eCommerce performance optimization services

Find what slows or breaks critical commerce journeys.

For teams facing poor Core Web Vitals, slow APIs, checkout instability or uncertain peak-load capacity. We measure before changing and verify against the same evidence.

Best forLive stores with user, application or infrastructure evidence to investigate.
Scores and incidents exist, but the causal path is unclear.A measured remediation plan and verified changes.
Review a performance problem →See how the engagement works
Engagement

Optimisation begins with a representative journey and baseline.

Typical first step
Select the commercial journey and the evidence used to judge change.
Inputs we need
RUM or analytics, monitoring, traces, code access, environments and incident history.
Outputs
Baseline, diagnosis, remediation backlog, verified changes and regression controls.
Working format
Focused audit, implementation or an embedded improvement stream.
Scope

Field, lab and load evidence answer different questions.

A single Lighthouse score cannot explain production behaviour. The measurement mix follows the failure mode.

01

Real-user monitoring

Shows user segments, devices and production distributions.

Needs representative traffic and consistent event definitions.
02

Lab and tracing

Makes rendering and request paths reproducible.

Useful for diagnosis, not a substitute for field outcomes.
03

Load and resilience

Tests capacity, saturation and degradation behaviour.

Requires realistic journeys, data and safe environments.
A measured remediation plan and verified changes.Discuss the service →
Change

Replace isolated scores with a traceable performance budget.

Current state
  • Teams optimise a homepage lab score while checkout remains slow.
  • Frontend, API and database symptoms are investigated separately.
  • Peak capacity is assumed from infrastructure size.
  • Improvements ship without a comparable measurement window.
Desired outcome
  • Budgets follow critical journeys and user segments.
  • Traces connect browser, API, database and dependencies.
  • Load tests reveal saturation and degradation paths.
  • Verification uses the agreed baseline method and window.
Process

Baseline → Diagnosis → Remediation → Verification

01Baseline02Diagnosis03Remediation04Verification
01

Baseline

Input

Representative journeys, segments and available telemetry.

Action

Define metrics and capture comparable evidence.

Output

Baseline and measurement plan.

02

Diagnosis

Input

Baseline, traces, profiles and dependency data.

Action

Locate bottlenecks and causal chains.

Output

Prioritised findings with evidence.

03

Remediation

Input

Approved findings, code and environments.

Action

Implement focused changes and quality gates.

Output

Tested changes and release plan.

04

Verification

Input

Released changes and the agreed measurement window.

Action

Compare like-for-like field, lab or load evidence.

Output

Verification report and regression budget.

Scope

Performance work across the full request path.

01

Storefront and Core Web Vitals

Rendering, assets, scripts and interaction diagnosis.

Boundary: Third-party vendor changes require their cooperation.
02

Backend and APIs

Latency, concurrency and dependency analysis.

Boundary: A rewrite is not assumed.
03

Database and cache

Query, index, cache and contention evidence.

Boundary: Data-model redesign is separately scoped.
04

Checkout reliability

Critical dependency and failure-path review.

Boundary: Payment-provider availability is external.
05

Peak-load readiness

Workload model, tests and bottleneck report.

Boundary: No capacity guarantee without agreed conditions.
06

Regression controls

Budgets, dashboards and release checks.

Boundary: Ongoing monitoring response is separate.
Sample output

Example verification record.

Illustrative structure only — not a client case or a performance claim.

Sample artifact

01JourneyUser segment and environment

02BaselineMetric, distribution and measurement window

03ChangeHypothesis and affected request path

04VerificationSame method, observed difference and caveats

Commercial model

Outputs

Included

  1. 01Journey baseline
  2. 02Core Web Vitals segment view
  3. 03Trace and dependency analysis
  4. 04Load-test scenario and results
  5. 05Remediation backlog
  6. 06Performance budgets and dashboards

Team shape

A performance specialist, the relevant frontend or backend engineer, and a quality specialist; the journey under test determines the mix.

Code and IP

The client owns the project-specific code and agreed deliverables after payment; third-party licenses and pre-existing tools keep their original terms.

Handoff and support

Handoff includes agreed repositories, documentation and knowledge transfer. Ongoing support is a separate scope unless included in the engagement.

Not included by default

Guaranteed Lighthouse scores, guaranteed conversion uplift, third-party vendor fixes and permanent incident response unless explicitly agreed.

Price factors

Journey count, telemetry quality, code and environment access, stack breadth, traffic model, test-data needs and remediation depth.

FAQ

Start with the journey, metric and environment.

Can you guarantee a Lighthouse score?

No. We optimise representative journeys and production experience; a lab score alone is not a business outcome.

Do you work on backend performance?

Yes. We can trace requests through APIs, databases, caches and external dependencies.

How is improvement verified?

The baseline defines the method, segment and measurement window; the same conditions are used after release where possible.

Can you prepare for peak traffic?

We can model and test critical paths, but any capacity statement is limited to the agreed workload and environment.

Start with the journey, metric and environment.

After contact we define the baseline and available evidence, then set the diagnostic boundary.

Review a performance issue →