Which 2026 Travel Nursing SEO Statistics Are Safe to Use for Decisions?

45-60% is the range the source edition assigns to specialty-specific searches. Its examples distinguish broad travel nursing queries from narrower searches that combine a clinical specialty, assignment characteristic, or geography.

The supplied record does not disclose the query corpus, search engine, collection period, sampling rule, or denominator, so the value cannot be treated as a verified share of the overall travel nursing search market.

Decision use: compare the intent categories in your own Search Console data with active assignment inventory and candidate application paths. If specialty terms consistently lead candidates to relevant opportunities, maintain durable specialty information that helps them evaluate assignments, requirements, recruiter contacts, and market context.

A dedicated location page should exist only for a genuine location with useful location-specific information; a nominal service area by itself does not justify a page.

25-40% is a separate source range for candidates using 'near me' modifiers. The record describes this as local search behavior but does not supply a supporting source URL, sample definition, observation period, or evidence that the modifier independently signals immediate application intent.

Decision use: inspect the local queries and profile interactions your agency can actually measure, and keep Google Business Profile information accurate only for eligible, genuine physical locations.

Do not treat profile activity, a map presence, or a location page as an official or guaranteed ranking mechanism. Source status: the original attributions are 'Search engine data analysis' and 'Local search behavior reports'; the underlying citations are absent from this record and still require reconciliation.

15-30% is the reported CTR increase attached to recruiter-led content in the source edition. The record describes results in which a recruiter's identity or expertise is visible, but it does not provide an experiment design, baseline CTR, query group, ranking distribution, observation period, or statistical controls.

In 2026, that limits the decision value of the range: accurate recruiter pages and bylines can help candidates understand authorship and accountability, but this figure does not establish recruiter profiles as a Google ranking factor or prove a causal CTR effect.

Review recruiter-name impressions, clicks, assisted applications, and engagement in your own analytics, and keep biographies useful to candidates rather than publishing them solely to chase a benchmark. Source status: 'User engagement studies' is the only attribution provided, so external verification remains unresolved.

10-20% is the separate range assigned to traffic from branded recruiter searches. The source suggests that recruiter name recognition may coincide with name-based demand, but it does not identify the agencies, recruiters, channels, or attribution windows behind the figure.

Decision use: monitor recruiter-name queries and the landing pages they reach, then compare those observations with candidate actions that your reporting defines consistently. Make recruiter information crawlable when it genuinely helps candidates and connect it naturally to relevant assignment or editorial content.

Do not infer that search visibility itself creates recruiter authority. Source status: the original attribution is 'Internal agency traffic audits', with no supporting dataset included here.

The source edition reports organic conversion rates of 3-7% and describes paid social at 1-2%. It does not define whether a conversion is a completed application, inquiry, recruiter contact, account creation, or another event, and it does not document the channel-attribution model.

The same source text says a one-second load delay can decrease conversions by 5-10% in the mobile-first 2026 environment. Because no supporting source URL or experiment is supplied, that statement should remain a previously published claim requiring reconciliation rather than a universal performance rule.

Decision use: choose one candidate conversion event, define it consistently, segment it by device and acquisition source, and compare completion behavior before applying any benchmark to forecasting or target setting.

Mobile speed and application usability can still be audited as operational quality issues, but this record does not prove a guaranteed conversion lift. Source status: 'Industry conversion benchmarks' is the only attribution preserved in the underlying material.

30-50% lower Cost Per Lead (CPL) via SEO vs. PPC is another published source claim without a documented sample, spend definition, attribution model, lead qualification rule, or supporting source URL in this JSON.

For pricing context, see the travel nursing SEO cost guide. Do not translate this range into an ROI, revenue, placement, or application guarantee. Instead, calculate CPL from your own consistently defined qualified-candidate events, include the labor and vendor costs assigned to each channel, and compare like-for-like reporting over a 12-18 month period.

Source status: the original attribution is 'Marketing spend analysis', so the claim still requires source reconciliation before external presentation as verified evidence.

65-80% is the source edition's stated share of nurses searching on mobile devices. The record does not identify the device-report source, sample, observation period, geography, or definition of the search activity included.

Use the figure as a reason to inspect your own device mix, assignment-search behavior, resume-upload flow, and application completion by device, not as a prediction of your traffic. Candidates may research or apply away from a desktop, so mobile usability is a practical quality concern, but this statistic does not prove that a particular design change will increase traffic, applications, or placements.

Source status: the original attribution is 'Device usage statistics', and no supporting source URL appears in the supplied record.

40-55% is the separate range the source assigns to searchers interacting with AI Overviews. The record connects the observation to search behavior in 2026 but does not define an interaction, identify the tested query set, or explain how exposure was recorded.

Treat Google AI Overviews and other Google AI features as search surfaces to observe, not as a special markup program or a guaranteed inclusion channel. Structured data should be used only when it accurately represents page content and follows documented eligibility requirements; FAQ content can be useful to readers, but this page should not claim FAQ markup creates a Google FAQ rich result.

For measurement, record the exact citation or recommendation classification you can observe, the query context, and the page surfaced, then keep those observations separate from downstream candidate actions. Source status: 'Search engine evolution reports' is the original attribution and remains unreconciled in this file.

• Avg Organic Ctr: 2.5-4.5% for top 3 positions. The value is preserved from the source, but the record does not define query mix, device split, brand exclusions, result type, or observation period, so compare it only after aligning those definitions.
• Avg Time To Rank: 4-9 months for competitive keywords. Treat this as a reported timing observation, not a schedule or performance guarantee; keyword difficulty, site history, baseline authority, and measurement rules are not documented in the source file.
• Avg Cost Per Lead: $40-$85 for organic nursing leads. The record does not explain which labor, vendor, content, or platform costs are included, nor how a lead is qualified, so standardize your own CPL definition before comparison.
• Local Pack Importance: High: Drives 25% of total mobile clicks. Preserve the figure as published context, but the supplied record has no supporting click-study URL, denominator, query mix, or period that would allow independent verification.
• Mobile Search Share: 65-80% of total industry volume. Use this as a directional device-share reference until first-party analytics confirm the device mix for your own candidate journeys and application events.

• Separate specialty, location, licensing, pay, recruiter-name, and general assignment queries so broad traffic does not obscure the search intent that brings candidates to relevant job information.
• Write down the exact candidate event your organization calls a conversion, then apply that definition consistently across organic search, paid channels, recruiter referrals, and direct visits.
• Measure recruiter-profile discovery as observable user behavior, including impressions, clicks, and assisted candidate actions, rather than assuming authorship or profile activity is an undocumented ranking mechanism.
• Audit mobile assignment search, filters, resume upload, and application completion for friction, then evaluate changes against first-party analytics instead of treating external percentages as forecasts.
• For Google AI features, log the query context, surfaced page, and exact citation or recommendation classification you can observe; do not convert a recorded citation into an assumed candidate choice or hiring event.
• Before any benchmark enters executive or external reporting, reconcile its original dataset, period, denominator, metric definition, attribution rule, and supporting source so the evidence status is explicit.