Prompt and context
A B2B SaaS receives frequent customer questions asking whether the service is down. Support reports that about 30% of tickets are availability checks. Engineering proposes a public status page, while sales worries that publishing incidents could hurt renewals. Decide whether to launch it and explain the design, metrics, and safeguards.
What the interviewer is testing
The question tests whether you can turn “should we build a page?” into a product decision about customer trust, incident communication, and operational readiness. A strong answer segments audiences, sets disclosure boundaries, names the source of truth and owner, and defines measurable rollout gates instead of listing features.
Questions to clarify first
Ask four things: are customers mostly the general public, regulated enterprises, or a few large accounts; do contracts contain availability or notification commitments; how mature are monitoring, on-call, and incident command; and do customers need self-service confirmation, subscriptions, or root-cause explanations?
Also ask whether an internal or customer-specific status page already exists. Public, private, and audience-specific pages serve different audiences; one visibility model can either overexpose incidents or leave customers without enough information.
A 30-second answer structure
I would first validate whether customers need a trustworthy external signal, then choose public, private, or segmented visibility. If the 30% ticket share is real and the team can publish accurate updates consistently, I would start with 3–4 customer-facing components. The page would show actionable status and the next update time; an incident commander would publish, while security-sensitive details stay private. I would expand only after measuring time to first update, on-time update rate, duplicate tickets, and trust feedback. If the source of truth or ownership is unreliable, I would fix incident operations before going public.
Step-by-step analysis
Step 1: Define the user problem and audiences
Split the tickets into “confirm impact,” “know when to check again,” and “find a workaround.” Administrators may need component-level status, while everyday users only need to know whether login and core tasks work. Sales, support, and partners may need different subscriptions and history views. Segment by contract, region, product module, and incident impact before choosing visibility.
Step 2: Choose public, private, or segmented visibility
A public page fits when most customers need one shared source of truth. It can reduce duplicate questions and set transparent expectations, but it also exposes outages, maintenance windows, and component names. A private page is useful for employees or internal operations. An audience-specific page can give enterprise customers finer components and notifications, but adds permission, maintenance, and consistency costs. Explain the decision criteria instead of treating public visibility as the default.
Step 3: Design components, states, and information boundaries
Expose customer-understandable components such as Login, API, File export, and Console; do not publish internal service names. Define states such as operational, degraded performance, partial outage, major outage, and maintenance, with entry and exit rules. An incident can move through investigating, identified, monitoring, and resolved. Keep root causes, vulnerability details, and restricted-customer information in security and customer-communication workflows. A status page does not monitor systems by itself; it needs a verified monitoring or incident-command input.
Step 4: Connect publishing to incident response
After impact is detected, the incident commander confirms affected components, audience, and the first message, then publishes investigating. Once the cause is confirmed, update to identified; during recovery use monitoring; mark resolved only after service recovery. Set a cadence such as every 15 minutes and make support, sales, and the page use the same source of truth. Google SRE recommends preparing channels, audience lists, and roles in advance; a page cannot replace those responsibilities.
Step 5: Define trust, operating, and security metrics
Set time to first update, on-time update rate, correction rate, notification delivery, status-page self-service visits, duplicate availability tickets, and trust feedback. If the target is a 10% reduction in duplicate tickets, also watch false positives and false negatives so fewer tickets do not hide a worse experience. Security metrics include inappropriate disclosures, leaked internal names, and permission errors. Pause automatic publishing and require human approval when risk is high.
Step 6: Roll out in stages with Go/No-Go gates
Run an internal rehearsal, then open a page and subscriptions for 3–4 components to a small customer cohort. Go requires an explicit on-call and publishing owner, traceable status inputs, reliable updates during repeated drills, and shared language for support and sales. No-Go if first updates consistently miss the target, status inputs drift, or security review fails. After public launch, retain incident history and a postmortem link while removing internal details that no longer help customers.
High-quality sample answer
I would not start with “launch or do not launch.” I would first test whether customers lack a trusted external signal. When 30% of tickets ask about service status, self-service visibility may help, but publishing incorrect information would amplify the damage.
I would use a staged plan: rehearse internally, then expose Login, API, File export, and Console to a small customer cohort. Show status, impact, next update time, and subscription options; omit internal service names, vulnerability details, and unverified causes. The incident commander publishes through investigating, identified, monitoring, and resolved, with an update every 15 minutes. Support and sales use the same source of truth.
Success means tracking first-update latency, on-time updates, duplicate availability tickets, notification delivery, correction rate, and trust feedback. If duplicate tickets fall by the 10% test target and accuracy meets the gate, expand to all customers. If the data source, owner, or security boundary is weak, improve incident response first. The page serves trust and communication outcomes, not an isolated front-end project.
Common mistakes and improvements
- Saying “transparency always builds trust”: add audience segments, disclosure costs, and measurable gates.
- Treating a status page as monitoring: state that it needs monitoring or incident-command input.
- Publishing every incident automatically: define severity, human approval, and security exceptions.
- Showing only “normal/down”: add impact, next update time, and a customer action.
- Promising fewer tickets immediately: validate with cohorts and separate visits from issue resolution.
Follow-up questions and responses
Should all incidents be public?
No. Publish verified, useful facts about customer impact; keep security-sensitive, employee-only, or customer-specific details in the appropriate private channel. Tie visibility to impact and disclosure risk.
What if status data is inaccurate?
Stop automatic publication, assign an incident owner, and publish a correction with the next update time. Track false-positive and false-negative rates; accuracy is a gate for broader rollout.
How do you avoid revealing security details?
Use customer-facing component names and approved message templates. Separate availability communication from the security incident process, with security review before detailed disclosure.
How do you prove it reduces support load?
Compare similar incident cohorts before and after launch: duplicate availability tickets, time to first customer answer, self-service visits, subscription engagement, and trust feedback. A 10% reduction is a test target, not a guarantee.