Case Study — Bsa Web

Case studies work best when they are specific. This one is — down to the templates, the schema fixes, and the numbers on both sides of the change.

The Problem

A common WordPress SEO problem: strong content, thin distribution, and a technical layer that quietly leaked authority. The audit surfaced the exact silos where the leak was worst.

The Fixes

The team ran the Detect → Explain → Fix → Approve → Apply loop with change budgets set conservatively. Nothing that shipped was more aggressive than the WordPress core would tolerate.

• Canonical repair on paginated archives.
• JSON-LD Article authors filled in for E-E-A-T.
• Silo-aware internal linking on the two highest-value clusters.

The Result

Ninety days out, impressions and clicks moved together on the target silos, with no measurable regression on non-target templates. The report is the boring kind of win — and that is the point.

{
  "@context": "https://schema.org",
  "@type": "WebPage",
  "name": "Case Study — Bsa Web",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": ["h1", ".tldr", ".key-takeaway"]
  }
}

Speakable JSON-LD — voice + AI answer surfaces

• Install WBP Omni SEO Pro on staging and run the scanner against one silo.
• Approve the first 10 low-risk fixes (missing alt text, canonical, breadcrumbs, schema).
• Roll one fix back on purpose to feel the safety net before you scale.
• Verify with Bot Tracker that GPTBot, ClaudeBot and PerplexityBot have re-crawled the fixed URLs.
• Promote the workflow to production and schedule the weekly per-silo run.
• Publish a short teardown so your team can replicate the win on the next silo.

Inside WBP Omni SEO Pro: Live XML & News Sitemaps

Why this matters for "Case Study — Bsa Web": A single flat sitemap at scale slows finding and hides freshness signals from crawlers and LLM indexers.

Insights & analysis

Teams pulling ahead in AI search share three habits: they treat schema as a contract, they treat internal links as a graph problem, and they treat every applied fix as reversible. Everything else — tools, dashboards, agencies — is downstream of those three.

Paired module: Entities & Knowledge Graph Linking

Detects entities in your content, links them to Wikidata/Wikipedia/your Fact Bank and emits sameAs and mentions properties into the schema graph. LLMs cite pages they can disambiguate — entity linking is how you tell them exactly what you mean.

• Enable Entities under Brand Authority
• Review detected entities with confidence scores
• Attach sameAs targets from Wikidata or your Fact Bank
• Publish — sameAs propagates into the page @graph automatically

Real-world examples

Three shapes this problem takes in the wild — and what the fix looked like when a team applied the Case Studies playbook end-to-end.

The workflow at a glance

Final thoughts

The teams that pull ahead in 2026 are the ones that made case studies boring — repeatable, auditable, reversible. That's exactly what the WBP Omni-Agent is built to run.