Black Friday is just around the corner. Be prepared for the storm.

We know, the summer is almost here and the last thing you want to think about is November. Though, Black Friday is only six months away from now, which makes this the perfect time to start preparing your sites and applications for the expected cyber crowds.

To make sure you are fully prepared for November 24th, we serve you 3 Best Practices for making sure you are ready. Don't wait to the last minute, the earlier you discover flaws, the less you will have to spend in the long run.

Despite the somewhat ominous name of “Black Friday,” the United States’ unofficial shopping holiday is a joyous occasion for many — especially from the comfort of their own home.

Online shopping outpaced in-store shopping last year, and we don’t see that trend reversing anytime soon.

So, be well prepared for this year's storm, start load testing and optimize your site or applications (tisk, tisk) already now.

Now the three bits of wisdom to help you get the most from your load tests in crunch time leading up to Black Friday and Cyber Monday.

1. Plan the user scenario(s)

Over the 6+ years of being the world’s top cloud-based performance and load testing company, we’ve noticed that most people who ask us for help or advice often start with, “Hey, I need to test “X” amount of users, where do I start?”

The real place to start is in the user scenarios that you want to test. For the uninitiated, a user scenario — which can also be referred to as a “load script” — is a program that describes every action Virtual Users in a load test should perform.

For instance, if you’re running an e-commerce website where users are required to login using a username and password, that’s an important part of your flow, and you need to include those HTTP requests in your user scenario.

You’ll want to make these requests dynamic so the Virtual Users aren’t using the same username and password in every iteration. You can do that by using data stores. Learn more about that in this helpful article.

So, how should you do that?

Our most popular option is the Load Impact User Scenario Recorder, which is conveniently located on the Chrome Web Store.

After you install the extension, simply click the extension, select “Start Recording,” and then go through the user scenario you want to test on your website.

When you’re done, simply click the extension icon and select “Stop.” You’ll then be taken to another tab, where your Load Impact account will open and you’ll save the new scenario.

It’s super simple, and that’s why it’s been so popular for our users over the years. Check out this quick tutorial if you want to see it in action.

2. Determine the number of concurrent users in your load test

Now we can get to the fun part of determining how many concurrent Virtual Users to configure in your load test. We recommend starting with this formula:

Hourly Sessions x Average Session Duration (in seconds) / 3,600

Remember to look for data in peak periods and try estimate what your needed levels will be for your service to run through this years storm of online users. Looking at users for a specific time period, Google Analytics has made it super easy to find the data you need to fill this formula. Here it is in seven easy steps.

• Login to your Google Analytics account
• Click the “Reporting” tab across the top
• Select “Audience” in the sidebar menu
• Click “Overview”
• Set the time period you want to base your data on in the top-right corner
• Make sure "Hourly" is selected in the top-right of the line graph
• And the data you need is right in front of you!

If you want a little more insight into the reasoning behind this magic formula, check out this blog post, aptly named: Determining Concurrent Users in Your Load Tests.

3. Establish benchmarks with load testing

From the mathematical formula and insight from your analytics, you’ll easily figure out how many concurrent users your website serves now.

We recommend you isolate the key hours of operation and conversion and see how your website performs under “normal” traffic.

Then run a few tests with varying durations, and you’ll get the behind-the-scenes view of your website’s performance and establish important benchmarks. It’s also very likely that you’ll discover little optimizations to make immediately, too.

Now, when you run your larger load tests to understand your site’s scalability, you can easily correlate how much additional traffic effects load times.

For instance, maybe 10x the normal traffic level increases load times 5x, but 15 the normal traffic crashes your entire site.

When explaining the need of optimizations or more infrastructure, it’s always good to have this data and these comparisons available to help other stakeholders, perhaps marketing or the C-suite, understand the site’s overall performance.