SleekRank for fossil listings
Per-specimen and per-locality landing pages built from one spreadsheet. Map species and formation to headlines, age and provenance to badges, preparation notes to schema, and ship indexable WordPress pages from a single base template.
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Locality-and-formation pages are how fossils get found
Fossil search is unusually precise. A collector chasing "Hell Creek Tyrannosaurus tooth Garfield County" wants the species, the formation, the county, the geological age, the preparation level, and any restoration disclosure. The rankable surface is species x formation x locality x preparation, tens of thousands of permutations once you cover trilobites, ammonites, dinosaur material, and a working stock. Hand-building those pages is impossible. SleekRank reads a single Google Sheet, CSV, JSON file, or REST endpoint and emits one WordPress page per row, all sharing the base template you already designed in the editor.
The data layer is the inventory. Add a row for a 4-inch Tyrannosaurus tooth from the Hell Creek Formation in Garfield County at $14,000 with a no-restoration disclosure and the page goes live on the next cache refresh. Update the price after a Heritage natural-history auction settles a comparable specimen, every relevant page picks it up. No static rebuilds, no per-listing edits, no engineer.
Mappings do the wiring. Tag mappings push the species and formation into the H1 and document title; selector mappings put the locality and preparation level into the spec block; list mappings render measurement details and matrix notes from a JSON column. The XML sitemap auto-includes every generated URL. Sold specimens return 404 cleanly on the next refresh.
Workflow
From inventory row to ranked fossil page
Design the base page
Connect the sheet
Wire the mappings
Publish and flush
Data in, pages out
From inventory row to live listing URL
Each row becomes one page. The slug column maps to the URL, the rest of the columns flow into headlines, age badges, preparation notes, and OG tags through simple selector or list mappings.
| slug | species | formation | locality | age | price |
|---|---|---|---|---|---|
| tyrannosaurus-tooth-hell-creek-garfield-county | Tyrannosaurus rex | Hell Creek | Garfield County, MT | Late Cretaceous | $14,000 |
| megalodon-tooth-hawthorne-formation-bone-valley | Otodus megalodon | Hawthorne | Bone Valley, FL | Miocene | $2,400 |
| elrathia-trilobite-wheeler-shale-utah | Elrathia kingii | Wheeler Shale | Millard County, UT | Middle Cambrian | $45 |
| cleoniceras-ammonite-mahajanga-madagascar | Cleoniceras besairiei | Bemiriva | Mahajanga, Madagascar | Early Cretaceous | $180 |
| knightia-fish-green-river-wyoming | Knightia eocaena | Green River | Lincoln County, WY | Eocene | $95 |
/fossils/{slug}/
- /fossils/tyrannosaurus-tooth-hell-creek-garfield-county/
- /fossils/megalodon-tooth-hawthorne-formation-bone-valley/
- /fossils/elrathia-trilobite-wheeler-shale-utah/
- /fossils/cleoniceras-ammonite-mahajanga-madagascar/
- /fossils/knightia-fish-green-river-wyoming/
Comparison
Hand-crafting fossil pages vs SleekRank
Building each listing manually
- Each specimen is a duplicated WordPress page with hand-typed locality and age
- Adding 60 freshly prepped specimens means 60 pages built one at a time
- Restoration disclosures after a re-prep require touching every page
- No structured data layer, Product schema hand-written per specimen
- Sitemap, indexing, OG tags, all maintained per page
- Inventory lags reality, sold specimens linger, sitemaps drift
SleekRank
- One base page in WordPress, thousands of fossil pages generated from data
- CSV, Google Sheets, JSON, REST API, or Notion as the source of truth
- Edit a row, page updates automatically on the next cache refresh
- Mappings handle title, H1, age badges, preparation notes, meta tags, and OG images
- XML sitemap auto-generated for every produced URL
- WordPress-native, works with your theme, your blocks, your editor
Features
What SleekRank gives you for fossil listings
Seven data source types
Google Sheets, CSV files, JSON URLs, JSON files, Notion databases, REST APIs, and CSV URLs. Mix multiple sources in one page group when inventory data and stratigraphic database data live separately.
Four mapping types
Replace by tag (h1, title), by CSS selector (#age, #preparation), by list iteration for measurement details, or by meta tag for description and og:image. Each mapping targets one cell.
Cache and rebuild
Set cache duration per source, 10 minutes during a Tucson Fossil Show week, 24 hours when stable. Invalidate on schedule or on demand. Pages render from cache, not from a static build step.
Use cases
Where fossil listings shine with SleekRank
Fossil dealers
Per-specimen pages with species, formation, locality, and age beat a generic shop archive. Collectors search for the precise formation, serve them a URL with the preparation log already laid out.
Natural-history auctions
Each lot becomes a WordPress companion page that ranks on long-tail species-plus-locality queries, with a clean redirect to the live bidding page when the auction goes hot.
Museum study sites
Per-formation reference pages drawn from collection data feed the queries that academic press cannot cover, generated from a curator spreadsheet rather than a CMS export.
The bigger picture
Why per-locality fossil pages outrank shop archives
A single shop archive filtered by query string cannot win "Hell Creek Tyrannosaurus tooth Garfield County" against a competitor who built a dedicated, schema-marked URL for it. Google ranks pages, not parameters. Fossil intent is also high-value bottom-of-funnel, the buyer quotes the formation, knows the locality, and is comparing three dealers at once.
Duplicated boilerplate gets bounced and unique data wins. The specimens that rank carry specifics: precise locality, formation, geological age, preparation level, restoration disclosure, photographs of the specimen in matrix and prepped. Maintaining that uniqueness across 1,800 specimens by hand is impossible; maintaining it across 1,800 rows in a sheet is a single afternoon.
SleekRank turns the inventory spreadsheet into the SEO surface, which collapses the gap between the prep technician who handles the matrix and the team that owns the URLs. The base page still belongs to WordPress, so design, tracking, and CRO experiments stay where they always lived. Adding a new specimen becomes a row plus a cache flush rather than a sprint.
Questions
Common questions about SleekRank for fossil listings
Page groups with 5,000+ generated URLs run on a single base template without issue. The data layer is cached and rendering re-uses your existing WordPress page, so the practical ceiling is your hosting plan and your sitemap budget. Most fossil catalogues top out well below the technical limit because Google's crawl budget for new pages slows past a few thousand.
Yes. Edit your Google Sheet, push to your inventory REST endpoint, or update the CSV in the theme. SleekRank refreshes on the next cache cycle, and you can clear the cache manually from the admin or via WP-CLI. No theme deploy, no static site build, no engineering ticket.
Yes. SleekRank uses your existing base WordPress page as the template. Whatever theme, blocks, page builder, or custom CSS rendered that page renders every generated URL identically. Bricks, Elementor, Gutenberg, Oxygen, and classic themes all work because SleekRank operates on the rendered HTML.
Yes. They are real WordPress URLs with full HTML, sitemap inclusion, and per-page meta tag mappings for title, description, canonical, and og:image. The base template page is excluded from the sitemap and marked noindex automatically so it never competes with the generated listings.
Yes. You can branch a mapping based on a species-group column, or run multiple page groups against subsets of the data. A common pattern: /fossils/{slug}/ for vertebrate material with a richer template, /fossils/invertebrate/{slug}/ for trilobites and ammonites with a leaner one.
On the next cache refresh the URL stops resolving and returns 404. The sitemap is regenerated automatically so search engines drop the URL cleanly. If you would rather redirect a sold specimen to a similar species, point the slug at a wildcard rule in your normal WordPress redirects plugin before deleting the row.
Make the data carry the difference. Localities, formations, ages, preparation notes, restoration disclosures, and matrix details all vary per row. Avoid copy-paste paragraphs that swap only the species name. The richer the per-specimen data, the lower the duplicate-content risk.
Yes. A URL pattern like /{species}/{formation}/ produces /trex/hell-creek/, /megalodon/hawthorne/, /elrathia/wheeler/ from a combined data set or two joined sheets. Use a species sheet and a formations sheet, then run mappings against the cross-product.
Pricing
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