Skip to main content

Why Is a Crash-Free Black Friday/Cyber Monday Weekend So Elusive?

Mehdi Daoudi
Catchpoint

The online retail industry has yet to have a Black Friday/Cyber Monday weekend unscathed by web performance (speed and availability) problems. Luckily, performance during 2019's hyper-critical online holiday shopping weekend was better than in years past, as we did not see any systemic, lengthy outages.

While no website went completely down, in 2019 customers expect blisteringly fast load times. So the new rule is: slow is the new down.

40 percent of consumers will leave a page that takes longer than three seconds to load

Several retailers did experience significant problems, most notably Costco which endured 17 hours of slow performance that ultimately led to the company losing an estimated $11 million in sales. H&M experienced 10 hours of slowdown which was also costly, as the most recent statistics show 40 percent of consumers will leave a page that takes longer than three seconds to load.

Statistics show retailers lose half a billion dollars each year due to slow websites, with conversion rates also dropping seven percent as a result. So why have online retailers yet to figure out how to be crash-free during this all-important peak traffic period? We've identified several reasons for this, including:

Some retailers still don't have capacity figured out

Although most ecommerce and online retailers were prepared well in advance of Black Friday, others were caught off guard when traffic volume spiked. The extra load that holiday sales bring is one of the main causes of performance issues for online retailers. Servers are simply unable to handle the influx of traffic, which can cause a major bottleneck in the application delivery chain. Costco was among the first retailers to hit this performance roadblock.

This points to the fact that some retailers aren't conducting sufficient load testing. They may not have the resources to do so, and unless they make the decision to move to a scalable hosted platform, they are likely doomed for repeat failures. A case in point is H&M, which experienced similar performance issues on Black Friday 2017.

Some online retailers aren't measuring comprehensively enough

Slow performance anywhere in the conversion path (search page, product detail page, add to cart, etc.) can hurt an online retailer substantially. Yet, many are still relying on binary homepage measurements of a home page being "up" or "down," which is far too simplistic. Applications can be unreachable even if a web page is available.

Costco's performance this year was a prime example of this. Even at times when Costco's homepage was readily available, the search results page, product details page, and the shopping cart page were still considerably slow. It is absolutely critical to monitor the entire conversion path and time to complete end-to-end transactions.

Third parties — both infrastructure providers and other external third-party services — continue to be a source of problems

There were no instances in 2019 of a popular third-party service going down entirely or slowing dramatically, consequently dragging down all the sites it supports. One reason for the decline in third-party issues may relate to the fact that shoppers did not wait until Friday to place orders. The increase in website traffic on the Tuesday and Wednesday before Thanksgiving distributed traffic across more days for these third parties, which come under tremendous load during the holidays.

There were, however, several isolated instances that continue to demonstrate how important it is to closely monitor third-parties, particularly those existing on the external network which lately have been an increasing source of problems. For instance:

■ On Thanksgiving Day, Home Depot's website slowed down when issues arose while fetching content from a particular host mapped to Google Cloud.

■ Forever21 was briefly impacted by high connect and wait times on Saturday, November 30 due to its inability to load images and scripts served from their CDN. This impacted end users for approximately 15 minutes.

■ Sephora experienced performance volatility from a specific host, a third-party community integration, on the page. The community platform used by Sephora experienced performance issues, which, in turn, slowed down the site.

Conclusion

Ecommerce and online retailers continue to optimize and improve performance of webpages as well as critical transactions under load. However, in 2019 many issues continued to surface due to well-known problems, including insufficient capacity, measurements and third parties. With peak traffic periods so critical to the yearly revenue picture, online retailers need to understand that truly effective performance management requires year-round, proactive, customer-centric monitoring. This is the best way for organizations to ensure they're delivering to customers and users the performance levels they have come to expect, at all times of year.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

The Latest

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 ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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 ...

Why Is a Crash-Free Black Friday/Cyber Monday Weekend So Elusive?

Mehdi Daoudi
Catchpoint

The online retail industry has yet to have a Black Friday/Cyber Monday weekend unscathed by web performance (speed and availability) problems. Luckily, performance during 2019's hyper-critical online holiday shopping weekend was better than in years past, as we did not see any systemic, lengthy outages.

While no website went completely down, in 2019 customers expect blisteringly fast load times. So the new rule is: slow is the new down.

40 percent of consumers will leave a page that takes longer than three seconds to load

Several retailers did experience significant problems, most notably Costco which endured 17 hours of slow performance that ultimately led to the company losing an estimated $11 million in sales. H&M experienced 10 hours of slowdown which was also costly, as the most recent statistics show 40 percent of consumers will leave a page that takes longer than three seconds to load.

Statistics show retailers lose half a billion dollars each year due to slow websites, with conversion rates also dropping seven percent as a result. So why have online retailers yet to figure out how to be crash-free during this all-important peak traffic period? We've identified several reasons for this, including:

Some retailers still don't have capacity figured out

Although most ecommerce and online retailers were prepared well in advance of Black Friday, others were caught off guard when traffic volume spiked. The extra load that holiday sales bring is one of the main causes of performance issues for online retailers. Servers are simply unable to handle the influx of traffic, which can cause a major bottleneck in the application delivery chain. Costco was among the first retailers to hit this performance roadblock.

This points to the fact that some retailers aren't conducting sufficient load testing. They may not have the resources to do so, and unless they make the decision to move to a scalable hosted platform, they are likely doomed for repeat failures. A case in point is H&M, which experienced similar performance issues on Black Friday 2017.

Some online retailers aren't measuring comprehensively enough

Slow performance anywhere in the conversion path (search page, product detail page, add to cart, etc.) can hurt an online retailer substantially. Yet, many are still relying on binary homepage measurements of a home page being "up" or "down," which is far too simplistic. Applications can be unreachable even if a web page is available.

Costco's performance this year was a prime example of this. Even at times when Costco's homepage was readily available, the search results page, product details page, and the shopping cart page were still considerably slow. It is absolutely critical to monitor the entire conversion path and time to complete end-to-end transactions.

Third parties — both infrastructure providers and other external third-party services — continue to be a source of problems

There were no instances in 2019 of a popular third-party service going down entirely or slowing dramatically, consequently dragging down all the sites it supports. One reason for the decline in third-party issues may relate to the fact that shoppers did not wait until Friday to place orders. The increase in website traffic on the Tuesday and Wednesday before Thanksgiving distributed traffic across more days for these third parties, which come under tremendous load during the holidays.

There were, however, several isolated instances that continue to demonstrate how important it is to closely monitor third-parties, particularly those existing on the external network which lately have been an increasing source of problems. For instance:

■ On Thanksgiving Day, Home Depot's website slowed down when issues arose while fetching content from a particular host mapped to Google Cloud.

■ Forever21 was briefly impacted by high connect and wait times on Saturday, November 30 due to its inability to load images and scripts served from their CDN. This impacted end users for approximately 15 minutes.

■ Sephora experienced performance volatility from a specific host, a third-party community integration, on the page. The community platform used by Sephora experienced performance issues, which, in turn, slowed down the site.

Conclusion

Ecommerce and online retailers continue to optimize and improve performance of webpages as well as critical transactions under load. However, in 2019 many issues continued to surface due to well-known problems, including insufficient capacity, measurements and third parties. With peak traffic periods so critical to the yearly revenue picture, online retailers need to understand that truly effective performance management requires year-round, proactive, customer-centric monitoring. This is the best way for organizations to ensure they're delivering to customers and users the performance levels they have come to expect, at all times of year.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

The Latest

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 ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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 ...