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E-Commerce Secrets to Retail Holiday Success - Part 1

Ari Weil

Since forever, fourth-quarter holiday sales have been the key to retail success. It was true when retail was strictly bricks-and-mortar, and it is true now when online counts for a bigger and bigger share of holiday sales. Optimizing online web performance is critical to keep and convert customers and achieve success for the holidays and the entire retail year.


Recent research from Akamai indicates that website slowdowns as small as 100 milliseconds can significantly impact revenues. Whether on desktop, tablet or mobile, consumers will not tolerate delays. Higher-than-ever expectations for mobile pose challenges.

Akamai's The State of Online Retail Performance report lays out the challenges online retailers face. But it also illuminates ideal performance benchmarks that retailers can target to make sure shoppers stick with their sites, explore their offerings, and convert into purchasers.

It takes effort to optimize your users' experience, both on the front-end and on the back-end, to achieve those benchmarks. To be successful in the fourth-quarter holiday season, that work needs to start now and continue right through the end of the year.

Study Data Correlate Web Performance and Retail Results

For the study, Akamai assembled a massive volume of user data — the equivalent of 10 billion user visits — to uncover the performance sweet spots that correlated to the lowest bounce rates, the longest user sessions, and the highest conversions.

The data show that desktop is still the online channel that delivers the highest conversions and, by inference, the most revenue. And while mobile now accounts for virtually half of online shopping, it still lags far behind in keeping and converting shoppers — just one in five transactions are completed on mobile, compared to desktop's nearly 70 percent share of completed transactions.

These numbers, however, can be deceiving when we take the consumers' cross-device journey into consideration. Many users will start their product research process on mobile devices because of their convenience. For example, users might use their mobile devices when they are on the train going to the office, and then they will complete the transaction on a desktop at work. If we look at it through this lens, a poor mobile experience will not only hurt your mobile conversion but quite possibly also damage your desktop conversion rate.

Tablets are a modest but consistent bright spot, according to the study. While they represent the smallest share of shoppers, they enjoy high conversion and low bounce rates, and consumers appear to be more tolerant of small slowdowns or performance glitches on tablets than on either desktop or mobile. These findings once again highlight the multi-device consumer path to purchase; while they may not be willing to wait on other devices, often when users are on their tablets, they are multi-screening, meaning it may increase their willingness to wait.

A One-Second Slowdown Slashes Conversion by 20 Percent

There is simply no wiggle room when it comes to website load time. Even just a 100ms delay — 1/10 of a second — reduces conversion by 2.4 percent on desktop and over 7 percent on mobile. When the delay increases to a full second, conversion plummets by more than 20 percent on desktop and mobile and almost 18 percent on tablet.

The number to aim for is the load time that delivers “peak conversion,” when the highest proportion of visitors are going to complete an action. For desktop, the magic number is 1.8 seconds to achieve a conversion rate of 12.8 percent. For mobile, a 2.7 second load time correlates to a 3.3 percent conversion rate, and on tablets, a 1.9 second load time delivers 7.2 percent conversion.

On average, the difference between a converted and non-converted session is 1.1 seconds on desktop, 0.6 seconds on mobile, and 1.0 second on tablet. All of those numbers add up to one compelling conclusion: every millisecond matters.

Read E-Commerce Secrets to Retail Holiday Success - Part 2

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

E-Commerce Secrets to Retail Holiday Success - Part 1

Ari Weil

Since forever, fourth-quarter holiday sales have been the key to retail success. It was true when retail was strictly bricks-and-mortar, and it is true now when online counts for a bigger and bigger share of holiday sales. Optimizing online web performance is critical to keep and convert customers and achieve success for the holidays and the entire retail year.


Recent research from Akamai indicates that website slowdowns as small as 100 milliseconds can significantly impact revenues. Whether on desktop, tablet or mobile, consumers will not tolerate delays. Higher-than-ever expectations for mobile pose challenges.

Akamai's The State of Online Retail Performance report lays out the challenges online retailers face. But it also illuminates ideal performance benchmarks that retailers can target to make sure shoppers stick with their sites, explore their offerings, and convert into purchasers.

It takes effort to optimize your users' experience, both on the front-end and on the back-end, to achieve those benchmarks. To be successful in the fourth-quarter holiday season, that work needs to start now and continue right through the end of the year.

Study Data Correlate Web Performance and Retail Results

For the study, Akamai assembled a massive volume of user data — the equivalent of 10 billion user visits — to uncover the performance sweet spots that correlated to the lowest bounce rates, the longest user sessions, and the highest conversions.

The data show that desktop is still the online channel that delivers the highest conversions and, by inference, the most revenue. And while mobile now accounts for virtually half of online shopping, it still lags far behind in keeping and converting shoppers — just one in five transactions are completed on mobile, compared to desktop's nearly 70 percent share of completed transactions.

These numbers, however, can be deceiving when we take the consumers' cross-device journey into consideration. Many users will start their product research process on mobile devices because of their convenience. For example, users might use their mobile devices when they are on the train going to the office, and then they will complete the transaction on a desktop at work. If we look at it through this lens, a poor mobile experience will not only hurt your mobile conversion but quite possibly also damage your desktop conversion rate.

Tablets are a modest but consistent bright spot, according to the study. While they represent the smallest share of shoppers, they enjoy high conversion and low bounce rates, and consumers appear to be more tolerant of small slowdowns or performance glitches on tablets than on either desktop or mobile. These findings once again highlight the multi-device consumer path to purchase; while they may not be willing to wait on other devices, often when users are on their tablets, they are multi-screening, meaning it may increase their willingness to wait.

A One-Second Slowdown Slashes Conversion by 20 Percent

There is simply no wiggle room when it comes to website load time. Even just a 100ms delay — 1/10 of a second — reduces conversion by 2.4 percent on desktop and over 7 percent on mobile. When the delay increases to a full second, conversion plummets by more than 20 percent on desktop and mobile and almost 18 percent on tablet.

The number to aim for is the load time that delivers “peak conversion,” when the highest proportion of visitors are going to complete an action. For desktop, the magic number is 1.8 seconds to achieve a conversion rate of 12.8 percent. For mobile, a 2.7 second load time correlates to a 3.3 percent conversion rate, and on tablets, a 1.9 second load time delivers 7.2 percent conversion.

On average, the difference between a converted and non-converted session is 1.1 seconds on desktop, 0.6 seconds on mobile, and 1.0 second on tablet. All of those numbers add up to one compelling conclusion: every millisecond matters.

Read E-Commerce Secrets to Retail Holiday Success - Part 2

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...