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Slow Websites Will Cost Retailers Big Bucks This Holiday Season

Top Retail Sites Not Prepared for Holiday Shopping Boom
Kent Alstad

As the 2015 holiday shopping season rapidly approaches, only a few retailers – 12% of the top 100 ecommerce sites – are currently meeting customer expectations for both content and page speed, according to Radware's latest web performance report, State of the Union: Ecommerce Page Speed & Web Performance Summer 2015. It is even more surprising that 14% of top retailers take more than 10 seconds just to become functional, an increase from 9% in February 2015.


According to Statista, retail sales are estimated to exceed $1.7 trillion in 2015. Radware’s findings are a warning to the retail industry: bulky, slow web pages will fail to convert sales – even when top retailer’s sites may meet consumer demand for more content and complexity.

In fact, 57% of site visitors will abandon a web page after just three seconds if they are unable to interact with the key content. This Time to Interact (TTI) is critical.

“Site performance and download times are some of the most critical aspects of ecommerce that correlate to conversion rates,” said Sucharita Mulpuru, Forrester Research.

No retailer wants to abandon up to 57% of their inbound site traffic, especially during the holiday selling season. Retailers must invest in user experience for online customers, and that includes both content and page load time. Serving more content to customers is expected but the goal is delivering more content, faster. That’s the "magic formula". Web performance optimization, or lack thereof, will directly impact the bottom line for retailers this holiday season.

Today’s consumers expect more feature-rich browsing and shopping experiences that rely heavily on the increased use of high-pixel-count imagery, GIF and animated file formats, JavaScript, and app-like animations. Radware found that because of this, site owners are adding more features but they are not taking advantage of core optimization techniques. These issues result in increasing page sizes and complexity that typically contribute to slower load times.

Additional findings from the report include:

Page size and complexity are common contributors to slower load times, impacting the TTI. The median page is 1945 KB in size and contains 169 resource requests. The median Time to Interact is 5.5 seconds, which is considerably slower than users’ reported wait-time threshold of 3 seconds. The slowest page on the top 100 list had a TTI of 34.1 seconds.

Site owners have not implemented the latest core optimization techniques. Despite the fact that images comprise 50% to 60% of the average page’s total size, 48% of the top 100 sites received an “F” score from webpagetest.org for image compression.

The report also includes 14 tips to take your website from slow to "go" this holiday season, including:

Preload resources in the browser using an automated solution to increase load speed

Reformat images – avoid wasting bandwidth with unnecessarily high resolution

Rethink the design and location of call to action links below large feature banners

House heavy content below the fold to allow a faster loading experience

Consolidate JavaScript and CSS into common files

Compress text using common technologies like gzip

Kent Alstad is VP of Acceleration at Radware.


Methodology: The tests in this study were conducted using an online tool called WebPagetest – an open-source project primarily developed and supported by Google – which simulates page load times from a real user’s perspective using real browsers. Radware tested the home page of the top 100 sites from the Alexa Retail 500 three consecutive times. The system automatically clears the cache between tests. The median test result for each home page was recorded and used in our calculations. The tests were conducted on July 16, 2015, via the WebPagetest.org server in Dulles, VA, using Chrome 43 on a DSL connection. In very few cases, WebPagetest rendered a blank page or an error in which none of the page rendered. These tests were re-run with the same criteria, and flagged as such, with the results substituted in the list. To identify the Time to Interact (TTI) for each page, Radware generated a timed filmstrip view of the median page load for each site in the Alexa Retail 100. Time to Interact is defined as the moment that the featured page content and primary call-to-action button or menu is rendered in the frame.

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Slow Websites Will Cost Retailers Big Bucks This Holiday Season

Top Retail Sites Not Prepared for Holiday Shopping Boom
Kent Alstad

As the 2015 holiday shopping season rapidly approaches, only a few retailers – 12% of the top 100 ecommerce sites – are currently meeting customer expectations for both content and page speed, according to Radware's latest web performance report, State of the Union: Ecommerce Page Speed & Web Performance Summer 2015. It is even more surprising that 14% of top retailers take more than 10 seconds just to become functional, an increase from 9% in February 2015.


According to Statista, retail sales are estimated to exceed $1.7 trillion in 2015. Radware’s findings are a warning to the retail industry: bulky, slow web pages will fail to convert sales – even when top retailer’s sites may meet consumer demand for more content and complexity.

In fact, 57% of site visitors will abandon a web page after just three seconds if they are unable to interact with the key content. This Time to Interact (TTI) is critical.

“Site performance and download times are some of the most critical aspects of ecommerce that correlate to conversion rates,” said Sucharita Mulpuru, Forrester Research.

No retailer wants to abandon up to 57% of their inbound site traffic, especially during the holiday selling season. Retailers must invest in user experience for online customers, and that includes both content and page load time. Serving more content to customers is expected but the goal is delivering more content, faster. That’s the "magic formula". Web performance optimization, or lack thereof, will directly impact the bottom line for retailers this holiday season.

Today’s consumers expect more feature-rich browsing and shopping experiences that rely heavily on the increased use of high-pixel-count imagery, GIF and animated file formats, JavaScript, and app-like animations. Radware found that because of this, site owners are adding more features but they are not taking advantage of core optimization techniques. These issues result in increasing page sizes and complexity that typically contribute to slower load times.

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Page size and complexity are common contributors to slower load times, impacting the TTI. The median page is 1945 KB in size and contains 169 resource requests. The median Time to Interact is 5.5 seconds, which is considerably slower than users’ reported wait-time threshold of 3 seconds. The slowest page on the top 100 list had a TTI of 34.1 seconds.

Site owners have not implemented the latest core optimization techniques. Despite the fact that images comprise 50% to 60% of the average page’s total size, 48% of the top 100 sites received an “F” score from webpagetest.org for image compression.

The report also includes 14 tips to take your website from slow to "go" this holiday season, including:

Preload resources in the browser using an automated solution to increase load speed

Reformat images – avoid wasting bandwidth with unnecessarily high resolution

Rethink the design and location of call to action links below large feature banners

House heavy content below the fold to allow a faster loading experience

Consolidate JavaScript and CSS into common files

Compress text using common technologies like gzip

Kent Alstad is VP of Acceleration at Radware.


Methodology: The tests in this study were conducted using an online tool called WebPagetest – an open-source project primarily developed and supported by Google – which simulates page load times from a real user’s perspective using real browsers. Radware tested the home page of the top 100 sites from the Alexa Retail 500 three consecutive times. The system automatically clears the cache between tests. The median test result for each home page was recorded and used in our calculations. The tests were conducted on July 16, 2015, via the WebPagetest.org server in Dulles, VA, using Chrome 43 on a DSL connection. In very few cases, WebPagetest rendered a blank page or an error in which none of the page rendered. These tests were re-run with the same criteria, and flagged as such, with the results substituted in the list. To identify the Time to Interact (TTI) for each page, Radware generated a timed filmstrip view of the median page load for each site in the Alexa Retail 100. Time to Interact is defined as the moment that the featured page content and primary call-to-action button or menu is rendered in the frame.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...