school_compare/docs/superpowers/specs/2026-08-20-seo-programme-design.md

SEO Programme — Design

Date: 2026-08-20 Status: awaiting review

Problem

schoolcompare ranks second for "school compare" — an exact match for the brand and the domain. It ranks poorly for "compare schools", "school comparison" and "schools near me". The first is a naming artefact and transfers to nothing; the rest are the queries that actually carry parent demand.

The cause is structural, not editorial. The site publishes five route families:

/  /compare  /rankings  /admissions  /school/[slug]

Location intent has no landing page at all. Every competitor outranking us on those queries wins with programmatic location pages:

Competitor	URL pattern
School Guide	/best-schools-in/manchester
Locrating	/the-best-primary-schools-in-Manchester_…
FindMySchool	/best-primary-schools/manchester
Snobe	/best-primary-schools/manchester
School Atlas	/guides/best-primary-schools-manchester

"Schools near me" is a local-intent query. Google resolves it against the user's coordinates and serves pages that are about a place. A national homepage cannot win it. No title or description change fixes this; only pages Google can localise will.

Baseline (measured 2026-08-20, production API)

Measure	Value
Unique schools	27,229
URLs in sitemap.xml	27,232
Schools with 2024/25 performance data	21,266
Schools with no current performance data	~5,963 (22%)
Welsh establishments (all metrics null)	1,569
Overseas / offshore establishments	467
Static URLs in sitemap	3
Routes setting a canonical	1 of 5

Three findings from that table drive the plan.

We submit ~6,000 thin pages to Google. build_sitemap() (backend/app.py:73) enumerates every URN regardless of whether the school has any data. Welsh establishments return school_type: "Welsh establishment" with every performance metric, Ofsted grade and phase field null. Overseas and offshore establishments ("BFPO Overseas Establishments", "Gibraltar Overseas Establishments", "Jersey Offshore Establishments") are in the local-authority list too. At 22% of the submitted corpus this is a site-wide quality signal problem and a crawl-budget waste, not a rounding error.

W1 item 4 removes 2,036 of those — every non-England establishment — taking the corpus to 25,193. The 3,927 that remain are English schools with no current data: mostly newly opened, special, nursery or alternative provision. Those are a template problem, not a corpus problem, and item 5 handles them separately.

The homepage is its own competitor. app/page.tsx accepts eleven search params (search, local_authority, school_type, phase, page, postcode, radius, sort, gender, admissions_policy, has_sixth_form) and sets no canonical. Every filter combination is a crawlable near-duplicate of the single page we are asking to rank for "compare schools".

School pages are near-orphans. Reachable from the sitemap and from site search, but almost nothing links to them contextually, so they accrue no internal authority.

Also noted: the sitemap emits invented priority values and no lastmod. Google ignores priority and changefreq entirely; lastmod is the field it does read, and we omit it.

Keyword clusters

Ranked by judgement of UK parent search behaviour and by the competitive SERP evidence above. Google Search Console is connected, so cluster priorities are to be re-derived from measured impressions before build starts (see Workstream 0).

C1 — Head "compare" terms. compare schools · school comparison · school comparison tool · compare school performance · compare primary schools · compare secondary schools · compare two schools

C2 — League tables and rankings. primary school league tables · secondary school league tables · school league tables 2026 · SATs results by school · GCSE results by school · KS2 league tables · Progress 8 rankings · best primary schools in [town] · top 10 primary schools in [LA]

C3 — Local / near me. schools near me · primary schools near me · secondary schools near me · best schools near me · good schools near me · schools in [town] · primary schools in [LA] · schools near [postcode] · [postcode] school catchment

C4 — Individual school long tail. [school] ofsted · [school] SATs results · [school] catchment area · [school] reviews · [school] URN

C5 — Admissions. primary school admissions 2027 · national offer day 2027 · school application deadline · school admissions appeal · oversubscription criteria · distance criteria school admissions · didn't get first choice school · school admissions [LA]

C6 — Metric explainers. what is a good SATs score · what is Progress 8 · what is Attainment 8 · expected standard KS2 meaning · scaled score explained · Ofsted grades explained · Ofsted report cards · pupil premium explained

C7 — Head to head. [school A] vs [school B] · academy vs community school · grammar school vs comprehensive · faith school vs community school

Workstreams

W0 — Measure before touching anything

Export a Google Search Console baseline: impressions, clicks, average position and CTR by query and by page, for the trailing 16 months. Bucket queries into C1–C7. This sets the counterfactual — without it, no later claim about lift is defensible, because school-search traffic is strongly seasonal (results day in December, offer day in March/April).

Re-rank C1–C7 against measured impressions and adjust the sequence below if the data disagrees with the judgement calls.

W1 — Crawl hygiene and index sanity

Cheap, and it unblocks everything after it. Adding 5,000 pages on top of a corpus that is 22% thin would compound the existing problem.

1. Canonical on every route. /, /rankings, /compare and /admissions currently set none.
2. The homepage canonicalises to / regardless of search params.
3. /compare?urns=… gets noindex, follow — it is an unbounded parameter space with no standalone value.
4. England only — DONE. Wales, the Crown Dependencies, Gibraltar and the service/overseas schools are removed from the corpus at the mart boundary, not hidden at the view layer. dim_school and dim_location both exclude TypeOfEstablishment in {25, 26, 30, 37} — Offshore schools, Service children's education, Welsh establishment, British schools overseas — listed once as vars.non_england_school_type_codes in dbt_project.yml. That removes 2,036 establishments and 29 local authorities, and because build_sitemap() reads the same marts, it drops them from the sitemap in the same stroke. assert_england_only_schools fails the pipeline if a GIAS refresh reintroduces them or if the two models drift apart.
5. Prune the remaining thin pages: exclude any school with no performance data and no Ofsted record. Distinct from item 4 — these are English schools with nothing yet to show, so the fix may be a better template rather than removal.
6. Rebuild the sitemap as a sitemap index: one child per page family, real lastmod from the data-load timestamp, priority and changefreq dropped.

W2 — The location layer

The dominant lever. dim_location already carries town, county, local_authority_name, parliamentary_constituency, latitude, longitude and postcode, so no new ingestion is required.

Routes:

/schools/[la]                     e.g. /schools/manchester
/schools/[la]/primary
/schools/[la]/secondary
/best-primary-schools/[town]
/best-secondary-schools/[town]
/schools/near/[outcode]           e.g. /schools/near/m20
/schools/near-me                  geolocating hub

Thin-page threshold: generate a town or outcode page only where at least five schools have current performance data. Below that, 301 to the parent LA page. This is the single most important constraint in the workstream — it is what separates a location layer from index bloat.

Each page must earn its place with content a parent would actually use, not a template shell:

• H1 matching the query intent ("Best primary schools in Manchester")
• Counts framed usefully: "137 primary schools, 9 rated Outstanding"
• A ranked table of the top 20 on the headline metric
• Local average against the England average
• Ofsted grade distribution
• Map
• Links to neighbouring towns and to the parent LA
• An FAQ block (feeds FAQPage in W4)
• Links to every school page in scope — this is what de-orphans W1's corpus

Sizing estimate: ~150 usable LAs × 3 ≈ 450; towns clearing the threshold ≈ 1,200 × 2 ≈ 2,400; outcodes ≈ 2,300. Roughly 5,000 new pages, comfortably inside a sitemap index and well under the per-file 50,000 limit.

W3 — Make rankings indexable

/rankings is driven entirely by query params, so Google indexes approximately one page where there should be hundreds.

/rankings/[phase]/[metric]
/rankings/[phase]/[metric]/[la]

The interactive filter UI stays; its state moves into real paths. Param forms canonicalise to the clean path. This is the direct play for C2.

W4 — Structured data and internal linking

• Replace the bare EducationalOrganization on school pages with School, and populate it properly.
• BreadcrumbList site-wide.
• ItemList on every rankings and location page.
• FAQPage on admissions and on location pages.
• New school-page modules: "Other schools in [town]", "Nearby schools", "Compare with similar schools". Each links out to W2 and W3 pages, which is what circulates authority instead of stranding it.

Explicitly not doing Dataset or AggregateRating — no review corpus exists, and fabricating one would be both useless and a policy violation.

W5 — Admissions expansion

One static page currently carries an entire cluster.

/admissions/[la]                  per-authority deadlines and offer day
/admissions/appeals
/admissions/national-offer-day

school admissions [LA] is high-intent and highly seasonal; per-authority pages are the natural unit.

W6 — Explainer content

/guides/progress-8
/guides/attainment-8
/guides/sats-scaled-scores
/guides/ofsted-grades
/guides/expected-standard

Each links into the corresponding W3 rankings page. Cheap to build, and it is what gives the metric vocabulary enough topical weight to support C1–C4.

W7 — Head-to-head pages

/compare/[school-a]-vs-[school-b]

C7 is uncontested and native to the product. It is also the easiest way to destroy everything W1 fixes: 27,229 schools generate 370 million pairs. Curated pairs only — same town, both with current data, both with real search demand — capped in the low thousands. Gated behind evidence that W2 is indexing cleanly.

W8 — Metadata rewrite for C1

Current homepage title is schoolcompare | Compare every school in England, which spends the most valuable position on the brand. Rewrite the homepage, rankings and compare titles and descriptions around C1 phrasing. Small change, and the cheapest item in the programme.

Sequencing

W0 → W1 → W2 → W3 → W4 → W5 → W6 → (W7 if W2 indexes cleanly)

W1 before W2 is not negotiable: adding pages to a corpus that is 22% thin compounds the problem rather than diluting it.

This spec is a programme, not a single implementation plan. Each workstream gets its own plan and its own PR; W2 will likely need several. Only W0 and W1 are ready to plan against today — the rest should be re-read after W0's Search Console baseline lands, because that data may reorder them.

Testing

Per CLAUDE.md, user-facing behaviour changes extend the e2e/ journeys in the same PR. Each workstream adds:

• W1: canonical present and correct on every route; /compare?urns= carries noindex; sitemap excludes a known dataless URN.
• W2: a known LA, town and outcode page renders with the expected school count; a below-threshold town redirects to its LA.
• W3: a clean rankings path renders; the param form canonicalises to it.
• W4: JSON-LD parses and validates against the declared types.

Risks

Index bloat. The failure mode of every programmatic SEO programme. The five-school threshold, the W1 prune and the W7 gate are the three controls.

Helpful-content exposure. Google's stance on templated location pages has hardened. The mitigation is that each page carries genuinely local computed data — real counts, real distributions, real local-vs-national comparison — rather than a name substituted into boilerplate.

Build cost. School pages already use ISR with a 7-day revalidate and PRERENDER_SCHOOLS gating full prerender. 5,000 more routes need the same treatment; full static generation of 32,000 pages is likely impractical in CI.

Seasonality. Results day and offer day dominate the traffic curve. Judging the programme on a mid-summer window would misread it in either direction. W0's baseline must be year-on-year, not month-on-month.

Open questions

1. Catchment areas are Locrating's moat and a strong C3 driver ([postcode] school catchment). fact_admissions carries admission distances. Is deriving approximate catchment a later workstream, or out of scope?