According to comScore reported holiday season US retail e-commerce spending from desktop computers for the entire November-December 2015 holiday season, $56.4 billion was spent online on desktop computers, marking a 6-percent increase versus the corresponding days last year.
Cyber Monday (Monday, Nov. 30) once again ranked as the heaviest spending day of the year with more than $2 billion in desktop buying for the second year in a row.
Total digital spend for the holiday season, when inclusive of comScore’s preliminary mobile commerce estimates, reached $69.1 billion, about a 13-percent annual gain vs. $61.3 billion spent in the 2014 season. Mobile commerce is estimated to have accounted for 18 percent of total digital commerce in November-December 2015, an increase from 13 percent in the previous season. A total of $12.7 billion was spent via smartphones and tablets during this period, up a staggering 59-percent versus year ago.
comScore’s holiday season forecast had expected desktop e-commerce to grow 9 percent to $58.3 billion and mobile commerce to grow 47 percent to $11.7 billion. While desktop spending fell short by 3 percentage points and $1.9 billion, preliminary mobile estimates suggest it exceeded forecast by 12 percentage points and nearly $1 billion, helping to offset the shortfall on desktop.
“Despite falling slightly short of our original forecast of 14 percent growth, the 2015 online holiday shopping season was nevertheless very successful with growth rates well into double digits and once again far exceeding that of brick-and-mortar,” said comScore chairman emeritus Gian Fulgoni. “Fairly early on it became clear that desktop e-commerce would likely underperform our expectations while mobile commerce was poised to over perform, but for the most part signs continued to point to hitting that 14-percent overall growth estimate. Where the season ultimately fell short was in the last two weeks of the year, and in particular the week before Christmas. We had anticipated heavy desktop spending through Free Shipping Day on December 18th that unfortunately did not materialize, and spending began to soften more than expected by the Wednesday of that week.”
Fulgoni continued: “If there is an underlying takeaway from this holiday season, I think it will be remembered as the one where ‘mobile ate brick-and-mortar.’ Mobile became an essential shopping channel nearly doubling desktop in total retail traffic, while seeing growth rates approaching 60 percent year-over-year at the same time that offline retail experienced softness throughout the season. I believe that we’ve seen a paradigm shift in 2016 where the future of retail will increasingly be defined by consumers’ behavior on mobile.”
Cyber Monday (Nov. 30), for the sixth consecutive year, ranked as the heaviest online buying day with $2.28 billion in desktop spending. The day after Cyber Monday ranked second for the season at $1.95 billion, followed by Black Friday (Nov. 27) with $1.656 billion and Friday, Dec. 11 with $1.477 billion. For the entire season, sixteen individual days exceeded $1 billion in online spending via desktop, an increase from fifteen the previous year.
Hot Topic
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
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.