Black Friday checklist 2026: How to prepare your commerce platform for the holiday rush

The high stakes of Black Friday and Cyber Monday

Every year, Black Friday and Cyber Monday (BFCM) mark the most intense pressure test for brands and retailers. These days are synonymous with staggering spikes in online traffic, fierce competition for consumer attention and enormous revenue potential. For many brands, the holiday shopping season can represent as much as 20% of annual retail spending.

While peak season isn’t limited to BFCM, with events like Back-to-School and Valentine’s Day driving similar surges, the fact is that the holiday season is of strategic importance for the supermajority of retailers today.

The BFCM season has evolved throughout the years. Once confined to a two-day weekend of doorbusters and flash sales, it has now expanded, with brands running six-week campaigns blending early urgency driven by product drops and social media surges, core-weekend deals and post-event bundles.

This year, AI shopping is expected to have an immense impact on product discovery, comparison, and ultimately, conversion. Data from leading retailers show that AI site traffic generally accounts for 5% of referrals, with some cases closer to 10%. The same survey revealed that shoppers referred by AI tools generated 53% more revenue per visit than other shoppers.

In the US, nearly 132 million consumers have bought a retail product with AI’s help. And retail giants and brands, from Best Buy to Kate Spade, are betting heavily on AI-driven sales. This is where the commercetools AI Hub comes in, bringing AI-powered shopping tools, resources, and insights together in one place to help brands and retailers navigate the shift to AI-driven commerce.

This year, a growing share of that AI activity is shifting from recommendations to action, with shopping agents and AI assistants browsing, comparing and completing purchases on shoppers’ behalf. This behavior changes more than traffic volume. Agents can bypass the storefront and call commerce APIs directly, generate multiple requests for a single purchase, and retry automatically when they encounter delays. At the same time, bot protections designed to block unwanted automated traffic can also block legitimate shopping agents.

As shopping becomes more automated, peak-season readiness needs to extend beyond traffic capacity and storefront performance. Brands must also ensure that promotions, carts, checkout flows and inventory logic can handle the increased volume and different behaviors that AI-driven commerce introduces. Getting these fundamentals right before the seasonal freeze can help prevent avoidable friction when demand is at its highest.

Best practices for your functional readiness

The decisions made in October around promotions, carts, checkout logic and inventory can have just as much impact on the customer experience during Black Friday.

• Audit your promotions before the freeze: Peak is when campaign volume spikes, and teams often load in far more active promotions than they run at any other point in the year. Reviewing what’s live, what’s expired and what’s overlapping is quick to do in advance and painful to untangle mid-campaign.
• Tune your cart settings for peak volume: Create carts when a shopper adds their first item rather than on arrival, and shorten retention for peak-period and anonymous carts. Both keep your data footprint proportionate to a period that generates far more carts than orders.
• Review any custom logic in the cart and checkout path: If you’ve extended those flows, check timeout settings and make sure each step degrades gracefully rather than blocking the shopper. Anything on the critical path deserves a second look before a freeze.
• Validate stock at decision points: Confirm availability at add-to-cart and checkout, rather than relying on what was shown at browse time. On a normal day, the difference is academic. During a sell-out, it’s the difference between a clean stockout and orders you can’t fulfill.

Best practices for your technical readiness

Once your functional setup is ready, focus on the application and integration layer that will carry the additional demand.

Transparency is key. If you’re already a customer, work closely with your Customer Success Manager (CSM) to share:

• Planned load testing schedules.
• Anticipated traffic volumes.
• Major campaigns that could trigger sudden bursts.
• Expected AI-agent or automated traffic, where known.

The earlier commercetools knows your expectations, the better we can align resources.

AI agents introduce a different traffic pattern from traditional storefront traffic. Before peak, make sure your automated traffic strategy is explicit:

• Give agent traffic its own credentials rather than sharing the storefront’s. This lets you see agent activity separately, control it independently and switch it off without touching your website if something goes wrong.
• Align with agent partners on peak behavior. Tell them your expected volumes, agree on how they’ll back off if you’re under pressure, and test together before the freeze.
• Decide which automated traffic is welcome. Controls designed to stop unwanted automated traffic can also prevent legitimate shopping agents from reaching the commerce APIs they need. Decide which automated traffic is welcome — and make sure your controls can distinguish it — before peak week.
• Check the limits on your own AI dependencies. External services, recommendation engines and model providers enforce their own rate limits and quotas. Verify your tier limits and fallback options with key partners in advance so that an agent experience doesn’t stall due to something entirely outside your platform.

As a general guideline, it’s crucial to prepare your product data for AI discovery. According to , merchants increasingly see agentic commerce as a real sales channel, but many still feel unprepared to connect to AI platforms and agent networks. Well-structured, complete and consistent product data is an important foundation for making products understandable and discoverable by AI agents.

commercetools enables merchants to drive product discovery and selling across GenAI channels withthe AI Hub. In addition to AI Hub,theSmart Data Modeler (included in the AI Hub) helps businesses structure and prepare product data for AI-driven commerce.

Peak season means more requests and, inevitably, more edge cases. Protect your performance by:

• Adding a unique X-Correlation-Id to every request for faster tracing and debugging, especially during high-volume periods.
• Configuring your application to capture and alert internal teams to specific exception codes and details returned by the commercetools platform.
• Implementing exponential backoff for retries, especially on concurrent modifications.
• Designing smart retry mechanisms for transient errors (like network hiccups). A general guideline is a ~2-second timeout for GET requests and ~5-8 seconds for POST requests.
• Logging all errors centrally and reviewing logs frequently to identify patterns, so you can identify and fix underlying technical implementation issues in your application.

💡 Check our best practices for error handling through timeout and retries.

Observability gives you visibility into what’s happening in real time. Best practices include:

• Centralized logging to capture and consolidate error data.
• Implement Application Performance Monitoring (APM) tools to track latency, throughput and bottlenecks. commercetools offers open telemetry support via SDKs for observability, providing insights into how well your application performs.
• Additionally, commercetools offers Platform Insights as an add-on feature that allows analyzing metrics and server-side logs collected from commercetools APIs.
• Alerting systems to flag anomalies before they impact customers.

Every API call counts during peak season. Optimize your usage by:

• Caching static or slow-changing resources to reduce redundant calls.
• Ensuring gzip compression on API requests to compress response times, which is a default feature when using commercetools SDKs (e.g., Java SDK Middlewares).
• Avoiding unnecessary queries or unbounded searches that stress APIs.

Use our official documentation to prepare:

• Performance tips cover query optimization and caching.
• Load testing guidelines help simulate realistic peak traffic.

💡 Premium Support and Expert Services provide hands-on guidance and testing validation.

Advanced guidance: Managing concurrency and throughput

For enterprise-scale retailers, concurrency and throughput management can be the difference between smooth scaling and overwhelmed systems. This is how commercetools Spherehandles parallel requests:

• Circuit breaker protection: All our endpoints are protected by sophisticated circuit breaker logic. This complex algorithm acts independently across multiple layers to maintain platform stability under heavy loads.
• Concurrent connections: We generally advise that no SINGLE syncing application should maintain more than 20 concurrent connections to the platform.
• Testing for higher throughput: If your business objectives necessitate higher throughput, progressively ramp up your concurrent connections during testing until you observe significant 5xx errors. Should you encounter 5xx errors, a robust retry mechanism with exponential backoff and error handling is critical.
• Ramp-up strategy: For highly concurrent processes and load tests, always ramp up over the first 10-15 minutes. This allows the commercetools APIs to scale effectively to meet your increased demand.
• Staggering multiple projects: If you operate multiple commercetools projects that require separate high-concurrency sync updates, staggering their start times can help distribute the load and ensure optimal performance for all.

💡 Need additional support?

If your business objectives for throughput are still not met after implementing these best practices and testing thoroughly, please contact us!

Our team will work closely with you to ensure top-notch performance.

Get peak-ready: Protect performance and unlock AI-driven commerce

Black Friday and Cyber Monday readiness is about more than surviving a traffic spike. As AI-driven shopping reshapes how customers discover and buy products, retailers need to ensure their commerce operations are ready for both traditional shoppers and AI agents.

By validating the fundamentals, optimizing API performance and testing realistic peak scenarios well before the freeze, teams can reduce risk, protect the customer experience and make the most of the season’s revenue potential.

Ready to see how commercetools can support your next high-traffic event? Contact our sales team or start our 60-day free trial to learn how your business can scale during BFCM and other peak sales events.

FAQs

Start with functional readiness: Audit your promotions before the freeze, tune cart settings for peak volume, review any custom logic in the cart and checkout path and validate stock at add-to-cart and checkout. Then, cover technical readiness: Share traffic expectations with your platform vendor, prepare for AI-driven traffic, build in error handling and optimize your API interactions.

Give agent traffic its own credentials, align with agent partners on expected volumes and how they back off under pressure, decide which automated traffic is welcome and make sure your controls can tell it apart and check the rate limits of your own AI dependencies.

Add a unique X-Correlation-Id to every request, alert your internal teams to specific exception codes, use exponential backoff for retries (especially on concurrent modifications) and design smart retries for transient errors, with a timeout of about 2 seconds for GET requests and 5 to 8 seconds for POST requests.

Peak is when campaign volume spikes and teams often load far more active promotions than at any other time of year. Reviewing what's live, what's expired and what overlaps is quick to do in advance and painful to untangle mid-campaign.