Why you should run A/B tests during Black Friday & Christmas

Traffic surges, conversion rates climb, and revenue charts start looking like they’ve been chugging energy drinks. For a CRO specialist, it’s the perfect storm for big wins. Some of my most successful experiments have come during this period, delivering +15% to +20% lifts in Black Friday revenue.

But here’s the twist – a surprising number of e‑commerce teams still shy away from testing during the biggest sales weekend of the year. Why? They’re worried an A/B test will somehow break the site or slow things down when it matters most.

Let’s clear something up right away – A/B testing isn’t what crashes your site! If your infrastructure is solid, running experiments won’t be the tipping point for the website to go down. In fact, A/B testing platforms are designed to be lightweight and robust, even under heavy traffic. The real risks usually come from untested code deployments or major infrastructure changes – not from well-implemented experiments.

So while the fear is understandable, it shouldn’t stop you from running experiments when they matter most. In fact, I’d argue that the holiday rush is exactly when you should be testing. Here are my three strongest arguments:

1. You get more data faster!

Let’s start with the obvious: traffic. During Black Friday and Christmas, your site is flooded with visitors. What does that mean for your experiments? You reach statistical significance faster. A test that would normally take weeks to reach a conclusion can now be wrapped up in days – or even hours. This means you can iterate quickly, learn faster, and make more confident decisions while the stakes (and the rewards) are at their highest.

If you’ve ever been frustrated by slow-moving tests in Q2, you’ll love the velocity you get in Q4!

2. Learning what works – when it matters most

User behavior during the holidays is different. People are more motivated, more price-sensitive, and more likely to make impulsive purchases. If you only test in the “off-season,” you’re optimizing for a completely different mindset.

Running A/B tests during Black Friday and Christmas means you’re learning what works when it really matters. You’re optimizing for the most competitive, high-pressure environment your site will ever face.

It’s important to note that the insights you gain from Black Friday and Christmas tests are often unique to these high-intent, deal-driven periods. What works during the holiday rush – when shoppers are motivated by urgency, scarcity, and discounts – may not translate to your everyday site experience. Instead of viewing these results as universally applicable, treat them as a playbook of best practices specifically for future Black Friday, Christmas, and other major sales events. These learnings are incredibly valuable for optimizing your next big campaign, but they shouldn’t automatically be rolled out across the rest of the year. Focus on building a bank of deal-related insights that you can revisit and refine every holiday season.

3. The impact of winning (or losing) is magnified

Here’s the closing argument: Every percentage point of uplift is worth so much more during the holidays.

A 2% increase in conversion rate in July? Nice.

A 2% increase in conversion rate on Black Friday? That covers the CRO team costs for years!

The stakes are higher, the rewards are bigger, and the cost of getting it wrong is steeper. And I get it. The fear of losing is real. Loss aversion is one of the strongest principles in behavioural economics. So the key here is to build a rigid process for not mixing in gut-feeling-ideas into your Black Friday launch schedule.

To illustrate this, let’s dig into my test example that was introduced above. The highest-impact test I’ve ever run was also the simplest from a technical perspective – a single CSS tweak plus a JS calculation. That variation drove a +20% increase in mobile revenue and a +15% lift on desktop. The ROI for that weekend was off the charts.

The chain reaction? The online sales department not only succeeded in their targets for the Black Friday campaign, but they also became some of the strongest advocates for CRO and experimentation moving forward. My test variation didn’t just become a new best practice for Black Friday – it changed the way the organization approached optimization year-round. And even the CEO visited my LinkedIn profile. What July test has ever rendered that outcome?

My recommendations for where to start with Black Friday testing

Now, before you start imagining complex redesigns or high-stakes experiments, let’s get practical. The beauty of Black Friday and Christmas isn’t just the surge in traffic – it’s that even the smallest tweaks can have an outsized impact. You don’t need to gamble with a new deal engine or roll out risky changes to see meaningful results. Start small and get your easy wins to calm the nerves of colleagues who didn’t want to run experiments in the first place!

This is the perfect time to focus on those “quick win” experiments that are easy to implement, low risk, and rooted in solid behavioral economics. These are the kinds of changes that can be set up and QA’d easily, but still deliver statistically significant results in a matter of hours. As the period is based on discounts, I suggest that you dig into behavioural economics to see how you can amplify the discount communication to become a bargain!

Here are a few behavioural economics areas I recommend starting with:

• Scarcity: Label products that are running out of stock.
• Social Proof: The number of users currently browsing a specific item.
• Loss-aversion: Exit-intent pop-ups to combat basket drop-off rate.
• Price psychology: Is a “-25%” or “-50€” discount more convincing for your customers?

Most of these principles can be implemented with front-end changes or messaging tweaks that carry minimal risk of introducing bugs. The key is to do your homework. Ensure you thoroughly understand how your site’s deal engine works and verify the rounding rules for discounted prices. Once you’ve mapped out these details, setting up and launching these types of A/B tests becomes a smooth process. And if you want to take an even easier route, then choose the Multi-armed bandit user allocation! This ensures that any low-performing variation has a gradual exclusion for new visitors, while increasing the traffic to the profitable variation.

And remember:

Not testing is a risk, too.

If you’re operating on gut feeling alone, you’re almost certainly leaving money on the table – and you’ll never know just how much you missed out on.