Post-Launch Commerce Optimisation Checklist

Summary

The first 90 days after launch expose what discovery missed, what breaks under real load, and where conversion quietly bleeds out. This checklist structures a rigorous review across performance, conversion, and operations.

Nobody Owns the 90-Day Review

Most teams celebrate launch, then scatter. The agency moves to the next engagement. The client's internal team shifts to firefighting. Nobody owns the structured review that should happen at 30, 60, and 90 days.

Problems visible in production weren't visible in staging. Real traffic patterns expose architecture decisions that seemed fine in theory. Conversion issues compound daily, a 0.5% drop in checkout completion adds up fast. Operational friction burns out internal teams before anyone formally surfaces it.

This checklist is not a health check. It's a structured audit designed to surface what needs to change before optimisation debt accumulates.

How to Use This Checklist

Work through each section with the relevant stakeholder group. The merchandising team sees different problems than the dev team.

For each question:

Document the current state with evidence, not assumptions
Flag items that need deeper investigation
Assign owners to unresolved issues

Schedule reviews at day 30, 60, and 90. Some issues only emerge under sustained load or seasonal traffic changes.

Performance Under Real Load

Infrastructure and Response Times

What is the 95th percentile page load time for PDP and PLP pages under current traffic?
How does checkout performance degrade during peak traffic windows versus baseline?
Which third-party scripts contribute the most to render-blocking, and were any added post-launch without review?
Are CDN cache hit ratios where they should be, or is origin traffic higher than expected?
What's the actual error rate in production logs, not the monitoring dashboard summary?

Search and Navigation

How does site search response time scale with catalogue size changes since launch?
Are faceted navigation queries hitting performance thresholds on high-cardinality attributes?
What percentage of search queries return zero results, and has this changed since launch?

Integration Stress Points

Which integrations have thrown errors or timeouts in production that didn't surface in testing?
How are inventory sync delays manifesting in customer-facing availability issues?
What's the actual order-to-OMS latency distribution, and are outliers causing downstream problems?

Conversion Reality Check

Funnel Leakage

Where is the largest drop-off in the checkout funnel compared to pre-launch benchmarks or projections?
What's the cart abandonment rate by device type, and does mobile match expectations?
Are guest checkout completion rates significantly different from account checkout, and do you know why?

Pricing and Promotions

Have any promotion configurations caused margin erosion that wasn't caught during setup?
Are pricing rules behaving correctly across customer segments, or are edge cases leaking through?
What's the redemption rate on launch promotions, and does it indicate friction or awareness issues?

Product Discovery

Which high-margin products have lower-than-expected traffic from category pages?
Are product recommendations driving measurable conversion lift, or just clicks?
How does search-driven conversion compare to navigation-driven conversion?

Payment and Checkout Friction

What's the payment failure rate by method, and are declines higher than processor benchmarks?
Are address validation errors causing checkout abandonment in specific regions?
How many customers contact support during checkout, and about what?

Operational Strain

Order Management

What's the average time from order placement to fulfilment handoff, and where are the bottlenecks?
How many orders require manual intervention, and what are the top three reasons?
Are returns and exchanges flowing through the system as designed, or are workarounds emerging?

Content and Catalogue Operations

How long does it take to publish a new product from creation to live on site?
What content changes require developer involvement that were supposed to be self-service?
Are merchandising teams using the tools as designed, or have they reverted to spreadsheets?

Support Load

What are the top five customer support ticket categories, and do any trace back to platform issues?
Are support agents using the admin tools effectively, or do they need additional training or tooling?
How many issues escalate to the agency that should be resolved internally?

Technical Debt Accumulation

Code and Configuration Quality

What post-launch hotfixes were applied, and have they been properly reviewed and documented?
Are there configuration changes in production that don't exist in lower environments?
Which custom code paths have been flagged as problematic but not yet addressed?

Monitoring and Observability

Are alerting thresholds set appropriately based on actual production patterns, not pre-launch guesses?
What signals would indicate a problem before customers notice, and are those being monitored?
Is there a clear runbook for the most likely failure scenarios?

Dependency and Upgrade Exposure

Are any third-party dependencies approaching end-of-support or known vulnerability status?
What platform updates have been released since launch, and what's the plan to evaluate and apply them?

Stakeholder Alignment Check

Internal Team Confidence

Does the merchandising team feel they can execute their day-to-day without bottlenecks?
Does the operations team trust the data in the system for inventory and order accuracy?
Are there unresolved concerns from launch that haven't been formally addressed?

Vendor and Partner Relationships

Are integration partners responsive to issues, or is there friction in the support process?
Has the agency provided a clear transition or support handoff plan?

Turning Findings Into Decisions

A completed checklist only matters if it drives action.

Prioritise by daily cost, Conversion leaks and operational strain cost money now. Performance issues that don't affect users can wait.
Separate symptoms from root causes, High cart abandonment is a symptom. The root cause might be payment friction, shipping cost surprise, or slow checkout rendering.
Assign ownership and timelines, Every flagged issue needs an owner and a review date, or it becomes background noise.
Build the cadence into your engagement model, 30/60/90 reviews shouldn't be optional add-ons.

How DigitalStack Approaches This

DigitalStack structures post-launch reviews the same way it structures discovery, with connected data, not scattered documents.

Findings from a 90-day review feed back into the original objectives, requirements, and architecture decisions:

A conversion issue traces to the original requirement that shaped that flow
Stakeholder feedback on operational pain connects to the roles and responsibilities mapped during discovery
Recommendations link to the technical constraints documented upfront

The goal isn't generating a report. It's maintaining a continuous view of the engagement, from first discovery session through post-launch iteration, so that context doesn't evaporate when the team moves on.

Next Step

If your post-launch reviews rely on ad hoc check-ins and disconnected spreadsheets, the findings won't connect to the decisions that caused them.

[See how DigitalStack connects discovery to post-launch optimisation →]