Local Visibility Scorecard — Canonical Rubric¶
Generated from
rubric.json. Do not edit this file by hand. Runpython3 render_rubric.py.
Version: 1.0.0 · Framework: local-discovery · Updated: 2026-10-27 · Total: 100
Evidence-based diagnosis of local discovery across Search, Maps, AI answers, competitors, and external authority
The seven categories¶
| Category | Weight | Question |
|---|---|---|
| A. Intent & Demand Coverage | 15 | Across the commercially meaningful things local customers search for, how broadly is this business visible? |
| B. Maps & Local Pack Visibility | 25 | How consistently does the business appear prominently in Google's local-business results throughout the target market? |
| C. Organic Search Visibility | 15 | How well does the business appear in ordinary Google search results for commercially relevant local intent? |
| D. AI & Generative Visibility | 20 | When prospective customers ask AI systems for local service recommendations, how often and how credibly does the business appear? |
| E. Competitive Share of Visibility | 10 | Relative to the actual businesses competing for the same local demand, what share of discovery does the business earn? |
| F. Authority & Entity Footprint | 10 | How strongly is the business corroborated across external sources that support discovery and recommendation? |
| G. Visibility Resilience | 5 | Is discoverability reasonably diversified, or does it depend on one fragile source of visibility? |
| Total | 100 |
Maps & Local Pack receives the highest weight because local-business results are the densest discovery surface for a home-service business. AI & Generative Visibility receives the second-highest weight because AI answers are now a real recommendation surface, but only validated surfaces contribute to the score.
Bands¶
| Score | Band | Label |
|---|---|---|
| 90–100 | A | Elite |
| 75–89 | B | Strong |
| 60–74 | C | Average |
| 40–59 | D | Weak |
| 0–39 | F | Critical |
Scoring model¶
For each category: normalized = category.max * earned / applicable_max. Total = sum(normalized) * 100 / sum(category.max for categories with applicable checks). Category caps apply to normalized category points; overall caps apply to the total. Final = min(total, overall cap).
Rounding. Category normalized values are rounded to 2 decimals. Total and final are rounded to 1 decimal. Display = final rounded to the nearest integer (half up). Bands use the display score.
Owner data. Owner-data questions are never scored and never reduce the public score.
Connected mode. Authorized Search Console, GA4, Google Ads, Bing, or client revenue data is reported separately and never silently rewrites the Public Mode score.
Evidence. Every applicable check needs evidence and confidence verified or strong_signal. A deterministic check must be verified.
Demand weighting. Each core service cluster receives equal cluster weight (1 / number of core service clusters). Within a cluster, intent weight is proportional to sqrt(max(search_volume,1)) and capped at 50% of the cluster weight before renormalization. This prevents a single head term from dominating the score.
Visibility index. For a query/surface observation, rank credit is 1.0 for rank 1-3, 0.7 for 4-10, 0.3 for 11-20, and 0 outside the top 20. Demand-weighted coverage is sum(weight * credit) / sum(weight) over applicable core queries. Top-N coverage counts a query when the best observed rank on that surface is at most N.
Geo-grid aggregation. A grid point is covered for an intent when the target appears in the top 10 at that point. Geo-grid consistency is the demand-weighted share of grid points covered across configured core Maps intents. Quadrant metrics split the grid into four geographic quadrants around the configured center.
AI aggregation. Each prompt-platform pair is observed R times. Mention, recommendation, and citation status for the pair is true when it appears in at least ceil(R/2) repeats. Repeat stability is the share of pairs where all repeats agree. Only validated consumer/search surfaces or validated model/API surfaces contribute to the core score. Source types are recorded separately and are never pooled.
Missing observations. A missing observation is reported as not collected, never as rank 0. If core coverage falls below a validity threshold, the run returns INSUFFICIENT EVIDENCE and no score is written.
Validity gates¶
A gate failure produces INSUFFICIENT EVIDENCE, not a low business score. NOT APPLICABLE is never used for a temporary provider failure.
| Gate | Threshold |
|---|---|
Artifact schema is valid (schema_valid) |
The audit validates against the V1 schema and its schema_version is known. |
Target business resolved (target_resolved) |
business.resolution.resolved is true and match confidence is at least 0.80. |
Query universe locked (query_universe_locked) |
query_universe.locked is true, a hash is present, and the hash matches the universe content. |
Market configuration matches the universe (market_match) |
Trade, market name, language, and device match between the audit and the query universe. |
Core query coverage (core_query_coverage) |
At least 80% of planned core queries are observed on each required core surface. |
Geo-grid coverage (grid_coverage) |
At least 80% of planned grid points are observed for each configured Maps surface. |
Validated AI surface available (ai_surface_availability) |
At least one validated AI surface has observations. |
AI repeat completeness (ai_repeat_completeness) |
At least 80% of planned prompt-platform-repeat observations are present. |
Competitor cohort locked (competitor_cohort_locked) |
competitors.locked is true and at least two business competitors are in the locked cohort. |
Authority data present (authority_data_present) |
At least one referring-domain or external listing observation is present. |
Provider error rate (provider_error_rate) |
The recorded provider error rate is at most 0.10. |
No critical source outage (critical_source_outage) |
No required core source is recorded as a critical outage. |
Check index¶
| ID | Title | Cat | Max | Severity | Evaluation | Applicability |
|---|---|---|---|---|---|---|
| LV-INT-01 | Core service clusters with any qualified visibility | A | 3 | high | deterministic | required |
| LV-INT-02 | Demand-weighted non-branded coverage | A | 3 | critical | deterministic | required |
| LV-INT-03 | High-commercial-intent coverage | A | 2 | high | deterministic | required |
| LV-INT-04 | Emergency or urgent intent coverage | A | 2 | high | deterministic | conditional (emergency_service) |
| LV-INT-05 | Service + city intent coverage | A | 2 | high | deterministic | conditional (city_modified_demand) |
| LV-INT-06 | Near-me intent coverage | A | 1 | medium | deterministic | conditional (near_me_demand) |
| LV-INT-07 | Problem and symptom intent coverage | A | 2 | medium | deterministic | required |
| LV-MAP-01 | Demand-weighted Local Pack Top-3 coverage | B | 3 | critical | deterministic | required |
| LV-MAP-02 | Local Pack Top-10 coverage | B | 3 | high | deterministic | required |
| LV-MAP-03 | Local Pack Top-20 coverage | B | 2 | medium | deterministic | required |
| LV-MAP-04 | Average visible Local Pack position | B | 2 | medium | deterministic | required |
| LV-MAP-05 | Google Maps Top-3 coverage | B | 3 | critical | deterministic | required |
| LV-MAP-06 | Google Maps Top-10 coverage | B | 2 | high | deterministic | required |
| LV-MAP-07 | Geo-grid consistency | B | 3 | high | deterministic | required |
| LV-MAP-08 | Service-specific Maps coverage | B | 3 | high | deterministic | required |
| LV-MAP-09 | Geographic gap severity | B | 2 | medium | deterministic | required |
| LV-MAP-10 | Local Finder coverage | B | 2 | medium | deterministic | conditional (local_finder_configured) |
| LV-ORG-01 | Demand-weighted organic Top-3 coverage | C | 3 | high | deterministic | required |
| LV-ORG-02 | Organic Top-10 coverage | C | 3 | high | deterministic | required |
| LV-ORG-03 | Organic Top-20 coverage | C | 2 | medium | deterministic | required |
| LV-ORG-04 | Demand-weighted ranking coverage | C | 2 | medium | deterministic | required |
| LV-ORG-05 | Ranking URL relevance to intent | C | 2 | high | model_judgment | required |
| LV-ORG-06 | City-modified organic coverage | C | 2 | medium | deterministic | conditional (city_modified_demand) |
| LV-ORG-07 | Service-cluster organic coverage | C | 1 | medium | deterministic | required |
| LV-AI-01 | AI mention coverage | D | 3 | critical | deterministic | required |
| LV-AI-02 | AI recommendation coverage | D | 3 | critical | deterministic | required |
| LV-AI-03 | AI citation and source coverage | D | 3 | high | deterministic | required |
| LV-AI-04 | Service relevance in AI answers | D | 2 | high | model_judgment | required |
| LV-AI-05 | Location relevance in AI answers | D | 2 | high | model_judgment | required |
| LV-AI-06 | Entity accuracy in AI answers | D | 1 | medium | model_judgment | required |
| LV-AI-07 | Competitive share of AI answers | D | 2 | medium | deterministic | required |
| LV-AI-08 | Prompt-intent coverage | D | 2 | high | deterministic | required |
| LV-AI-09 | AI repeat stability | D | 1 | medium | deterministic | required |
| LV-AI-10 | Validated AI surface breadth | D | 1 | medium | deterministic | required |
| LV-CMP-01 | Business-competitor share of Top-3 | E | 2 | high | deterministic | required |
| LV-CMP-02 | Business-competitor share of Top-10 | E | 2 | high | deterministic | required |
| LV-CMP-03 | Maps share of visibility | E | 1 | medium | deterministic | required |
| LV-CMP-04 | Organic share of visibility | E | 1 | medium | deterministic | required |
| LV-CMP-05 | AI recommendation share | E | 1 | medium | deterministic | required |
| LV-CMP-06 | Service-specific competitor gap | E | 2 | high | deterministic | required |
| LV-CMP-07 | Geographic competitor gap | E | 1 | medium | deterministic | required |
| LV-AUT-01 | Relevant referring domains | F | 2 | high | deterministic | required |
| LV-AUT-02 | Local source relevance | F | 2 | high | model_judgment | required |
| LV-AUT-03 | Industry, manufacturer, and trade sources | F | 2 | medium | deterministic | required |
| LV-AUT-04 | External listing and entity consistency | F | 2 | high | deterministic | required |
| LV-AUT-05 | Competitor authority gap | F | 1 | medium | deterministic | required |
| LV-AUT-06 | Authority overlap with AI citations | F | 1 | medium | deterministic | required |
| LV-RES-01 | Surface concentration | G | 1 | medium | deterministic | required |
| LV-RES-02 | Service concentration | G | 1 | medium | deterministic | required |
| LV-RES-03 | Geographic concentration | G | 1 | medium | deterministic | required |
| LV-RES-04 | Branded versus non-branded dependence | G | 1 | medium | deterministic | conditional (branded_diagnostics_enabled) |
| LV-RES-05 | Reproducible visibility trend | G | 1 | low | deterministic | conditional (historical_runs_available) |
Checks by category¶
A. Intent & Demand Coverage — 15 points¶
Across the commercially meaningful things local customers search for, how broadly is this business visible?
LV-INT-01 — Core service clusters with any qualified visibility (3 points)¶
Stage: search · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Breadth matters: a business can rank well for one service and be invisible for the rest of what it sells.
| Score | Anchor |
|---|---|
| 3 | At least 80% of core service clusters have a top-20 Maps/Pack or organic result, or an AI mention, somewhere in the market. |
| 2 | 50–79% of core service clusters have qualified visibility. |
| 1 | 25–49% of core service clusters have qualified visibility. |
| 0 | Fewer than 25% of core service clusters have qualified visibility. |
Evidence to capture: Core service clusters from the locked query universe and any qualified top-20 or AI-mention observation.
Recommended intervention: Prioritize the service clusters with no qualified visibility. Confirm the business actually sells them before treating the gap as a defect.
LV-INT-02 — Demand-weighted non-branded coverage (3 points)¶
Stage: search · Severity: critical · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: The score should reflect how much commercially meaningful demand is covered, not how many keywords were collected.
| Score | Anchor |
|---|---|
| 3 | Demand-weighted coverage is at least 75% of the core non-branded intent weight. |
| 2 | Demand-weighted coverage is 50–74%. |
| 1 | Demand-weighted coverage is 25–49%. |
| 0 | Demand-weighted coverage is below 25%. |
Evidence to capture: Demand-weighted share of core non-branded intents with any qualified visibility. Service clusters are equally weighted; within a cluster, no single intent may exceed 50% of the cluster weight.
Recommended intervention: Rebuild the content and entity strategy around the uncovered demand, starting with the highest-weight clusters. Do not optimize a head term at the expense of every other service.
LV-INT-03 — High-commercial-intent coverage (2 points)¶
Stage: search · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Commercial intent is where visibility is most likely to matter to the business.
| Score | Anchor |
|---|---|
| 2 | At least 70% of high-commercial intents have a top-10 result or AI mention on at least one core surface. |
| 1 | 35–69% of high-commercial intents have that visibility. |
| 0 | Fewer than 35% of high-commercial intents have that visibility. |
Evidence to capture: Share of intents classified commercial or transactional with a qualified top-10 or AI mention.
Recommended intervention: Focus the next content and profile work on the commercial intents that are absent.
LV-INT-04 — Emergency or urgent intent coverage (2 points)¶
Stage: search · Severity: high · Evaluation: deterministic · Applicability: conditional · condition: emergency_service · service mapping: market_intelligence
Principle: Urgent demand is often the highest-intent, highest-value demand a trade sells.
| Score | Anchor |
|---|---|
| 2 | At least 70% of emergency intents have a top-10 result or AI mention on at least one core surface. |
| 1 | 30–69% of emergency intents have that visibility. |
| 0 | Fewer than 30% of emergency intents have that visibility. |
Evidence to capture: Share of emergency and urgent intents with qualified visibility. Only scored when configuration.emergency_service is true.
Recommended intervention: Treat emergency visibility as a service-line decision: either build a credible urgent path or state that the business does not offer one.
LV-INT-05 — Service + city intent coverage (2 points)¶
Stage: search · Severity: high · Evaluation: deterministic · Applicability: conditional · condition: city_modified_demand · service mapping: market_intelligence
Principle: Service + city queries are how many local customers express intent.
| Score | Anchor |
|---|---|
| 2 | At least 70% of service + city intents have a top-20 Maps/Pack or organic result. |
| 1 | 30–69% of service + city intents have that visibility. |
| 0 | Fewer than 30% of service + city intents have that visibility. |
Evidence to capture: Share of city-modified service intents with qualified visibility. Only scored when configuration.city_modified_demand is true.
Recommended intervention: Create or improve the location-specific service pages and confirm the market is actually served.
LV-INT-06 — Near-me intent coverage (1 points)¶
Stage: search · Severity: medium · Evaluation: deterministic · Applicability: conditional · condition: near_me_demand · service mapping: market_intelligence
Principle: Near-me queries are the closest thing to a customer standing in the market and asking who is nearby.
| Score | Anchor |
|---|---|
| 1 | At least 50% of near-me intents have a top-10 Maps/Pack or organic result. |
| 0 | Fewer than 50% of near-me intents have that visibility. |
Evidence to capture: Share of near-me intents with qualified visibility. Only scored when configuration.near_me_demand is true.
Recommended intervention: Check proximity, service-area configuration, and the strength of the local entity footprint before adding pages.
LV-INT-07 — Problem and symptom intent coverage (2 points)¶
Stage: search · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Problem-led searches are how customers describe the job before they know the service name.
| Score | Anchor |
|---|---|
| 2 | At least 60% of problem/symptom intents have a top-20 organic result or AI mention. |
| 1 | 25–59% of problem/symptom intents have that visibility. |
| 0 | Fewer than 25% of problem/symptom intents have that visibility. |
Evidence to capture: Share of problem and symptom intents with qualified visibility.
Recommended intervention: Map content to the symptoms the business actually solves. Do not publish generic DIY content that cannot produce a service lead.
B. Maps & Local Pack Visibility — 25 points¶
How consistently does the business appear prominently in Google's local-business results throughout the target market?
LV-MAP-01 — Demand-weighted Local Pack Top-3 coverage (3 points)¶
Stage: discover · Severity: critical · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: The Local Pack is the most concentrated local-discovery surface. Top-3 presence is the practical visibility outcome.
| Score | Anchor |
|---|---|
| 3 | Demand-weighted Top-3 coverage in the Local Pack is at least 50%. |
| 2 | Demand-weighted Top-3 coverage is 25–49%. |
| 1 | Demand-weighted Top-3 coverage is 10–24%. |
| 0 | Demand-weighted Top-3 coverage is below 10%. |
Evidence to capture: Best Local Pack rank per core query across the grid; demand-weighted.
Recommended intervention: Investigate relevance, proximity, authority, service-area competition, and profile configuration. Cross-reference GBP Scorecard for profile diagnosis.
LV-MAP-02 — Local Pack Top-10 coverage (3 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Top-10 presence shows whether the business is a realistic option beyond a single lucky location.
| Score | Anchor |
|---|---|
| 3 | At least 70% of core Local Pack observations place the business in the top 10. |
| 2 | 45–69% place it in the top 10. |
| 1 | 20–44% place it in the top 10. |
| 0 | Fewer than 20% place it in the top 10. |
Evidence to capture: Share of core Local Pack query-grid observations with a top-10 target rank.
Recommended intervention: Look for the service and geographic clusters where the business disappears, not just the market average.
LV-MAP-03 — Local Pack Top-20 coverage (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A business absent from the top 20 is not a realistic local option on that surface.
| Score | Anchor |
|---|---|
| 2 | At least 80% of core Local Pack observations place the business in the top 20. |
| 1 | 50–79% place it in the top 20. |
| 0 | Fewer than 50% place it in the top 20. |
Evidence to capture: Share of core Local Pack query-grid observations with a top-20 target rank.
Recommended intervention: Prioritize complete absence over rank improvement. A missing entity is a different problem from a weak rank.
LV-MAP-04 — Average visible Local Pack position (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Average position adds texture that top-N coverage alone hides.
| Score | Anchor |
|---|---|
| 2 | The demand-weighted average visible Local Pack position is 3.0 or better. |
| 1 | The average visible position is between 3.1 and 7.0. |
| 0 | The average visible position is worse than 7.0, or the business is not visible. |
Evidence to capture: Demand-weighted average of the best Local Pack rank per core query. Missing observations are excluded from the average and counted by coverage checks.
Recommended intervention: Use this as context, not as the primary score. Coverage and geographic consistency are more robust.
LV-MAP-05 — Google Maps Top-3 coverage (3 points)¶
Stage: discover · Severity: critical · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Maps is a distinct surface from the Local Pack. Its ordering can differ and must not be silently merged.
| Score | Anchor |
|---|---|
| 3 | At least 50% of core Maps observations place the business in the top 3. |
| 2 | 25–49% place it in the top 3. |
| 1 | 10–24% place it in the top 3. |
| 0 | Fewer than 10% place it in the top 3. |
Evidence to capture: Share of core Google Maps query-grid observations with a top-3 target rank.
Recommended intervention: Diagnose Maps separately. Check proximity, category relevance, and geographic coverage before assuming a content problem.
LV-MAP-06 — Google Maps Top-10 coverage (2 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Top-10 Maps visibility is the threshold where a business is a plausible choice across the market.
| Score | Anchor |
|---|---|
| 2 | At least 70% of core Maps observations place the business in the top 10. |
| 1 | 40–69% place it in the top 10. |
| 0 | Fewer than 40% place it in the top 10. |
Evidence to capture: Share of core Google Maps query-grid observations with a top-10 target rank.
Recommended intervention: Compare Maps and Local Pack results. A gap between them is diagnostic, not noise.
LV-MAP-07 — Geo-grid consistency (3 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A single strong pin can hide a market-wide visibility gap. The grid measures consistency.
| Score | Anchor |
|---|---|
| 3 | At least 60% of grid points have a top-10 Maps result for at least one core Maps intent. |
| 2 | 35–59% of grid points are covered. |
| 1 | 15–34% of grid points are covered. |
| 0 | Fewer than 15% of grid points are covered. |
Evidence to capture: Share of configured grid points with a top-10 target result, demand-weighted across core Maps intents.
Recommended intervention: Use the grid and quadrant summary to find the areas where the business disappears. Do not average the gap away.
LV-MAP-08 — Service-specific Maps coverage (3 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A business can dominate one service in Maps and be absent from the services it wants to grow.
| Score | Anchor |
|---|---|
| 3 | At least 75% of core service clusters have 40% or better top-10 Maps coverage. |
| 2 | 50–74% of clusters meet that threshold. |
| 1 | 25–49% of clusters meet it. |
| 0 | Fewer than 25% of clusters meet it. |
Evidence to capture: Share of core service clusters whose Maps top-10 coverage is at least 40%.
Recommended intervention: Separate the strong service from the weak service in the report. The fix is usually service-specific, not market-wide.
LV-MAP-09 — Geographic gap severity (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: The weakest area is the clearest evidence of a geographic visibility gap.
| Score | Anchor |
|---|---|
| 2 | The weakest grid quadrant still has at least 40% top-10 Maps coverage. |
| 1 | The weakest quadrant has 15–39% coverage. |
| 0 | The weakest quadrant has less than 15% coverage. |
Evidence to capture: Top-10 Maps coverage in the weakest of the four grid quadrants.
Recommended intervention: Check whether the weak quadrant is actually served. If it is, investigate proximity and location-page coverage.
LV-MAP-10 — Local Finder coverage (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: conditional · condition: local_finder_configured · service mapping: market_intelligence
Principle: Local Finder can reveal a different ordering from the Local Pack and Maps.
| Score | Anchor |
|---|---|
| 2 | At least 60% of configured Local Finder observations place the business in the top 10. |
| 1 | 30–59% place it in the top 10. |
| 0 | Fewer than 30% place it in the top 10. |
Evidence to capture: Share of configured Local Finder observations with a top-10 target rank. Only scored when configuration.local_finder_configured is true.
Recommended intervention: Treat Local Finder as a separate observation. Do not merge it into the Maps rank.
C. Organic Search Visibility — 15 points¶
How well does the business appear in ordinary Google search results for commercially relevant local intent?
LV-ORG-01 — Demand-weighted organic Top-3 coverage (3 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Organic Top-3 visibility is rare and valuable for local commercial queries.
| Score | Anchor |
|---|---|
| 3 | Demand-weighted organic Top-3 coverage is at least 35%. |
| 2 | Demand-weighted Top-3 coverage is 15–34%. |
| 1 | Demand-weighted Top-3 coverage is 5–14%. |
| 0 | Demand-weighted Top-3 coverage is below 5%. |
Evidence to capture: Best organic rank per core query, demand-weighted.
Recommended intervention: Investigate the pages that rank, the intent match, and the authority gap. Cross-reference Website Scorecard for page quality.
LV-ORG-02 — Organic Top-10 coverage (3 points)¶
Stage: discover · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Top-10 organic presence is the practical threshold for non-branded discovery.
| Score | Anchor |
|---|---|
| 3 | At least 60% of core organic observations place the business in the top 10. |
| 2 | 35–59% place it in the top 10. |
| 1 | 15–34% place it in the top 10. |
| 0 | Fewer than 15% place it in the top 10. |
Evidence to capture: Share of core organic queries with a top-10 target rank.
Recommended intervention: Focus on the service clusters with no top-10 presence. Confirm a relevant page exists before recommending content.
LV-ORG-03 — Organic Top-20 coverage (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A business absent from the top 20 is not a realistic organic option for that intent.
| Score | Anchor |
|---|---|
| 2 | At least 75% of core organic observations place the business in the top 20. |
| 1 | 45–74% place it in the top 20. |
| 0 | Fewer than 45% place it in the top 20. |
Evidence to capture: Share of core organic queries with a top-20 target rank.
Recommended intervention: Prioritize complete absence over marginal rank movement.
LV-ORG-04 — Demand-weighted ranking coverage (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Rank credit captures partial visibility that top-N coverage alone does not.
| Score | Anchor |
|---|---|
| 2 | The demand-weighted rank credit is at least 0.60. |
| 1 | Rank credit is 0.30–0.59. |
| 0 | Rank credit is below 0.30. |
Evidence to capture: Rank credit: 1.0 for top 3, 0.7 for 4–10, 0.3 for 11–20, 0 outside the top 20; demand-weighted across core organic queries.
Recommended intervention: Use coverage bands for the primary diagnosis and rank credit as supporting context.
LV-ORG-05 — Ranking URL relevance to intent (2 points)¶
Stage: discover · Severity: high · Evaluation: model_judgment · Applicability: required · requires: organic_target_observations · service mapping: market_intelligence
Principle: A ranking for the wrong page can look like visibility while failing the customer.
| Score | Anchor |
|---|---|
| 2 | Every observed ranking URL is a dedicated page that matches the service and intent. |
| 1 | Some rankings use a generic home page or a page that only partially matches the intent. |
| 0 | Rankings are dominated by unrelated pages or a page that does not represent the service. |
Evidence to capture: The ranking URL, its path or title, and the tracked intent. The reviewer judges relevance; the scorecard does not audit the page itself.
Recommended intervention: Map each commercial intent to a page that genuinely serves it. Do not score page speed, forms, or UX here; those belong to Website Scorecard.
LV-ORG-06 — City-modified organic coverage (2 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: conditional · condition: city_modified_demand · service mapping: market_intelligence
Principle: City-modified queries show whether the business is visible in the places it claims to serve.
| Score | Anchor |
|---|---|
| 2 | At least 70% of city-modified organic queries have a top-20 target rank. |
| 1 | 30–69% have that visibility. |
| 0 | Fewer than 30% have that visibility. |
Evidence to capture: Share of city-modified organic queries with a top-20 target. Only scored when configuration.city_modified_demand is true.
Recommended intervention: Check location-page coverage and the market configuration before adding pages.
LV-ORG-07 — Service-cluster organic coverage (1 points)¶
Stage: discover · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Portfolio coverage prevents one strong service from hiding an organic gap in the rest of the business.
| Score | Anchor |
|---|---|
| 1 | At least 60% of core service clusters have 30% or better top-10 organic coverage. |
| 0 | Fewer than 60% of service clusters meet that threshold. |
Evidence to capture: Share of core service clusters with at least 30% top-10 organic coverage.
Recommended intervention: Use the cluster view to decide whether the organic gap is service-specific or market-wide.
D. AI & Generative Visibility — 20 points¶
When prospective customers ask AI systems for local service recommendations, how often and how credibly does the business appear?
LV-AI-01 — AI mention coverage (3 points)¶
Stage: ask · Severity: critical · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Mention is the first threshold of AI visibility. It is not the same as a recommendation.
| Score | Anchor |
|---|---|
| 3 | The target is mentioned in at least 60% of validated prompt-platform pairs (majority of repeats). |
| 2 | The target is mentioned in 35–59% of pairs. |
| 1 | The target is mentioned in 15–34% of pairs. |
| 0 | The target is mentioned in fewer than 15% of pairs. |
Evidence to capture: Share of validated prompt-platform pairs where the target is mentioned in at least half of repeats.
Recommended intervention: Analyze the prompt intents and surfaces where the business is absent. Distinguish mention from recommendation before prescribing a fix.
LV-AI-02 — AI recommendation coverage (3 points)¶
Stage: ask · Severity: critical · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A mention inside a directory list is not the same as a recommendation.
| Score | Anchor |
|---|---|
| 3 | The target is recommended in at least 40% of validated prompt-platform pairs. |
| 2 | The target is recommended in 20–39% of pairs. |
| 1 | The target is recommended in 5–19% of pairs. |
| 0 | The target is recommended in fewer than 5% of pairs. |
Evidence to capture: Share of validated prompt-platform pairs where the target is recommended, not merely mentioned, in at least half of repeats.
Recommended intervention: Analyze the citation and corroboration ecosystem, not just content. A recommendation usually depends on third-party evidence.
LV-AI-03 — AI citation and source coverage (3 points)¶
Stage: ask · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Being named is weaker than being the cited source. The distinction predicts durable AI visibility.
| Score | Anchor |
|---|---|
| 3 | The target's domain or entity is cited in at least 35% of validated prompt-platform pairs. |
| 2 | The target is cited in 15–34% of pairs. |
| 1 | The target is cited in 5–14% of pairs. |
| 0 | The target is cited in fewer than 5% of pairs. |
Evidence to capture: Share of validated prompt-platform pairs where the target's domain or entity is cited as a source, in at least half of repeats.
Recommended intervention: Build citable, source-worthy content and third-party corroboration. Do not claim a citation you cannot observe.
LV-AI-04 — Service relevance in AI answers (2 points)¶
Stage: ask · Severity: high · Evaluation: model_judgment · Applicability: required · requires: ai_target_observations · service mapping: market_intelligence
Principle: AI answers can mention a business for the wrong service, which can create misleading visibility.
| Score | Anchor |
|---|---|
| 2 | Every observed mention or recommendation is for the relevant service and the customer's stated problem. |
| 1 | Some mentions are generic, adjacent-service, or only loosely relevant. |
| 0 | Mentions are off-service or do not address the customer's problem. |
Evidence to capture: The AI answer text, the prompt intent, and the configured service cluster.
Recommended intervention: If relevance is weak, investigate entity ambiguity and content-to-intent mismatch. Do not treat the mention as a win.
LV-AI-05 — Location relevance in AI answers (2 points)¶
Stage: ask · Severity: high · Evaluation: model_judgment · Applicability: required · requires: ai_target_observations · service mapping: market_intelligence
Principle: A recommendation for a business outside the customer's market is not local visibility.
| Score | Anchor |
|---|---|
| 2 | Every mention or recommendation places the business in the target market. |
| 1 | Some mentions are ambiguous, broader than the market, or only partially local. |
| 0 | Mentions are for another market or do not establish local relevance. |
Evidence to capture: The AI answer text, the configured market, and the observed location context.
Recommended intervention: Clarify the service area and entity location. Cross-reference GBP Scorecard for location configuration.
LV-AI-06 — Entity accuracy in AI answers (1 points)¶
Stage: ask · Severity: medium · Evaluation: model_judgment · Applicability: required · requires: ai_target_observations · service mapping: market_intelligence
Principle: An AI answer that confuses the business with another entity can harm trust and send the wrong customer.
| Score | Anchor |
|---|---|
| 1 | Name, domain, phone, and service identity are accurate wherever observed. |
| 0 | A material identity error appears in an AI answer. |
Evidence to capture: The AI answer text and the resolved business identity.
Recommended intervention: Correct the underlying entity footprint and cross-reference GBP Scorecard identity checks. Do not edit an AI answer directly.
LV-AI-07 — Competitive share of AI answers (2 points)¶
Stage: ask · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Share of answer is more informative than an isolated mention.
| Score | Anchor |
|---|---|
| 2 | The target earns at least 25% of business-competitor recommendations in validated AI answers. |
| 1 | The target earns 10–24%. |
| 0 | The target earns less than 10%. |
Evidence to capture: Target recommendations divided by target plus locked business-competitor recommendations, demand-weighted. Directories and publishers are excluded from the competitor denominator.
Recommended intervention: Compare the sources AI systems cite for the competitors. The gap is usually corroboration, not prompt wording.
LV-AI-08 — Prompt-intent coverage (2 points)¶
Stage: ask · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: AI visibility should be measured across the demand model, not one convenient prompt.
| Score | Anchor |
|---|---|
| 2 | At least 60% of canonical prompt intents have a mention or recommendation on at least one validated surface. |
| 1 | 30–59% of prompt intents have that visibility. |
| 0 | Fewer than 30% of prompt intents have that visibility. |
Evidence to capture: Share of canonical prompt intents with at least one mention or recommendation across validated surfaces.
Recommended intervention: Expand prompt coverage and investigate the intents where the business never appears.
LV-AI-09 — AI repeat stability (1 points)¶
Stage: ask · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: AI answers vary. A score that hides the variance is less trustworthy than one that reports it.
| Score | Anchor |
|---|---|
| 1 | At least 80% of prompt-platform pairs have consistent mention status across all repeats. |
| 0 | Fewer than 80% of pairs are consistent. |
Evidence to capture: Share of prompt-platform pairs where every repeat agrees on whether the target was mentioned.
Recommended intervention: Increase repeats before drawing a conclusion. Report unstable prompts separately.
LV-AI-10 — Validated AI surface breadth (1 points)¶
Stage: ask · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A single AI surface is a fragile visibility source.
| Score | Anchor |
|---|---|
| 1 | The target is mentioned on at least 50% of validated AI surfaces with observations. |
| 0 | The target is mentioned on fewer than 50% of validated surfaces. |
Evidence to capture: Share of validated AI surfaces where the target appears at least once. Surfaces are never pooled across source_type.
Recommended intervention: Distinguish consumer/search surfaces from model/API surfaces in the report. Do not treat them as equivalent.
E. Competitive Share of Visibility — 10 points¶
Relative to the actual businesses competing for the same local demand, what share of discovery does the business earn?
LV-CMP-01 — Business-competitor share of Top-3 (2 points)¶
Stage: compare · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: Share of visibility relative to real local competitors is more meaningful than an absolute rank.
| Score | Anchor |
|---|---|
| 2 | The target earns at least 25% of business-competitor Top-3 appearances across core Maps/Pack/organic observations. |
| 1 | The target earns 10–24%. |
| 0 | The target earns less than 10%. |
Evidence to capture: Target Top-3 appearances divided by target plus locked business-competitor Top-3 appearances.
Recommended intervention: Identify the competitors winning the appearances and the surfaces where they win. Do not count directories as contractors.
LV-CMP-02 — Business-competitor share of Top-10 (2 points)¶
Stage: compare · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: Top-10 share shows whether the business is a consistent option, not a one-query exception.
| Score | Anchor |
|---|---|
| 2 | The target earns at least 25% of business-competitor Top-10 appearances. |
| 1 | The target earns 10–24%. |
| 0 | The target earns less than 10%. |
Evidence to capture: Target Top-10 appearances divided by target plus locked business-competitor Top-10 appearances.
Recommended intervention: Compare service by service. A market-wide average can hide a single-service collapse.
LV-CMP-03 — Maps share of visibility (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: Maps share isolates the local surface from organic and AI.
| Score | Anchor |
|---|---|
| 1 | The target earns at least 25% of business-competitor Maps appearances. |
| 0 | The target earns less than 25%. |
Evidence to capture: Target Maps appearances divided by target plus business-competitor Maps appearances.
Recommended intervention: If Maps share is weak, investigate proximity and local relevance before content.
LV-CMP-04 — Organic share of visibility (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: Organic share isolates search-result visibility from Maps and AI.
| Score | Anchor |
|---|---|
| 1 | The target earns at least 20% of business-competitor organic appearances. |
| 0 | The target earns less than 20%. |
Evidence to capture: Target organic appearances divided by target plus business-competitor organic appearances.
Recommended intervention: If organic share is weak, investigate page-to-intent coverage and authority.
LV-CMP-05 — AI recommendation share (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: AI share shows whether recommendation behavior is concentrated or shared.
| Score | Anchor |
|---|---|
| 1 | The target earns at least 20% of business-competitor recommendations in validated AI answers. |
| 0 | The target earns less than 20%. |
Evidence to capture: Target AI recommendations divided by target plus business-competitor recommendations.
Recommended intervention: Compare the cited sources. AI recommendations often follow corroboration, not direct optimization.
LV-CMP-06 — Service-specific competitor gap (2 points)¶
Stage: compare · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: Aggregate share can hide a service where the business is structurally behind.
| Score | Anchor |
|---|---|
| 2 | The target meets or beats the cohort median top-10 share in at least 75% of core service clusters. |
| 1 | The target meets the median in 40–74% of clusters. |
| 0 | The target meets the median in fewer than 40% of clusters. |
Evidence to capture: Per-service comparison against the locked business-competitor cohort median.
Recommended intervention: Prioritize the clusters where the gap is largest and the service matters commercially.
LV-CMP-07 — Geographic competitor gap (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: marketing_intelligence
Principle: A competitor can dominate one part of the market while the market average looks acceptable.
| Score | Anchor |
|---|---|
| 1 | The target meets or beats the cohort median top-10 Maps coverage in at least half of the grid quadrants. |
| 0 | The target meets the median in fewer than half of the quadrants. |
Evidence to capture: Per-quadrant target coverage compared with the locked cohort median.
Recommended intervention: Use the quadrant comparison to decide whether the gap is geographic or service-specific.
F. Authority & Entity Footprint — 10 points¶
How strongly is the business corroborated across external sources that support discovery and recommendation?
LV-AUT-01 — Relevant referring domains (2 points)¶
Stage: compare · Severity: high · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Relevant corroboration matters more than raw link quantity.
| Score | Anchor |
|---|---|
| 2 | At least 8 relevant referring domains (local, industry, manufacturer, trade, or association). |
| 1 | 3–7 relevant referring domains. |
| 0 | Fewer than 3 relevant referring domains. |
Evidence to capture: Count of referring domains classified as locally or industrially relevant. Generic low-value directories are excluded.
Recommended intervention: Pursue a small number of genuinely relevant local, manufacturer, trade, or association sources. Do not buy generic directory links.
LV-AUT-02 — Local source relevance (2 points)¶
Stage: compare · Severity: high · Evaluation: model_judgment · Applicability: required · service mapping: market_intelligence
Principle: A local business needs local corroboration, not just links from anywhere.
| Score | Anchor |
|---|---|
| 2 | Multiple current local sources corroborate the business as a local operator. |
| 1 | One meaningful local source, or several low-relevance local directories, corroborate it. |
| 0 | No meaningful local corroboration is observable. |
Evidence to capture: The referring domains, listing sources, and their local relevance. The reviewer classifies source relevance.
Recommended intervention: Build relationships with local organizations, publications, and trade sources. Do not treat a generic directory as local proof.
LV-AUT-03 — Industry, manufacturer, and trade sources (2 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Trade-specific corroboration supports both search and AI recommendation.
| Score | Anchor |
|---|---|
| 2 | At least 4 industry, manufacturer, dealer, trade-association, or trade-publication sources. |
| 1 | 1–3 such sources. |
| 0 | No such sources are observed. |
Evidence to capture: Count of industry and trade sources in the referring-domain and listing observations.
Recommended intervention: Pursue manufacturer/dealer listings, trade associations, and credible trade publications where the business qualifies.
LV-AUT-04 — External listing and entity consistency (2 points)¶
Stage: compare · Severity: high · Evaluation: deterministic · Applicability: required · requires: listing_observations · service mapping: market_intelligence
Principle: Inconsistent entity data weakens both local search and AI entity resolution.
| Score | Anchor |
|---|---|
| 2 | At least 80% of observed external listings agree on name, domain, phone, and service category. |
| 1 | 50–79% agree. |
| 0 | Fewer than 50% agree. |
Evidence to capture: Share of observed listings with consistent name, domain, phone, and service category.
Recommended intervention: Correct the highest-authority inconsistent listings first. Cross-reference GBP Scorecard for the primary profile.
LV-AUT-05 — Competitor authority gap (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: Authority is relative. A number without a local comparison is not actionable.
| Score | Anchor |
|---|---|
| 1 | Relevant referring domains meet or exceed the locked cohort median. |
| 0 | Relevant referring domains are below the cohort median. |
Evidence to capture: Target relevant referring domains compared with the locked business-competitor cohort median.
Recommended intervention: Compare the sources the leading competitors have that the business does not. Prioritize relevance over volume.
LV-AUT-06 — Authority overlap with AI citations (1 points)¶
Stage: compare · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: AI answers cite sources. If the business is absent from the sources the market relies on, recommendation visibility is fragile.
| Score | Anchor |
|---|---|
| 1 | At least 25% of the target's relevant authority domains also appear as citation domains in the observed AI answer ecosystem. |
| 0 | Fewer than 25% overlap. |
Evidence to capture: Overlap between relevant referring domains and the domains cited in validated AI observations.
Recommended intervention: Prioritize sources that both corroborate the entity and appear in AI citations.
G. Visibility Resilience — 5 points¶
Is discoverability reasonably diversified, or does it depend on one fragile source of visibility?
LV-RES-01 — Surface concentration (1 points)¶
Stage: resilience · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A business that depends on one surface is fragile even when that surface is strong.
| Score | Anchor |
|---|---|
| 1 | The Herfindahl index of visibility appearances across Maps/Pack, organic, and AI is 0.55 or lower. |
| 0 | The Herfindahl index is above 0.55. |
Evidence to capture: Surface HHI computed from target appearances across core surfaces. Lower values indicate more diversified discovery.
Recommended intervention: Do not weaken a strong surface. Build a second surface as insurance and report the concentration explicitly.
LV-RES-02 — Service concentration (1 points)¶
Stage: resilience · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: One-service visibility is a business risk, not only an SEO risk.
| Score | Anchor |
|---|---|
| 1 | The Herfindahl index of visibility across core service clusters is 0.50 or lower. |
| 0 | The Herfindahl index is above 0.50. |
Evidence to capture: Service HHI computed from demand-weighted target visibility across service clusters.
Recommended intervention: Decide whether the concentration is intentional. If not, build visibility for the next most important service.
LV-RES-03 — Geographic concentration (1 points)¶
Stage: resilience · Severity: medium · Evaluation: deterministic · Applicability: required · service mapping: market_intelligence
Principle: A business visible in one corner of its market may not be visible across the market it claims.
| Score | Anchor |
|---|---|
| 1 | The Herfindahl index of top-10 Maps coverage across the four grid quadrants is 0.50 or lower. |
| 0 | The Herfindahl index is above 0.50. |
Evidence to capture: Geographic HHI computed from top-10 coverage across the four grid quadrants.
Recommended intervention: Check whether the concentration matches the service area. If not, investigate proximity and location coverage.
LV-RES-04 — Branded versus non-branded dependence (1 points)¶
Stage: resilience · Severity: medium · Evaluation: deterministic · Applicability: conditional · condition: branded_diagnostics_enabled · service mapping: market_intelligence
Principle: Strong branded visibility can mask weak non-branded discovery.
| Score | Anchor |
|---|---|
| 1 | Branded appearances are 20% or less of total observed search appearances. |
| 0 | Branded appearances are more than 20% of total appearances. |
Evidence to capture: Share of branded visibility among all observed search appearances. Branded queries are diagnostic and never inflate the core score. Only scored when configuration.branded_diagnostics_enabled is true.
Recommended intervention: Separate branded from non-branded demand in every report. Do not let branded rank inflate the core score.
LV-RES-05 — Reproducible visibility trend (1 points)¶
Stage: resilience · Severity: low · Evaluation: deterministic · Applicability: conditional · condition: historical_runs_available · service mapping: market_intelligence
Principle: A trend is useful only when the comparison is reproducible.
| Score | Anchor |
|---|---|
| 1 | The current demand-weighted visibility index is within 10% of the prior comparable run, or has improved. |
| 0 | The visibility index has declined by more than 10% against a comparable prior run. |
Evidence to capture: Demand-weighted visibility index compared with a prior run that used a comparable query universe and grid. Only scored when configuration.historical_runs_available is true and a comparable run is supplied.
Recommended intervention: Investigate lost visibility by surface and service. Do not invent a trend when the prior run is not comparable.
Hard caps¶
A cap is exceptional. V1 carries one. It exists only where an observable discovery failure can invalidate the rest of the diagnosis, and only when the run has sufficient valid evidence.
| Cap | Scope | Cap | Deterministic trigger | Rationale |
|---|---|---|---|---|
No qualified non-branded discovery (no_non_branded_discovery) |
overall | 25 | non_branded_discovery_present = False | If the business has zero qualified presence across every required core non-branded discovery surface, despite sufficient valid evidence, it cannot be discovered for the demand it sells. The score is capped in the Critical band. This is the only V1 cap. |
The verifier recomputes the trigger from facts and fails if the cap is active but undisclosed.
Journey stages¶
| # | Stage | Coverage | Customer question | Checks | Owner data |
|---|---|---|---|---|---|
| 1 | Search | scored | When a local customer searches for the service, does the business appear across the demand it sells? | LV-INT-01, LV-INT-02, LV-INT-03, LV-INT-04, LV-INT-05, LV-INT-06, LV-INT-07 | OD-LV-GSC-CLICKS, OD-LV-GSC-CTR, OD-LV-PRIORITY-SERVICES |
| 2 | Discover | scored | Does the business appear in Maps, the Local Pack, and ordinary organic results throughout the market? | LV-MAP-01, LV-MAP-02, LV-MAP-03, LV-MAP-04, LV-MAP-05, LV-MAP-06, LV-MAP-07, LV-MAP-08, LV-MAP-09, LV-MAP-10, LV-ORG-01, LV-ORG-02, LV-ORG-03, LV-ORG-04, LV-ORG-05, LV-ORG-06, LV-ORG-07 | — |
| 3 | Ask | scored | When a customer asks an AI system for a recommendation, is the business mentioned, recommended, and cited? | LV-AI-01, LV-AI-02, LV-AI-03, LV-AI-04, LV-AI-05, LV-AI-06, LV-AI-07, LV-AI-08, LV-AI-09, LV-AI-10 | OD-LV-AI-REFERRALS, OD-LV-AI-LEADS |
| 4 | Compare | scored | How does the business's share of discovery compare with real local competitors and credible external sources? | LV-CMP-01, LV-CMP-02, LV-CMP-03, LV-CMP-04, LV-CMP-05, LV-CMP-06, LV-CMP-07, LV-AUT-01, LV-AUT-02, LV-AUT-03, LV-AUT-04, LV-AUT-05, LV-AUT-06 | OD-LV-ORGANIC-LEADS, OD-LV-ORGANIC-REVENUE |
| 5 | Resilience | scored | Would the business still be discoverable if one surface, service, or area weakened? | LV-RES-01, LV-RES-02, LV-RES-03, LV-RES-04, LV-RES-05 | OD-LV-LOCAL-SEARCH-REVENUE |
| 6 | Handoff | observed_unscored | When the customer chooses the business, do the Google Business Profile and owned website create trust and convert? | — | — |
| 7 | Measure | owner_data_required | Can discovery-origin demand be tied to qualified leads, jobs, and revenue? | — | OD-LV-PAID-ROI |
Owner-data questions (never scored)¶
These questions require Search Console, analytics, CRM, phone, booking, or financial data. They do not reduce the public score.
| ID | Stage | Question | Why it matters |
|---|---|---|---|
| OD-LV-GSC-CLICKS | search | Search Console clicks by query cluster | Public SERP observation shows where the business appears; Search Console shows whether those impressions produced clicks. |
| OD-LV-GSC-CTR | search | Search Console CTR and average position | A ranking can be visible and still be ignored. CTR and position separate a ranking problem from a result-quality problem. |
| OD-LV-PRIORITY-SERVICES | search | Priority services by gross profit | The audit measures visibility across the configured services. The owner knows which services deserve disproportionate attention. |
| OD-LV-ORGANIC-LEADS | compare | Qualified leads from non-branded organic search | Visibility is not the same as qualified demand. Only the owner can show whether an organic visit became a real lead. |
| OD-LV-ORGANIC-REVENUE | compare | Revenue from organic discovery | A visibility gap matters more when the affected service produces meaningful revenue. |
| OD-LV-AI-REFERRALS | ask | AI referral traffic | A mention in an AI answer may or may not produce a visit. Referral data is the only public-adjacent way to see the handoff. |
| OD-LV-AI-LEADS | ask | AI-origin leads and jobs | Being recommended by an AI system is not proof that the recommendation becomes a customer. |
| OD-LV-LOCAL-SEARCH-REVENUE | resilience | Revenue concentration by service and area | A diversified visibility profile only matters if the underlying revenue is also diversified. |
| OD-LV-PAID-ROI | measure | Paid discovery return | Paid search and Local Services Ads are optional discovery channels. Their absence never lowers the public score. |
Opportunity flags (never scored)¶
An optional service is never the reason a business loses points.
| Flag | Service mapping | Why it may matter |
|---|---|---|
| Paid search coverage | marketing_intelligence |
Paid search can cover high-intent demand that organic and Maps visibility do not reach, but its absence is never a score penalty. |
| Local Services Ads | marketing_intelligence |
Local Services Ads can place a home-service business above the Local Pack for urgent demand. |
| Bing and secondary search coverage | market_intelligence |
Secondary engines can be a low-cost incremental discovery surface for some local trades. |
| Apple Maps presence | market_intelligence |
iPhone users may discover a local business outside Google. |
| Bing Maps presence | market_intelligence |
Bing Maps and Bing local results can corroborate the same entity. |
| Nextdoor and neighborhood presence | marketing_intelligence |
Neighborhood recommendations can matter for service-area businesses. |
| Yelp and marketplace profile | marketing_intelligence |
Some markets and trades see meaningful discovery through marketplaces even when they are not the primary surface. |
| YouTube and video discovery | market_intelligence |
Video can occupy SERP features and corroborate the work a business claims to do. |
| Local sponsorship and community presence | market_intelligence |
Local sponsorships can create relevant local citations and entity corroboration. |
| Manufacturer or dealer directory | market_intelligence |
A relevant manufacturer or dealer listing can be a strong, trade-specific corroborating source. |
| Local media and PR | market_intelligence |
Credible local publications can strengthen the entity footprint and AI citation ecosystem. |
| AI citation-source development | market_intelligence |
AI answers cite sources. Relevant, citable content and third-party corroboration can improve the chance of being referenced. |
| New service-area market | market_intelligence |
The audit may reveal a geographic visibility gap that is better addressed by a deliberate market decision than by more content. |
| Service and location content expansion | market_intelligence |
Organic and AI visibility can be limited by the absence of pages that match the tracked intent. |
Cross-scorecard ownership¶
| Question | Local Visibility | GBP Scorecard | Website Scorecard |
|---|---|---|---|
| Local Pack rank | SCORE | explanatory only | — |
| Google Maps rank | SCORE | explanatory only | — |
| Geo-grid visibility | SCORE | — | — |
| Organic rank and ranking URL | SCORE | — | explanatory only |
| AI mention, recommendation, and citation | SCORE | — | — |
| Competitor share of visibility | SCORE | — | — |
| Relevant referring domains and external corroboration | SCORE | — | — |
| GBP category quality | explanatory only | SCORE | — |
| GBP services, hours, attributes, photos | explanatory only | SCORE | — |
| GBP reviews and owner responses | — | SCORE | — |
| GBP phone, website, booking, or messaging action | — | SCORE | — |
| GBP-to-website handoff | — | SCORE | — |
| Page speed and mobile UX | — | — | SCORE |
| Website forms, CTA usability, booking flow | — | — | SCORE |
| On-site schema and technical implementation | — | — | SCORE |
| Website conversion tracking | — | — | SCORE |
| Review widget on website | — | — | SCORE |
| Paid search or Local Services Ads presence | diagnostic, never scored | — | — |
| Branded search visibility | diagnostic, never scored | — | — |
| Search Console clicks, calls, leads, revenue | OWNER DATA REQUIRED | OWNER DATA REQUIRED | OWNER DATA REQUIRED |
The same defect is not scored by two scorecards in one engagement. Local Visibility may identify which URL ranks; it does not score whether that page converts.
Fix mapping¶
Each check has a deterministic fix mapping in rubric.json. A mapping is metadata, not a sales recommendation.
| Check | Priority | Fix | Service mapping |
|---|---|---|---|
| LV-INT-01 | high | Prioritize the service clusters with no qualified visibility. Confirm the business actually sells them before treating the gap as a defect. | market_intelligence |
| LV-INT-02 | critical | Rebuild the content and entity strategy around the uncovered demand, starting with the highest-weight clusters. Do not optimize a head term at the expense of every other service. | market_intelligence |
| LV-INT-03 | high | Focus the next content and profile work on the commercial intents that are absent. | market_intelligence |
| LV-INT-04 | high | Treat emergency visibility as a service-line decision: either build a credible urgent path or state that the business does not offer one. | market_intelligence |
| LV-INT-05 | high | Create or improve the location-specific service pages and confirm the market is actually served. | market_intelligence |
| LV-INT-06 | medium | Check proximity, service-area configuration, and the strength of the local entity footprint before adding pages. | market_intelligence |
| LV-INT-07 | medium | Map content to the symptoms the business actually solves. Do not publish generic DIY content that cannot produce a service lead. | market_intelligence |
| LV-MAP-01 | critical | Investigate relevance, proximity, authority, service-area competition, and profile configuration. Cross-reference GBP Scorecard for profile diagnosis. | market_intelligence |
| LV-MAP-02 | high | Look for the service and geographic clusters where the business disappears, not just the market average. | market_intelligence |
| LV-MAP-03 | medium | Prioritize complete absence over rank improvement. A missing entity is a different problem from a weak rank. | market_intelligence |
| LV-MAP-04 | medium | Use this as context, not as the primary score. Coverage and geographic consistency are more robust. | market_intelligence |
| LV-MAP-05 | critical | Diagnose Maps separately. Check proximity, category relevance, and geographic coverage before assuming a content problem. | market_intelligence |
| LV-MAP-06 | high | Compare Maps and Local Pack results. A gap between them is diagnostic, not noise. | market_intelligence |
| LV-MAP-07 | high | Use the grid and quadrant summary to find the areas where the business disappears. Do not average the gap away. | market_intelligence |
| LV-MAP-08 | high | Separate the strong service from the weak service in the report. The fix is usually service-specific, not market-wide. | market_intelligence |
| LV-MAP-09 | medium | Check whether the weak quadrant is actually served. If it is, investigate proximity and location-page coverage. | market_intelligence |
| LV-MAP-10 | medium | Treat Local Finder as a separate observation. Do not merge it into the Maps rank. | market_intelligence |
| LV-ORG-01 | high | Investigate the pages that rank, the intent match, and the authority gap. Cross-reference Website Scorecard for page quality. | market_intelligence |
| LV-ORG-02 | high | Focus on the service clusters with no top-10 presence. Confirm a relevant page exists before recommending content. | market_intelligence |
| LV-ORG-03 | medium | Prioritize complete absence over marginal rank movement. | market_intelligence |
| LV-ORG-04 | medium | Use coverage bands for the primary diagnosis and rank credit as supporting context. | market_intelligence |
| LV-ORG-05 | high | Map each commercial intent to a page that genuinely serves it. Do not score page speed, forms, or UX here; those belong to Website Scorecard. | market_intelligence |
| LV-ORG-06 | medium | Check location-page coverage and the market configuration before adding pages. | market_intelligence |
| LV-ORG-07 | medium | Use the cluster view to decide whether the organic gap is service-specific or market-wide. | market_intelligence |
| LV-AI-01 | critical | Analyze the prompt intents and surfaces where the business is absent. Distinguish mention from recommendation before prescribing a fix. | market_intelligence |
| LV-AI-02 | critical | Analyze the citation and corroboration ecosystem, not just content. A recommendation usually depends on third-party evidence. | market_intelligence |
| LV-AI-03 | high | Build citable, source-worthy content and third-party corroboration. Do not claim a citation you cannot observe. | market_intelligence |
| LV-AI-04 | high | If relevance is weak, investigate entity ambiguity and content-to-intent mismatch. Do not treat the mention as a win. | market_intelligence |
| LV-AI-05 | high | Clarify the service area and entity location. Cross-reference GBP Scorecard for location configuration. | market_intelligence |
| LV-AI-06 | medium | Correct the underlying entity footprint and cross-reference GBP Scorecard identity checks. Do not edit an AI answer directly. | market_intelligence |
| LV-AI-07 | medium | Compare the sources AI systems cite for the competitors. The gap is usually corroboration, not prompt wording. | market_intelligence |
| LV-AI-08 | high | Expand prompt coverage and investigate the intents where the business never appears. | market_intelligence |
| LV-AI-09 | medium | Increase repeats before drawing a conclusion. Report unstable prompts separately. | market_intelligence |
| LV-AI-10 | medium | Distinguish consumer/search surfaces from model/API surfaces in the report. Do not treat them as equivalent. | market_intelligence |
| LV-CMP-01 | high | Identify the competitors winning the appearances and the surfaces where they win. Do not count directories as contractors. | marketing_intelligence |
| LV-CMP-02 | high | Compare service by service. A market-wide average can hide a single-service collapse. | marketing_intelligence |
| LV-CMP-03 | medium | If Maps share is weak, investigate proximity and local relevance before content. | marketing_intelligence |
| LV-CMP-04 | medium | If organic share is weak, investigate page-to-intent coverage and authority. | marketing_intelligence |
| LV-CMP-05 | medium | Compare the cited sources. AI recommendations often follow corroboration, not direct optimization. | marketing_intelligence |
| LV-CMP-06 | high | Prioritize the clusters where the gap is largest and the service matters commercially. | marketing_intelligence |
| LV-CMP-07 | medium | Use the quadrant comparison to decide whether the gap is geographic or service-specific. | marketing_intelligence |
| LV-AUT-01 | high | Pursue a small number of genuinely relevant local, manufacturer, trade, or association sources. Do not buy generic directory links. | market_intelligence |
| LV-AUT-02 | high | Build relationships with local organizations, publications, and trade sources. Do not treat a generic directory as local proof. | market_intelligence |
| LV-AUT-03 | medium | Pursue manufacturer/dealer listings, trade associations, and credible trade publications where the business qualifies. | market_intelligence |
| LV-AUT-04 | high | Correct the highest-authority inconsistent listings first. Cross-reference GBP Scorecard for the primary profile. | market_intelligence |
| LV-AUT-05 | medium | Compare the sources the leading competitors have that the business does not. Prioritize relevance over volume. | market_intelligence |
| LV-AUT-06 | medium | Prioritize sources that both corroborate the entity and appear in AI citations. | market_intelligence |
| LV-RES-01 | medium | Do not weaken a strong surface. Build a second surface as insurance and report the concentration explicitly. | market_intelligence |
| LV-RES-02 | medium | Decide whether the concentration is intentional. If not, build visibility for the next most important service. | market_intelligence |
| LV-RES-03 | medium | Check whether the concentration matches the service area. If not, investigate proximity and location coverage. | market_intelligence |
| LV-RES-04 | medium | Separate branded from non-branded demand in every report. Do not let branded rank inflate the core score. | market_intelligence |
| LV-RES-05 | low | Investigate lost visibility by surface and service. Do not invent a trend when the prior run is not comparable. | market_intelligence |
Family service taxonomy¶
| Mapping | Label | Use |
|---|---|---|
revenue_recovery |
Revenue Recovery | Recover revenue from open estimates, unsold opportunities, and conversion leaks. |
speed_to_lead |
Speed-to-Lead | Improve response time, routing, booking, and lead handling. |
customer_reactivation |
Customer Reactivation | Bring back inactive customers and past opportunities. |
market_intelligence |
Market Intelligence | Improve local visibility, service-area clarity, and market positioning. |
marketing_intelligence |
Marketing Intelligence | Connect lead sources, measurement, and channel profitability. |
cost_compression |
Cost Compression | Reduce waste from slow, broken, or unusable digital experiences. |
Scorecard family boundary: this reference covers discovery only. The GBP Scorecard diagnoses profile trust and action; the Website Scorecard diagnoses website conversion. See The Scorecard Family.