2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
Use a transparent acquisition baseline for staffing, BPO, facilities, contact-center, back-office, and managed support services while keeping employer demand separate from applicant and service-user activity.
DEFINITION
What is this about?
For SGT-21, the SellersGPT 2026 model reports USD 5.17 advertising CPC, USD 65 lead-action CPA, a 28.2% modeled lead-to-MQL rate, and USD 230 modeled cost per MQL after rounding. The planning band is USD 175 to USD 285, with Medium confidence. These country-neutral values are planning references, not observed universal averages, placement fees, contract prices, or a SellersGPT Qualified Lead billing price.
KEY TAKEAWAYS
- The canonical 2026 CPC is USD 5.17 per paid click, 1.4% above the USD 5.10 portfolio reference.
- The modeled lead-action CPA is USD 65 per captured action, not per qualified buying organization.
- USD 65 / 0.282 equals USD 230.50 and rounds to USD 230 per modeled MQL.
- Buyer identity, service scope, workforce or operating scale, location coverage, and procurement role should govern qualification.
- The USD 175 to USD 285 band is a scenario range, not a confidence interval, staffing markup, or commercial quote.
Who this report is for
This report is for B2B teams selling recurring or project-based support capacity to organizations. It is not a labor-market forecast, wage benchmark, placement-fee schedule, or guide for job applicants.
Contents
1 Benchmark snapshot 2 What the data says 3 What the benchmark measures 4 Industry demand context 5 CPC behavior 6 Buyer vs Applicant vs Service-User Filter 7 Illustrative planning scenario 8 How to compare your data 9 Limits 10 FAQ, methodology, related knowledge, and implementation notes
Benchmark snapshot
Metric and unit 2026 value Evidence label Denominator Interpretation Advertising CPC, USD per paid click USD 5.17 pricing_system_value Paid clicks Modeled traffic-cost reference Lead-action CPA, USD per captured action USD 65 sellersgpt_modeled Captured lead actions Upstream action cost Implied click-to-action rate, % of clicks 7.95% derived_calculation Paid clicks CPC / CPA diagnostic Modeled lead-to-MQL rate, % of actions 28.2% sellersgpt_modeled Captured actions Fit-plus-engagement assumption Modeled cost per MQL, USD per MQL USD 230 sellersgpt_modeled Modeled MQLs Rounded planning estimate Planning band, USD per MQL USD 175 to USD 285 sellersgpt_modeled Modeled MQLs Scenario range Confidence Medium sellersgpt_modeled Model mapping Composite category with mixed intent The CPC index is 101.4 when the 30-industry USD 5.10 portfolio mean equals 100. The difference is small and does not prove that outsourcing demand is more valuable, urgent, or qualified than the portfolio average.
What the data says
Google defines average CPC as click cost divided by paid clicks. Google Ads Help, "Average cost-per-click (Avg. CPC): Definition" Google defines average CPA as conversion cost divided by configured conversions. Google Ads Help, "Average CPA: Definition" The advertising platform does not decide whether that conversion represents a procurement buyer. The row is internally reproducible. USD 5.17 / USD 65 = 7.95% is the implied click-to-action rate. USD 65 / 0.282 = USD 230.50, rounded to USD 230. The implied rate is arithmetic from the displayed point estimates, not an independently observed outsourcing conversion series. The WordStream/LocaliQ 2026 search dataset provides broad auction context, including business-service and employment-adjacent traffic, but it is not a probability sample of global BPO procurement. WordStream by LocaliQ, "Google Ads Benchmarks 2026: Competitive Data & Insights for Every Industry" It is an input and sensitivity reference, not the public label for this modeled row.
What this benchmark measures
The report follows three units: paid clicks, captured lead actions, and modeled MQLs. It does not measure an executed statement of work, open requisition, accepted staffing order, approved vendor status, sales-accepted lead, placement, or customer. An actual SellersGPT Qualified Lead is a separate product-defined lifecycle state. Its exact unit price must resolve from the applicable pricing-system record. None of the benchmark values on this page is presented as that billing price.
Industry demand context
Administrative and support services are not one buying market. The U.S. Census classification for NAICS 561 includes office administration, facilities support, employment services, business support, travel arrangement, investigation and security, services to buildings, and other support activities. U.S. Census Bureau, "NAICS 561 - Administrative and Support Services" SGT-21 is a broader SellersGPT commercial group, not an official NAICS sector. The U.S. Census Bureau NAICS program is the governing public classification reference used for the crosswalk; it supplies industry structure, not advertising or MQL prices. The Bureau of Labor Statistics industry page uses establishment and household surveys to describe administrative and support services. U.S. Bureau of Labor Statistics, "Administrative and Support Services: NAICS 561" Its employment measures are useful market context, but employment is not digital buyer intent. A change in temporary-help employment can reflect labor supply, client demand, substitution, or macroeconomic conditions; it cannot validate an MQL cost. Occupational data also show why a single persona is inadequate. BLS publishes industry-specific employment structures for office administration, facilities support, employment services, business support, travel arrangement, security, and building services. U.S. Bureau of Labor Statistics, "National Industry-Specific Occupational Employment and Wage Estimates" The person searching may be a procurement leader, HR executive, operations manager, facility manager, candidate, employee, or consumer. Campaign records need an intent class before economics are compared.
Why CPC behaves this way
High-intent terms such as outsourced customer operations, employer-of-record support, multi-site facilities contract, or specialized recruiting can attract agencies, software firms, job platforms, and service providers. Broad phrases such as staffing, cleaning, payroll help, call center, or administrative jobs can attract a much larger nonbuyer audience. Geographic modifiers often matter because delivery, labor law, language, and site coverage are local. Brand demand and job demand can make raw CPC look efficient while depressing commercial yield. Conversely, a narrow enterprise query may have a higher CPC but better buyer fit. Split campaigns and conversion actions by buyer route, applicant route, current-worker support, and consumer service. Do not optimize the B2B campaign toward the cheapest form completion.
Why CPA and MQL diverge
Common false positives include job applications, resumes, shift questions, payroll or timesheet support, current-employee complaints, candidate-status enquiries, supplier pitches, one-person consumer requests, and locations outside service coverage. A valid B2B action should identify an organization, a business need, a plausible service category, and meaningful engagement. The model applies a 28.2% lead-to-MQL rate. Public First Page Sage data supplies industry and channel comparisons, but its agency-client cohort and proprietary MQL definitions cannot become a universal support-services rule. First Page Sage, "Lead-to-MQL Conversion Rate Benchmarks by Industry & Channel" Medium confidence reflects both the adjacent proxy and the breadth of this category.
Buyer vs Applicant vs Service-User Filter
Filter Buyer demand Applicant or worker Service user or consumer Vendor or other Identity Organization and work role verified Candidate, contractor, or employee Individual receiving or seeking service Supplier, partner, media, or unclear Primary intent Source, replace, expand, or evaluate service Find work or resolve employment issue Request delivery, help, or local service Sell, partner, research, or support Evidence Scope, location, scale, timing, or procurement step Resume, availability, shift, pay, status Address, appointment, personal problem Capability pitch or nonbuying question Routing B2B qualification queue Applicant/worker system Service operations or consumer funnel Partner, support, suppress, or research MQL treatment Score fit and engagement Exclude from B2B denominator Exclude unless campaign is explicitly consumer Exclude or classify separately First apply the intent filter. Then test account fit, service scope, supported geography, minimum scale, timing, and meaningful engagement. Missing data should remain Unknown. A job seeker with a complete form is not a low-scoring buyer; the record belongs to a different funnel.
Illustrative planning scenario
Assume a fictional mature cohort captures 100 valid lead actions at the modeled USD 65 CPA. Attributable media cost = 100 x USD 65 = USD 6,500 Modeled MQLs = 100 x 28.2% = 28.2 Modeled cost per MQL = USD 6,500 / 28.2 = USD 230.50 The published point estimate rounds to USD 230. At the USD 175 planning-band floor, the same USD 6,500 would correspond to about 37.1 MQLs. At the USD 285 ceiling, it would correspond to about 22.8. These are sensitivity scenarios, not predicted whole-lead counts. Suppose the 100 actions actually contain 34 procurement enquiries, 41 applicants, 12 worker-support requests, 7 vendors, and 6 Unknowns. The benchmark must not be applied to all 100 as though each entered the B2B qualification pool. Preserve the original action denominator, report the intent exclusions, and calculate the buyer-cohort rate separately. No outcome, customer, contract value, or billing price is implied.
How to compare your data
Use one mature cohort with the same channel, geography, objective, and attribution window. Reconcile spend to paid clicks, name every conversion action, remove test/spam/duplicate records, and tag intent before qualification. Report CPC, action CPA, buyer-intent rate, buyer-to-MQL rate, and total cost per MQL separately. Compare staffing, BPO, facilities, and back-office programs as distinct subsegments where volume permits. Also separate branded and nonbranded search, employer and applicant landing pages, and enterprise and local-service forms. If MQL reporting lags the action, freeze the cohort only after the agreed maturation window.
What this does not prove
The benchmark does not prove market size, labor availability, wage levels, client retention, fill rate, time-to-fill, gross margin, placement economics, contract value, close rate, or ROI. Country, labor regulation, delivery model, onshore/offshore mix, role scarcity, service complexity, buyer size, and brand demand can materially change results. The USD 175 to USD 285 band is a governed planning range, not a statistical confidence interval. Medium confidence describes source mapping and category breadth, not the probability that an individual campaign will land inside the band.
FAQ
Is a completed job application a lead action? It can be an applicant conversion in a recruiting funnel. It is not a B2B buyer action or MQL unless the person separately demonstrates an authorized organizational buying need. Should a staffing firm optimize all forms together? No. Buyer enquiries, applicants, current-worker support, and vendor forms have different business values and should use distinct actions, routes, and reports. Why is confidence only Medium? The category spans several business models, and public data does not isolate one global, B2B-only outsourcing funnel with a common qualification definition. Is USD 230 a placement fee or contract acquisition cost? No. It is a modeled marketing cost per MQL. Placement fees, delivery costs, and customer acquisition require downstream cohort data. Can the planning band be quoted to a client? It may be disclosed as a SellersGPT modeled planning range with its scope and limitations. It must not be presented as a guaranteed result, market tariff, or product billing price.
Sources and methodology
1 Google Ads Help, "Average cost-per-click (Avg. CPC): Definition" 2 Google Ads Help, "Average CPA: Definition" 3 WordStream by LocaliQ, "Google Ads Benchmarks 2026: Competitive Data & Insights for Every Industry" 4 First Page Sage, "Lead-to-MQL Conversion Rate Benchmarks by Industry & Channel" 5 U.S. Census Bureau, "North American Industry Classification System" 6 U.S. Census Bureau, "NAICS 561 - Administrative and Support Services" 7 U.S. Bureau of Labor Statistics, "Administrative and Support Services: NAICS 561" 8 U.S. Bureau of Labor Statistics, "National Industry-Specific Occupational Employment and Wage Estimates" How this was modeled SellersGPT normalized public search-cost and lead-to-MQL proxy families to SGT-21, preserved the pricing-system CPC at USD 5.17, applied the governed USD 65 lead-action CPA and 28.2% MQL rate, calculated USD 230.50, and published USD 230 with a USD 175 to USD 285 scenario band. Public sources supply definitions, external context, and proxy evidence; they do not independently report the SellersGPT result.
Sources and Methodology
- support.google.com: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- support.google.com: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- wordstream.com: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- census.gov: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- census.gov: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- bls.gov: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- bls.gov: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
- firstpagesage.com: 2026 B2B CPC, Lead-Action CPA, and MQL Benchmarks for Administrative, Support & Outsourcing Services
Methodology
This article separates cited official or first-party facts from SellersGPT calculations, examples, frameworks, and recommendations. Source links and scope are retained from the publication pack.
Limitations
This material supports planning and decision-making. It is not legal, financial, regulatory, or performance advice, and it does not guarantee leads, meetings, customers, revenue, or return on investment.