How to Ensure Business Continuity During Holiday Peak Traffic in 2018
How to Ensure Business Continuity During Holiday Peak Traffic in 2018
It's never too early to begin planning for the most lucrative shopping days of the year. Keep your performance up and your customers happy this year.
Join the DZone community and get the full member experience.Join For Free
Black Friday/Cyber Monday (BFCM) sales were bigger than ever in 2017, as sales for the holiday hit about $3.34 billion on Black Friday and even higher on Cyber Monday: $3.45 billion. That’s $6.79 billion in two days.
With such record-breaking online sales, it’s a real shame if your site is down.
Black Friday/Cyber Monday traffic taking down websites is a common problem for retailers as the holiday shopping season kicks off. Big retail companies like Macy’s and Lowe’s failed to heed the lessons of Black Fridays past and experienced major shopping jams, as their sites just couldn’t handle the heavy traffic. It’s happened before at Target, Victoria’s Secret’s, and Express Inc., costing them customer loyalty and a significant amount of revenue.
Macy's Website Crashes for the Second Straight Year
At least five retailers — Macy’s, Lowe’s, J. Crew, and U.K.-based retailers the Perfume Shop and Game — were affected by technical glitches on Black Friday that slowed purchasing activity and transaction processing on the busiest shopping day of the year.
Macy’s confirmed by Friday evening that earlier in the day credit card processing was slowed due to system “over-capacity” problems, an issue that affected stores in Chicago, Washington, D.C., San Diego and other markets, as well as the retailer’s website, according to ABC News and other media reports. This is the second straight year that Macy’s experienced a website crash, while Target suffered one in 2015 and numerous other retailers have had slower-than-usual processing times for online and mobile purchasing between Black Friday and Cyber Monday in recent years.
With mobile once again proving its importance, as mobile purchases surpass desktop throughout the entire weekend, it’s key to ensure a smooth customer experience at all times. Amazon shows that Thanksgiving mobile orders went up 50% from 2016 while Business Insider reports that “This was the first year that computers generated less than half of all online orders, comprising only 49% of online sales on Black Friday.” This is in line with BI Intelligence’s forecast— which expects eCommerce to grow at a 15.4% compound annual growth rate (CAGR) to hit $798 billion in 2021. No doubt that mobile is the future of eCommerce as we know it.
Why Are Major eCommerce Sites Crashing?
Many retailers say the technical glitches are due to capacity-related issues, something that could have been avoided with better planning — after all, what store chain isn’t expecting its system or network capacity to be pushed beyond usual limits this particular weekend of the year? Retailers must work hard to make sure this doesn’t happen again, as customers do not easily forgive: 68% of shoppers will leave the site and look elsewhere if they encounter basic functionality issues.
Website crashes and technical glitches can also lead to a decline in purchases and active trade, as Macy’s experienced back in 2016. According to Bloomberg report, Macy’s site couldn’t keep up with the heavy traffic flowing, leading to a reported decline of 1.71% during active trading on Friday. So not only were potential customers disappointed, causing them to leave the site or hit the refresh button over and over, but this downtime issue actually hurt the $13.52 billion retailer’s stocks.
How Can Retailers Prevent Crashes at High Peak Traffic?
In our internal analysis of the holiday season, we found that retailers using GigaSpaces technologies achieved success in surpassing key metrics for online retailing app performance. Notable metrics from our internal analysis over the years include:
A Story from the War Room
We sent our field engineer to work on-site with one of our top eCommerce customers. Here are some useful insights on how a preemptive support strategy and a short feedback loop works.
This retailer used our core engine XAP to provide access to its catalog, inventory data, and tax to achieve a zero-downtime holiday season for the third year in a row. As a result, this company delivered a fantastic customer experience with a page load time of 3.6 seconds on average, reaching 3.88 at its highest peak of holiday traffic, generating a 100 percent increase over 2016 holiday sales.
It’s notable to mention that this retailer did not experience any system performance issues.
Identifying and Mitigating Key Risks
Rather than reacting after a failure occurred – prevented failure in the first place.
- Common Causes: Most failures are the result of misconfiguration or capacity planning guesswork.
- Planning: Proactive tuning with continuous system monitoring produces predictable improvements at scale, eliminating risks from incorrect provisioning.
- Knowledge & Experience: eCommerce applications are complex and built from many subsystems. In many cases, an eCommerce organization does not have the expert skill-set in each of the subsystems. Having an expert in the room helps to bridge this gap and builds the capabilities of business operations.
- Fast Feedback: When product-related issues are identified, we were able to provide the fastest path to protect the business and address concerns in a timely fashion.
Using GigaSpaces Solutions to Buffer Peak Load Access to Shared Data Resources
- Typical eCommerce systems have shared data resources for managing inventory, orders, and catalog information.
- Putting the shared data resources in-memory provides faster and more efficient (parallel) access to this shared data.
- Data is mirrored back into the database in batches. In this way, peak load transactions are buffered so that database traffic does not crash the database back-end.
- The In-Memory computing grid acts as a system of record. Failure in the underlying database can be saved without affecting the online users while the database is restored to a working state.
- Using a combination of In-Memory & SSD allows very large In-Memory data sets to be stored at a reasonable cost, while still ensuring fast recovery during failure.
Self-Healing Systems recover from a failure in real time
- Failures are inevitable: Keeping a backup copy in-memory enables zero-downtime systems to service user traffic without interruption, even if something does go wrong.
- Systems provisioned for failure handle failure by design.
- Automatic failover and provisioning eliminate the need to overprovision (costly) resources in case of failure. Traditionally, it’s common for retailers to provision resources for holiday season that is 5 times the capacity of non-holiday traffic infrastructure.
Peak load performance often tends to stretch any system behavior in areas that are least expected and thus are often hard to handle. Quite often, peak loads lead to unexpected downtime.
There are many cases in which this sort of peak load performance is known in advance, as is the case with Black Friday and Cyber Monday. Still, many eCommerce sites continue to experience downtime or slowness during such events that lead to huge loss of revenue and reputation.
For the past few years we, together with our customers, have taken a preemptive approach by putting an engineer on-site to escort the customer team during the event itself. This resulted in huge success, leading to 100% uptime. We learn so much from the experience; the customer learned even better how to operate our product and what to look for to ensure that the system is running properly. We learned much about how the customer is using our product and was able to shorten the feedback loop between the customer and our product and engineering team.
Plan ahead to break from Black Friday/Cyber Monday tradition and be free of major eCommerce website crashes or slowdowns in 2018.
Published at DZone with permission of Dana Meschiany , DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.