quality Assurance processes for mobile apps and websites. Slow page delivery and bugs on mobile apps and websites could cost retailers dearly, as impatient customers lose patience and move to the sites of alternative vendors.
Whether mobile apps and websites are home-grown, outsourced or bought off-the-shelf, an appropriate mobile testing process must include both pre-launch testing and ongoing monitoring. Pre-launch testing can be done manually or automated. As many enterprises are familiar with the time and cost savings it can deliver, automated mobile testing is typically the best approach. When the mobile channel is launched, ongoing monitoring needs to be in place, so the mobile application or website is constantly monitored to ensure maximum uptime, and therefore maximum revenue and productivity.
"Despite improvements in the enterprise mobile testing market, most businesses have yet to replicate the efforts they put into the Quality Assurance for desktop-based applications," said Ren Bloom, vice president of marketing at Keynote. "This is the year for retailers to embrace mobile quality testing and improve their revenue and productivity."
The Latest
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...