Build authority across every sector you serve.
You compete with sector specialists in every vertical. They go deep. You go wide. Korvex gives you the intelligence to go deep and wide — with per-sector scoring, per-sector gaps, per-sector competitors, and per-sector revenue tracking.
You serve 4 sectors. Google sees one domain.
Sector specialists have it easy. A company that only does manufacturing compliance can pour all resources into one vertical. Every page reinforces the same topical authority. Every backlink strengthens the same entity associations.
You’re competing against them in manufacturing. And against healthcare specialists in healthcare. And against financial services publishers in financial services. Your authority is spread across verticals, and your SEO tools don’t measure performance by sector — they give you sitewide averages that hide the real picture.
If you can’t measure per sector, you can’t compete per sector.
Google can’t tell what you’re expert in
Strong manufacturing masks weak healthcare
You face different competitors per sector
Generic gaps miss sector-specific entities
Can’t tell which sectors drive leads
Korvex resolves every one of these by segmenting intelligence at the sector level.
Topical authority isn’t sitewide. It’s per-sector.
Koray’s topical authority model measures coverage across 3 axes — vastness, depth, and momentum. For multi-sector businesses, each axis must be measured per vertical. A manufacturing authority score of 78 means nothing if your healthcare score is 23.
How many subtopics you cover within a sector. Manufacturing might need 40 topic clusters to be comprehensive. Healthcare might need 60. Korvex benchmarks against sector-specialist competitors to set the target.
- Cluster count per sector
- Coverage % vs sector leaders
- Missing cluster identification
How thoroughly you cover each subtopic within a sector. Thin sector pages signal Google that you’re a generalist, not a specialist. Depth scoring measures entity density, word count, and information gain vs SERP leaders.
- Entity density per cluster
- Information gain scoring
- Depth vs SERP leader comparison
How fast you’re publishing new content within each sector. Publishing velocity signals ongoing investment. Sector specialists publish 2–4 pages per week in their vertical. If you publish 1 page per month per sector, Google notices.
- Publishing velocity per sector
- Content freshness decay curves
- Velocity vs competitor benchmarks
Your questions, answered.
Strategic intelligence for businesses operating across multiple industries.
Are we building authority per sector?
Topical authority mapping measures your coverage across Koray’s 3 axes: vastness (breadth of topics covered), depth (thoroughness per topic), and momentum (publishing velocity). Each sector gets its own authority score, tracked independently so you see exactly where you’re dominant and where you’re thin.
Which sectors generate the best leads?
GA4 attribution segmented by landing page groups. See traffic, conversions, and revenue broken down by industry sector — so you invest in the sectors that actually drive business, not the ones that just generate impressions.
Do landing pages show real expertise?
E-E-A-T fingerprinting runs stylometry analysis on every page — measuring authoritativeness, experience signals, and entity expertise. Not generic SEO metrics — actual expertise signals Google looks for when deciding whether you’re a real player in a sector.
What content gaps exist per sector?
Content gap analysis runs daily with entity-level competitor comparison. See exactly what topics and entities your competitors cover in each sector that you don’t — down to the specific subtopics and missing entities with salience scores.
Are we measuring by sector?
Configurable keyword groups give you separate ranking, traffic, and revenue dashboards per sector. Monitor manufacturing independently from healthcare. Set goals per vertical. Know exactly which sectors are growing and which are stalling.
How do we beat sector-specialist publishers?
Entity intelligence and information gain scoring identify where your real-world operational expertise can outperform publisher content. Semantic clustering maps topic ownership opportunities where hands-on experience wins over editorial breadth.
18 hypothesis generators. Running per sector. Every day.
The Strategic Content Intelligence System (SCIS) runs 18 generators against your data for each sector. Not generic sitewide advice — sector-specific recommendations with confidence scores, estimated revenue impact, and dependency mapping. A title optimisation for a manufacturing page uses manufacturing competitor patterns, not your healthcare SERP data.
Title Optimisation
Analyses SERP title patterns across top 10 competitors per query within each sector. Identifies click-optimized title structures with estimated CTR uplift per vertical.
Meta Description
Evaluates meta description performance against SERP click-through benchmarks. Sector-specific CTA patterns surface industry language that converts.
H1 Alignment
Ensures H1 tags match dominant search intent per sector. Detects mismatches between informational intent and commercial framing in each vertical.
Internal Linking
Identifies orphaned pages and broken hub-spoke structures within sector pillars. Maps PageRank distribution across sector hubs and suggests cross-sector linking.
Entity Gap Analysis
Compares your entity coverage against sector-specific competitors per query cluster. Flags missing entities with salience scores and topical relevance per vertical.
Content Freshness
Flags stale content prioritised by traffic impact within each sector. Calculates freshness decay curves based on SERP volatility for sector-specific topics.
Schema Markup
Detects missing structured data by analysing which SERP features sector competitors win. Maps schema types to pages with highest rich-result potential per vertical.
FAQ Opportunities
Identifies question-intent queries per sector where FAQ schema could win featured snippets. Extracts People Also Ask data to generate sector-specific FAQ content.
Keyword Cannibalisation
Detects cross-sector pages competing for the same queries using GSC impression overlap. Suggests sector-specific consolidation or intent differentiation.
Thin Content
Identifies below-threshold pages per sector hub using word count, entity density, and topical depth. Recommends expand, consolidate, or noindex by traffic profile.
Redirect Chains
Flags redirect chains hurting crawl budget within sector sections. Calculates aggregate crawl budget impact across each vertical’s sitemap partition.
Image Alt Text
Identifies missing or generic alt text on high-traffic sector pages. Generates entity-aware, sector-specific alt text suggestions aligned with topic clusters.
Page Speed Impact
Correlates Core Web Vitals changes with ranking movements per sector. Identifies pages where CWV improvements would have the highest position impact per vertical.
Topical Authority
Maps topic clusters per sector and measures depth vs sector-specialist competitors. Identifies where topical coverage is insufficient to establish authority in a vertical.
Competitor Content Gaps
Daily comparison against sector-specific competitors per cluster. Quantifies each gap in estimated monthly traffic and revenue potential per vertical.
Semantic Similarity
Detects near-duplicate content across sectors using Qdrant vector embeddings. Flags pages with semantic overlap that may trigger quality filters or cannibalise across verticals.
Featured Snippets
Identifies queries per sector where you rank positions 2–8 and a featured snippet exists. Analyses snippet format and suggests sector-appropriate content restructuring.
AI Search Readiness
Scores content per sector for citation-worthiness across ChatGPT, Perplexity, and Gemini. Evaluates structured data, entity markup, and answer format quality per vertical.
Each generator produces sector-specific recommendations scored by confidence (0–100), estimated revenue impact, implementation effort, and dependency chain. Manufacturing recommendations are prioritised separately from healthcare. You see the ranked output on a kanban board — drag to approve, Korvex handles the rest.
Every sector page scored daily across 47 factors.
Based on the Koray Tugberk methodology — the most comprehensive page-level scoring framework in SEO. Every page in every sector gets a daily score across technical SEO, content quality, entity relevance, authority signals, and user experience. Sector averages show you which verticals have strong content and which need investment.
The scoring drives recommendation prioritisation. Pages with the highest improvement potential and traffic value in each sector surface first — so your manufacturing team and healthcare team each get their own optimised action queue.
- 47 factors across 5 categories, weighted by impact
- Sector average scores for portfolio-level comparison
- Customisable factor weights per sector profile
- Daily rescoring with fresh GSC, GA4, and competitor data
See how Korvex maps your sectors.
14-day free trial. Full sector intelligence. No credit card required.
Content gaps aren’t sitewide. They’re sector-specific.
A generic content gap analysis tells you that competitors cover “predictive maintenance” and you don’t. Useless. That’s a manufacturing topic. Your healthcare competitors don’t cover it either.
Korvex runs gap analysis per sector, against sector-specific competitors. Manufacturing gaps use manufacturing competitor data. Healthcare gaps use healthcare competitor data. Each gap includes the specific entities you need to cover, the number of competitors who own that topic, and the estimated traffic opportunity — all scoped to the relevant vertical.
- Entity-level gap identification per sector
- Sector-specific competitor comparison, not sitewide
- Estimated traffic and revenue per gap opportunity
- Daily refresh as competitor content changes
4 competitors cover this · 8 entities to include
3 competitors cover this · 12 entities to include
5 competitors cover this · 6 entities to include
2 competitors cover this · 15 entities to include
3 competitors cover this · 9 entities to include
3 competitors · 11 entities
5 competitors · 7 entities
4 competitors · 14 entities
Mgmt
Safety
Assess
Software
Entities connect across sectors. Your graph should show it.
Google’s Natural Language API extracts entities from your content and competitor pages. Korvex stores these in a Neo4j knowledge graph with salience scores, topic relationships, and competitive gaps — all segmented by sector.
The graph reveals cross-sector entity opportunities. “Risk management” appears in manufacturing, healthcare, and financial services. If your manufacturing pages own that entity but your healthcare pages don’t, the graph highlights the gap. Qdrant vector embeddings detect semantic overlap across sectors to prevent content cannibalisation.
- Per-sector entity mapping vs sector-specific competitors
- Cross-sector entity opportunity detection
- Knowledge graph updated daily with fresh NLP extraction
- Vector embeddings prevent cross-sector cannibalisation
Topical authority tracked per vertical. With sector-specific benchmarks.
Sitewide topical authority is a vanity metric for multi-sector businesses. Your manufacturing authority might be 78 while your energy authority is 34. A sitewide average of 56 hides both the strength and the weakness.
Korvex measures vastness, depth, and momentum per sector and benchmarks against sector-specialist competitors. See where you’re dominant, where you’re competitive, and where sector specialists are running away from you — with specific recommendations to close the gaps.
- Per-sector authority scoring on 3 axes
- Benchmarked against sector-specialist competitors
- Authority trend lines per vertical updated daily
Up to 12 competitors per sector · Daily velocity, entity coverage, and SERP feature tracking
Different competitors in every sector. Korvex tracks them all.
In manufacturing, you compete with Siemens and Honeywell. In healthcare, it’s NHS Digital and specialist SaaS providers. In financial services, it’s the Big Four consultancies. No other platform lets you define separate competitor sets per sector and track them independently.
Daily monitoring per sector: content velocity, entity coverage shifts, SERP feature ownership, topical authority movements, and ranking trajectory by cluster. Content velocity is a 3–6 month leading indicator — see where competitors are investing before their rankings show it.
- Up to 12 competitors per sector, independently tracked
- Content velocity as early warning indicator
- Entity coverage gap tracking per sector
- Cross-sector competitive landscape overview
See per-sector intelligence running on your own data.
Full sector-level scoring, gap analysis, and competitor intelligence. No credit card required.
Hub/pillar structure mapped per sector.
Each sector needs its own hub page linking to pillar pages, which link to supporting content. Korvex maps your site architecture per sector, identifies orphaned pages, weak internal links, and missing pillar coverage. Health scores are calculated per sector hub.
Manufacturing
42 pages · 6 pillars
Strong linking
2 orphaned
Healthcare
31 pages · 4 pillars
Moderate linking
5 orphaned
Financial
28 pages · 5 pillars
Strong linking
1 orphaned
Energy
18 pages · 2 pillars
Weak linking
7 orphaned
pillar pages
orphaned pages
internal links mapped
74 automated jobs run overnight. Sector-segmented by the time you open your laptop.
The daily intelligence pipeline collects, analyses, scores, predicts, and recommends — all while you sleep. Every phase outputs sector-segmented data, so your morning brief shows manufacturing performance separately from healthcare, financial services, and energy.
GSC Performance
Search Console data across 12 dimension types, per sector
Keyword Rankings
DataForSEO rankings for all tracked keywords by vertical
GSC Crawl Health
Crawl budget analysis per sector hub using Koray methodology
GA4 Analytics
11 dimension types: traffic, revenue, conversions by sector
Site Health
Diagnostic snapshot across all sector pages
Competitor Analysis
Per-sector competitor velocity, entity coverage, rank changes
Content Gap Analysis
Cross-competitor gap identification by sector cluster
Ranking Predictions
ML model generates 30/60/90-day forecasts per vertical
Page Scoring
47-factor Koray score for every active page in each sector
SCIS Recommendations
18 generators produce sector-specific prioritised actions
Daily Email Brief
12-section report with per-sector performance delivered
Outcome Tracking
Measures deployed recs per sector, calibrates predictions
daily phases
scheduled jobs
registered tasks
manual steps
Know which sectors drive revenue. Invest accordingly.
GA4 integration maps the full path: organic landing page → sector attribution → conversion event → revenue. See exactly which sectors generate leads and which sectors generate impressions but no business.
When leadership asks “should we invest more in healthcare content?”, answer with data. Healthcare sector organic revenue: £4,200/month. Manufacturing: £12,400/month. Energy: £800/month. The numbers tell you where to double down and where to deprioritise.
- Revenue, leads, and conversions broken down by sector
- Month-over-month growth per vertical
- PPC cost equivalency per sector for ROI justification
- Revenue per recommendation tracked per vertical
prediction accuracy at 30 days
Model trained on per-sector data. Accuracy improves from ~80% in week 1 to 91%+ by day 30.
91% prediction accuracy. Per sector.
The XGBoost ensemble trains on sector-segmented historical data — GSC, GA4, rankings, page scores, and competitor patterns per vertical. Predictions are sector-specific because the ranking dynamics are different: a manufacturing title rewrite may yield different CTR uplift than a healthcare one.
Every prediction is tracked per sector. The model learns that entity enrichment works better in healthcare than manufacturing, and that schema markup has higher impact in financial services. Sector-specific calibration makes every prediction more accurate over time.
- Predict → execute → measure → learn per sector
- 30/60/90-day forecasts per vertical
- Seasonal pattern detection per sector
- Sector-specific model calibration from outcomes
AI answers are sector-specific. Is your content being cited in each vertical?
ChatGPT, Perplexity, Gemini, and Google AI Overviews pull content from the web and present it as synthesised answers. When someone asks an AI engine about manufacturing compliance, your manufacturing content needs to be structured for citation. Your healthcare content needs the same — independently.
Korvex scores AI readiness per sector page across 6 dimensions that determine citation-worthiness. See which verticals are well-structured for AI engines and which sectors are invisible to the growing segment of AI-mediated search.
- Per-sector AI readiness scores
- Citation tracking across 4 AI engines
- Sector-specific structural recommendations
Approve a recommendation. It deploys to the right sector page automatically.
When you approve a recommendation on the kanban board, Korvex pushes the change directly to WordPress, Shopify, or Webflow via their APIs. Title changes, meta descriptions, schema markup, internal links — deployed to the correct sector page with rollback capability. Every deployment is tracked for outcome measurement per sector.
WordPress
Title rewrites, meta descriptions, schema markup, internal links, and content enrichment deployed via the WordPress REST API. Sector-specific rollback on every change.
Shopify
Push content changes to articles, products, and pages per sector. Schema markup, meta fields, and product descriptions deployed via Shopify API.
Webflow
CMS collection items, page metadata, and structured content deployed through the Webflow API. Works with the Designer Extension for sector hub pages.
See per-sector intelligence on your own domain.
We’ll run the full 47-factor scoring, per-sector gap analysis, and competitive intelligence on your site. 14-day free trial.
Everything a multi-sector business needs. In one platform.
Three pillars of per-sector intelligence that replace sitewide averages, manual spreadsheets, and guesswork.
Per-Sector Measurement
Every metric segmented by vertical. Rankings, traffic, conversions, revenue, authority scores, and content health — all tracked independently per sector so you see the real picture, not a blended average.
- Sector-segmented keyword tracking
- Per-vertical revenue attribution
- Topical authority per sector
- Sector health scores and trends
Sector-Specific Intelligence
18 SCIS generators producing recommendations per sector. Content gap analysis against sector-specific competitors. Entity knowledge graph segmented by vertical. Predictions trained on per-sector data.
- Per-sector SCIS recommendations
- Sector-specific competitor sets
- Entity gaps by vertical
- ML predictions per sector
Closed-Loop Execution
Approve a recommendation, it deploys to the correct sector page via CMS API. Outcome tracked per vertical. Model calibrates per sector. System gets smarter about each vertical independently.
- Auto-deploy to WordPress/Shopify/Webflow
- Per-sector outcome tracking
- Sector-specific model calibration
- Rollback capability per deployment
What Korvex replaces for multi-sector businesses.
You’re currently stitching together sitewide tools that weren’t designed for sector segmentation. Here’s what changes.
Sitewide keyword tracking (no sector view)
Per-sector keyword groups with independent dashboards
One competitor set for the whole site
Up to 12 sector-specific competitors per vertical
Manual spreadsheets to segment by sector
Automatic sector attribution for every metric
Blended authority scores that hide sector gaps
Topical authority on 3 axes per vertical
Generic content gap analysis
Entity-level gaps per sector vs sector competitors
No per-sector revenue attribution
GA4 revenue mapped to sectors automatically
Monthly agency reports with sitewide averages
Daily sector-segmented intelligence pipeline
Manual CMS updates across sector pages
Auto-deploy approved changes to correct sector page
Multi-sector questions, direct answers.
Evaluating whether Korvex handles the complexity of a multi-sector business? Here’s what you need to know.
How does Korvex handle businesses serving 5+ sectors?
Every metric, score, and recommendation is segmented by sector from the ground up. Keyword groups, GA4 attribution, content gap analysis, competitor tracking, and topical authority are all sector-partitioned. You can monitor manufacturing independently from healthcare, financial services from energy. There is no practical limit to the number of sectors — each one gets its own dashboard, its own competitors, and its own authority scores.
Can we set different competitors per sector?
Yes. Each sector has its own competitor set — up to 12 competitors per vertical. In manufacturing, you might track Siemens and Honeywell. In healthcare, NHS Digital and Bupa. Korvex runs daily intelligence across all competitor sets simultaneously, so you see sector-specific competitive landscapes, not a single blended view.
How does per-sector revenue attribution work?
GA4 integration maps landing page groups to sectors. When a user lands on a manufacturing page, navigates to pricing, and converts, that revenue is attributed to the manufacturing sector. You see organic sessions, conversions, and revenue broken down by vertical — so you know which sectors drive business and which need investment.
What if we have cross-sector content that serves multiple verticals?
Cross-sector content (like a compliance management guide relevant to both manufacturing and healthcare) is tagged to all applicable sectors. Korvex tracks its performance contribution to each vertical independently. If that page ranks for manufacturing keywords and healthcare keywords, you see both contributions in the respective sector dashboards.
How does site architecture mapping work across sectors?
Korvex maps your hub/pillar structure per sector. Each vertical should have a hub page linking to pillar pages, which link to supporting content. The architecture analysis identifies orphaned pages, weak internal links, missing pillar coverage, and cross-sector linking opportunities. Health scores are calculated per sector hub.
Can the prediction model forecast per sector?
Yes. The XGBoost ensemble trains on sector-segmented data, producing 30/60/90-day forecasts per vertical. Seasonal patterns are detected per sector (manufacturing may spike differently from healthcare). Confidence intervals narrow as each sector accumulates more historical data. Accuracy: 91% portfolio average at 30 days.
How does CMS auto-publishing handle sector-specific content?
When you approve a recommendation on the kanban board, Korvex pushes the change to the correct CMS section. If it is a title rewrite on a manufacturing page, the WordPress/Shopify/Webflow API receives the change targeted at that specific page. Sector-specific schema markup, internal links, and entity enrichment are all handled automatically with rollback capability.
How long until we see per-sector intelligence?
Day 1: Sectors defined, keyword groups configured, GSC and GA4 data imported. Day 3: first per-sector recommendations generated with confidence scores. Day 7: sector-specific competitive analysis populated, entity graph built per vertical. Day 14: prediction model has enough sector-segmented data for initial forecasts. Day 30: closed-loop calibration active per sector, accuracy reaches 91%+.
Own every sector. Outrank every specialist.
14-day free trial. Full per-sector intelligence pipeline. 47-factor scoring, 18 hypothesis generators, entity knowledge graph, sector competitor tracking, and revenue attribution — all segmented by vertical from day one. No credit card required.
91% prediction accuracy · Per-sector intelligence · 74 automated overnight jobs