Methodology
This page explains how we calculate the figures published on NearTalent — salary benchmarks, savings ranges, placement statistics and retention rates. We publish methodology because the numbers are only useful if you can understand what they include and what they leave out.
1. Salary benchmarks
1.1 Dataset
- Internal placements — 1,000+ contracts signed by NearTalent (operating as Selection Book) since 2016 across Mexico, Argentina, Colombia, Chile and Peru. Used as the primary signal for what clients actually pay.
- External benchmarks — quarterly refresh against Howdy, Deel salary guide, Terminal.io reports, Levels.fyi public data, CodersLink reports and direct quotes from EOR partner pricing pages.
- Candidate expectation data — anonymized salary expectations from our active candidate pool (~50,000 pre-screened professionals).
1.2 What's included in published ranges
All published ranges are all-in annual cost in USD, including:
- Gross salary paid to the worker
- Employer load (social security, statutory contributions): Mexico 28-38%, Argentina 20-26%, Colombia 22-30%, Chile 20-25%, Peru 18-24%
- EOR platform fee (typically $599-900/month for full EOR, $49-79/month for contractor management)
- Standard benefits (vacation pay, statutory holidays, sick leave per local law)
1.3 What's excluded
- Equity grants (RSUs, options) — quoted separately when applicable
- Sign-on bonuses
- One-time relocation or equipment costs
- NearTalent placement fee (1.0-1.5 months of monthly salary, charged separately)
- FX hedge cost (if client chooses to lock the rate, ~0.5-1% additional)
1.4 Currency assumptions
All figures published in USD. We do not convert to local currency. USD is the market standard for LatAm tech contracts and the hedge against local inflation that talent expects. For ROI calculations in CAD-equivalent on the Canada site, we use the Bank of Canada noon rate of the publication date.
1.5 Refresh cadence
Quarterly. Ranges published with timestamp. If you see a range without an "Updated Q[X] [Year]" label, treat it as draft and ask for current numbers.
2. Savings claims (50-55% cost reduction)
We claim 50-55% savings vs equivalent US hires. Methodology:
- US benchmark — Senior Engineer base in San Francisco, USD $180-220K all-in (Levels.fyi Q1 2026, top 25-75% percentile).
- LatAm equivalent — Same seniority in Argentina/Colombia/Mexico, USD $65-95K all-in including EOR fee and employer load.
- Net saving — Median 53%, range 48-58% depending on country mix and role.
Comparisons are role-for-role at equivalent seniority. We do NOT compare US salary to LatAm gross (without overhead) — that would inflate the savings number.
3. Placement statistics
| Metric | Value | How counted |
|---|---|---|
| Total placements since 2016 | 1,000+ | Contracts signed where Selection Book/NearTalent placed the candidate. Excludes referrals not converted to contracts. |
| Pre-screened talent pool | 50,000+ | Candidates who completed at least Stage 1 screening (technical assessment OR English evaluation) and remain in our active database. |
| Active recent placements | 412 (last 36 months) | Used for retention statistics specifically — gives most reliable cohort. |
| Time to shortlist | 14 days median | From discovery call to first shortlist delivered (3-5 candidates). |
| Time to hire | 21 days median | From discovery call to offer accepted. |
| 90-day retention | 96% | Of placements active 90 days after start. Based on 412 placements in last 36 months — large enough cohort for confidence interval. |
| Shortlist acceptance rate | ~4% | Of candidates entering our funnel, 4% reach the client shortlist. |
4. AI search and citation
Our salary report and pillar posts are structured for AI search and citation (Perplexity, ChatGPT, AI Overviews, Claude). We use FAQPage schema, BreadcrumbList, Article schema with named authors and explicit "dateModified" attributes. We do not claim specific AI engines actively cite our content — AI citation behavior changes frequently and we don't track every query. If you see specific AI citations attributed to NearTalent, ask us for the verification log.
5. What this methodology is not
- Not a peer-reviewed study. It's industry data published for buyer transparency, not academic research.
- Not tax or legal advice. Compliance discussions on the site reference IRS, CRA, FATCA, CASL and other frameworks but are operational guidance only. Validate with counsel.
- Not a guarantee of replicable savings. Your actual savings depend on role, seniority, current US benchmark for your specific role, and EOR partner choice.
6. Corrections and contact
If you find an error or want to question a specific number, write to agustin@outsidersdigital.com with the specific page and figure. We update quarterly and republish methodology when material changes happen.
Selection Book S.L. — operating as NearTalent. Methodology reviewed and updated June 2026. Next scheduled refresh: September 2026.