Photo-editor shopping fragments by job: full DAM-plus-edit suites like Lightroom and Capture One, RAW-focused tools like DxO PhotoLab, web-first editors like Photopea, AI-driven tools like Topaz, and mobile-first apps like VSCO. Each cluster has different buyers and different shopping criteria, but they all show up in mixed pair searches: Lightroom vs Capture One, Photoshop alternatives, RAW editors compared. SleekRank turns the shelf into a sheet of ~80 apps and renders per-app pages plus pair pages within compatible clusters.

The base WordPress page holds the layout: pricing block, platform support (macOS, Windows, web, iOS, iPadOS, Android), RAW handling capabilities, AI tools list, file format support, integrations, verdict, FAQ, and a "compared with" cluster. SleekRank's mappings fill the H1 from {slug}, pricing tiers via selector mappings, platform and RAW support via list mappings, and a meta mapping renders og:image per app.

App category uses an app_class column with values dam-suite, raw-focused, web-first, ai-driven, and mobile-first. The template renders the right blocks for the right class: a DAM suite gets a library-management block, a RAW-focused app gets a RAW-engine and lens-correction block, a web-first app gets a browser-compatibility block, an AI-driven app gets a model-and-credits block, and a mobile-first app gets a touch-input and export block. Pair pages get gated on cross-class compatibility, with explicit exceptions from frequently_compared_with.

Photographers shop for editors against specific jobs. A wedding photographer wants Lightroom's catalog plus Capture One's color science and compares those two. A landscape photographer cares about DxO's lens corrections and DeepPRIME and compares it against Capture One.

A casual editor without budget searches Photoshop alternatives and lands on Photopea or Affinity. Each of those head-to-heads is its own page because each asks different questions. A page per app and a pair page per real combination matches the shopping behavior, where mega-posts lose to the URL that names the exact comparison the visitor came for.

The structure also matches how the shelf splits. DAM suites compete on library management and tethering. RAW-focused apps compete on engine quality and lens profiles.

Web-first apps compete on browser performance and format breadth. AI-driven apps compete on model quality and credit pricing. Mobile apps compete on export options and touch input.

An app_class column captures those distinctions, and the template surfaces the right blocks, so the Capture One page reads like a pro-RAW review while the Photopea page reads like a web-editor review. Maintenance is where the sheet pulls ahead hard. AI features ship monthly, new camera bodies get RAW support release by release, pricing moves with each major version.

A 80-post hand-written corpus rots in months because no writer keeps that many posts current. A sheet doesn't forget. The result is a shelf that earns rankings on the named head-to-heads photographers actually search, stays current because the data is the source, and grows with each new app launch.