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E-Commerce Secrets to Retail Holiday Success - Part 2

Ari Weil

Optimizing online web performance is critical to keep and convert customers and achieve success for the holidays and the entire retail year. Akamai's The State of Online Retail Performance report lays out the challenges online retailers face.

Start with E-Commerce Secrets to Retail Holiday Success - Part 1


Mobile Users Bounce Around

As noted above, half of the online shoppers browse for products and services on their mobile devices. And of those, more than half are going to bounce. The stickiest consumers are on tablets, where the bounce rate averages 40.6 percent. Desktop users fall in the middle, with a 43 percent bounce rate. Unfortunately, losing up to half of your visitors is the harsh reality of online commerce. Consumers aren't patient, and they are only one back-button click from Google search results and competitors' websites.

A one-second delay can bump the bounce rate by almost 50 percent on mobile, and a two-second delay more than doubles it. Mobile users seem to be the most sensitive ones, but the impacts are similar with delays on desktop and tablet. If you are acquiring customers through search engine marketing campaigns, then these user bounce rates mean you not only missed the chance to show these customers your products, but you also paid a per-click price just to have the user leave the page before it even finished loading.

An efficient and effective strategy for minimizing bounce rate is to be visually complete as quickly as possible and load important page elements above the fold first. Once users can see and interact with the page, they assume the page is loaded even if other elements or third-party scripts are still loading in the background.

A start-render measurement is often the metric tracked here to demonstrate the point in time when something was displayed on the screen. A maximum start-render time of 0.9 seconds on desktop, 1.3 seconds on mobile, and 1.5 seconds on tablets corresponds to the lowest bounce rate on each device.

Third-Party Scripts

When it comes to providing a fast and seamless experience, less is often more. By reducing the number of page elements on a page and by utilizing the least amount of third-party scripts, one can provide the best page performance. But we also should keep in mind the entire customer experience. For example, we know that consumers convert at a higher level on personalized pages, and personalization usually requires third-party scripts. So, should one remove all third-party scripts and give consumers a Google like search page? Probably not. If third-party scripts are used to appropriately improve the customer experience and are loaded asynchronously, they can increase conversion.

Interestingly, the highest-converting desktop and tablet pages contained 20–25 third-party scripts, and the best-converting mobile pages contained 15–20. This is consistent with a joint machine learning project conducted by Akamai and Google which found that user sessions that converted contained 48 percent more scripts than sessions that did not.

That said, those scripts should be used judiciously and optimized well; simply throwing more scripts on the page will certainly not help conversion. Before adding elements to a page, retailers should always ask – what customer struggle point does this address or how does this improve the customer experience? If the answer to these questions is none, then perhaps that new element is not a priority item to add to the page.

Holiday Preparedness Starts Now

The Akamai study offers a lot of data to parse. But what is the real bottom line for online retailers?

Optimize for mobile — its influence on sales is only going to increase.

Monitor your site all the time to spot poorly-performing pages so you don't leave money on the table.

Run load tests before peak traffic times based on real user traffic patterns.

Prioritize customer experience and remove unnecessary third-party tags.

Implement a robust caching and content delivery strategy to ensure uptime and scalability.

Holiday shopping and promotion start earlier every year, so you can't wait until November 22. Start now, be thorough, and make it the best online year ever.

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.

E-Commerce Secrets to Retail Holiday Success - Part 2

Ari Weil

Optimizing online web performance is critical to keep and convert customers and achieve success for the holidays and the entire retail year. Akamai's The State of Online Retail Performance report lays out the challenges online retailers face.

Start with E-Commerce Secrets to Retail Holiday Success - Part 1


Mobile Users Bounce Around

As noted above, half of the online shoppers browse for products and services on their mobile devices. And of those, more than half are going to bounce. The stickiest consumers are on tablets, where the bounce rate averages 40.6 percent. Desktop users fall in the middle, with a 43 percent bounce rate. Unfortunately, losing up to half of your visitors is the harsh reality of online commerce. Consumers aren't patient, and they are only one back-button click from Google search results and competitors' websites.

A one-second delay can bump the bounce rate by almost 50 percent on mobile, and a two-second delay more than doubles it. Mobile users seem to be the most sensitive ones, but the impacts are similar with delays on desktop and tablet. If you are acquiring customers through search engine marketing campaigns, then these user bounce rates mean you not only missed the chance to show these customers your products, but you also paid a per-click price just to have the user leave the page before it even finished loading.

An efficient and effective strategy for minimizing bounce rate is to be visually complete as quickly as possible and load important page elements above the fold first. Once users can see and interact with the page, they assume the page is loaded even if other elements or third-party scripts are still loading in the background.

A start-render measurement is often the metric tracked here to demonstrate the point in time when something was displayed on the screen. A maximum start-render time of 0.9 seconds on desktop, 1.3 seconds on mobile, and 1.5 seconds on tablets corresponds to the lowest bounce rate on each device.

Third-Party Scripts

When it comes to providing a fast and seamless experience, less is often more. By reducing the number of page elements on a page and by utilizing the least amount of third-party scripts, one can provide the best page performance. But we also should keep in mind the entire customer experience. For example, we know that consumers convert at a higher level on personalized pages, and personalization usually requires third-party scripts. So, should one remove all third-party scripts and give consumers a Google like search page? Probably not. If third-party scripts are used to appropriately improve the customer experience and are loaded asynchronously, they can increase conversion.

Interestingly, the highest-converting desktop and tablet pages contained 20–25 third-party scripts, and the best-converting mobile pages contained 15–20. This is consistent with a joint machine learning project conducted by Akamai and Google which found that user sessions that converted contained 48 percent more scripts than sessions that did not.

That said, those scripts should be used judiciously and optimized well; simply throwing more scripts on the page will certainly not help conversion. Before adding elements to a page, retailers should always ask – what customer struggle point does this address or how does this improve the customer experience? If the answer to these questions is none, then perhaps that new element is not a priority item to add to the page.

Holiday Preparedness Starts Now

The Akamai study offers a lot of data to parse. But what is the real bottom line for online retailers?

Optimize for mobile — its influence on sales is only going to increase.

Monitor your site all the time to spot poorly-performing pages so you don't leave money on the table.

Run load tests before peak traffic times based on real user traffic patterns.

Prioritize customer experience and remove unnecessary third-party tags.

Implement a robust caching and content delivery strategy to ensure uptime and scalability.

Holiday shopping and promotion start earlier every year, so you can't wait until November 22. Start now, be thorough, and make it the best online year ever.

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.