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Black Friday under Pressure: How the best retail teams get it right

Black Friday is a stress test for every retail app. See how leading teams use Embrace and OpenTelemetry to connect technical performance to real user experience—and keep conversions high when it matters most.

For engineering teams, Black Friday is a stress test. One slow API call or checkout timeout, and thousands of carts can vanish.

The difference between teams who panic and those who stay calm comes down to visibility — not just into systems, but into how users actually experience them.

That’s the essence of user-focused observability: connecting technical performance to what really happens on a shopper’s screen.

How top retail teams prepare for the surge

Plan early. Test often.

A major retailer described Black Friday prep as a “live-fire exercise.” Weeks before sales begin, they run load tests, validate alert thresholds, and confirm that telemetry pipelines can handle the flood of events.

Their philosophy: remove uncertainty early.

  • Pre-release stability checks
  • Fine-tuned alerts to cut noise
  • Clear on-call ownership

The goal isn’t perfection — it’s confidence.

Watch experience signals, not just errors.

When traffic spikes, they track more than crash rates: checkout latency, login stalls, API bottlenecks, image delays.

If something drifts, they can see it before users feel it.

“Would we have seen this coming?” is their guiding question.

 

Collaboration is the real differentiator

That same team automated Slack updates to surface live error data every few hours. Product, QA, and engineering stay synced without dashboard refreshes.

Many modern orgs are taking that a step further by standardizing telemetry through OpenTelemetry — giving mobile engineers, backend SREs, and product managers a shared language for performance.

When everyone sees the same signals, decisions happen faster and focus stays where it belongs: on the user experience.

 

Real-time execution in the wild

GOAT — the global platform for sneakers and apparel — treats Black Friday as mission-critical.

During record traffic surges, their engineers monitored live performance and user sessions to troubleshoot issues as they happened, maintaining 99.99 percent crash-free sessions despite a 44 percent jump in traffic across iOS and Android.

Crashes aren’t the only risk.

Slow startups, stalled checkouts, and subtle UI delays quietly erode conversions without ever triggering an alert.

As shown in our iOS performance guide, even a one-second delay in a key flow can reduce conversions by measurable margins.

Connecting behavior to impact.

New monitoring approaches now make those hidden costs visible—showing not just when apps crash, but when they quietly slow down or frustrate users.

Features like User Journeys build on session-level data to show where users drop off and how small slowdowns ripple across engagement and revenue — all without extra instrumentation.

 

Continuous learning after the rush

After the sale ends, top teams don’t move on — they review.

Every alert, false positive, and near miss becomes input for the next cycle. Over time, that habit turns reaction into prevention.

“We used to ask, how do we fix this faster? Now we ask, how do we make sure this never happens again?”

That’s real maturity: using every insight to make next year’s peak calmer and more predictable.

 

The broader shift

Across retail and e-commerce, teams are closing the gap between system health and user impact.

Real-time visibility — once reactive — is now the groundwork for proactive, user-centric reliability.

More teams are standardizing on OpenTelemetry and looking for ways to connect technical data with real user behavior. The goal isn’t just faster fixes—it’s a clearer understanding of how performance impacts people using the app.

 

Build your own plan

Black Friday exposes every blind spot in your stack. Don’t wait for it to find yours.

Our guide, 13 Ways to Improve Your iOS Shopping Experience, outlines practical steps to strengthen app performance ahead of high-traffic events — from optimizing startup time to tracking session health in real time.

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