Cookies used to measure how people use a website, including visit counts, traffic sources, and popular pages. They help organisations understand site behaviour and improve service delivery. Unlike essential cookies, performance cookies are generally non-essential and should be disclosed clearly so users can make an informed choice.
Expanded Definition
Performance cookies are non-essential browser cookies that collect aggregated or pseudonymous usage data so organisations can understand traffic patterns, page popularity, referral sources, and navigation behaviour. They sit apart from essential cookies because they are not required to deliver the core service, and their deployment usually depends on informed consent or a clearly documented lawful basis, depending on jurisdiction and implementation. Guidance varies across vendors and privacy regulators on the exact boundary between performance and analytics cookies, especially where session replay, A/B testing, or cross-page measurement is involved. For governance purposes, the key distinction is not the marketing label but whether the cookie is strictly necessary for the service requested by the user. The NIST Cybersecurity Framework 2.0 is useful here because it reinforces the need for accountable governance, transparent control decisions, and risk-informed measurement practices. The most common misapplication is treating performance cookies as automatically exempt, which occurs when teams copy a generic banner configuration without reviewing the actual data collected or how it is linked.
Examples and Use Cases
Implementing performance cookies rigorously often introduces a tension between measurement quality and user consent friction, requiring organisations to weigh operational insight against a smaller consented dataset.
- Tracking which pages on a documentation portal receive the most visits so content teams can improve navigation and reduce support tickets.
- Measuring referral sources for a public service website to determine whether campaigns are driving users to the right landing pages.
- Comparing load paths and bounce patterns across devices to identify pages that perform poorly on mobile connections.
- Using consented analytics to understand checkout drop-off points without collecting data that is unnecessary for the stated purpose.
- Reviewing cookie categories alongside guidance in the Ultimate Guide to NHIs when website telemetry is integrated into broader identity and access governance.
Teams often align these controls with privacy engineering patterns described in the NIST Cybersecurity Framework 2.0, especially where telemetry is used to support service improvement and resilience reporting.
Why It Matters in NHI Security
Performance cookies may seem far removed from Non-Human Identity security, but they often touch the same governance surface as tags, scripts, consent tooling, and third-party analytics integrations. Poorly governed measurement tools can create shadow data flows, weaken transparency, and introduce unauthorised access paths through tags or embedded scripts. That matters because identity security is not only about API keys and service accounts; it is also about controlling which machine-originated components are allowed to collect, transmit, and correlate user behaviour. NHIMG research shows that Ultimate Guide to NHIs reports only 5.7% of organisations have full visibility into their service accounts, underscoring how easily unmanaged machine activity can go unnoticed. In practice, the same discipline used for secrets, privilege, and telemetry review should apply to cookie-backed measurement systems, especially when vendors inject code into production pages. Organisations typically encounter the compliance and security cost only after a privacy complaint, a third-party review, or an incident response review, at which point performance cookies become operationally unavoidable to address.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.RM-01 | Performance cookie governance is a risk-management decision about non-essential data collection. |
| NIST AI RMF | Telemetry and analytics should be governed through measurable, accountable data practices. |
Document cookie telemetry risks and approve collection only where business value outweighs privacy impact.
