Recruiting-tech buyers shortlist three to five vendors and compare them in named pairs: Greenhouse vs Lever for a 200-person scale-up, Workable vs JazzHR for a startup, Gem vs SeekOut for sourcing. The long tail of those pair pages is huge and most review sites cover ten percent of it because hand-writing each pair takes a day. SleekRank turns the shelf into a sheet of about 150 vendors and renders both per-vendor pages and pair pages from the same data.

The base WordPress page holds the layout: pricing block, modules checklist (ATS, sourcing, scheduling, CRM), integrations table, verdict, FAQ, and a "compared with" cluster. SleekRank's mappings fill the H1 from {slug}, pricing and modules via selector and list mappings, and the meta mapping renders og:image per vendor. A second page group at /recruiting-software/{a}-vs-{b}/ reads two rows and renders a head-to-head template.

Vendor categorization handles the awkward case where some platforms are full ATS suites and others are sourcing-only or scheduling-only. A category column with values ats, sourcing, scheduling, crm drives a conditional include in the modules block, so a sourcing-only tool gets a sourcing-focused page rather than a half-empty ATS template. The same column controls which pair pages get generated: ATS-vs-ATS and sourcing-vs-sourcing combinations rank, mixed-category pairs don't get published.

Recruiting-software buyers don't search broadly. They search for specific vendors and specific head-to-heads inside a category they've already chosen. An ATS shopper searches Greenhouse vs Lever, not "best HR software." A sourcing-team lead searches Gem vs SeekOut, not "best recruiting tech." A page per vendor and a pair page per real combination matches that shopping behavior, where a mega-post loses to the URL that names the exact pair the visitor came for.

The structure also matches how vendors differ. ATSes share a feature shape, sourcing tools share a different shape, scheduling tools share a third. A category-aware template renders the right blocks for the right tool type, so the corpus stays useful even as it spans 150 vendors across four categories.

Maintenance is the real win. Pricing moves quarterly, modules ship monthly, vendors rebrand and acquire each other annually. A hand-written corpus of 150 posts and a few hundred pair pages rots fast because nobody opens that many posts to edit one bullet.

A sheet stays current because the edit is one cell. New vendors land in the corpus by adding a row and updating peers' frequently_compared_with values. The result is a shelf that earns rankings on specific head-to-heads, stays accurate because the data is the source, and grows in coverage with each new vendor instead of stalling.