gbp-review-strategy

Research source (Exa)

Default: Exa, per .claude/rules/exa-protocol.md (auto-loaded for research, audit, competitor, ICP, AEO, content sourcing, sales prospecting work).

Primary Exa tools for this skill: web_search_exa.

Use case: competitor review pattern research.

Tool surface during the migration window:

• New plugin (preferred): mcp__plugin_exa_exa__web_search_exa (after claude plugin i exa@claude-plugins-official).
• Legacy MCP (still mounted): mcp__exa__web_search_exa.
• Both backends route to the same Exa API — they don't double-bill.

Citation: every Exa-derived claim uses [VERIFIED: exa_search, {url}, accessed {YYYY-MM-DD}] per .claude/rules/ontology.md.

Quality gate (research outputs): ≥3 sources per major claim, ≥50% [VERIFIED] confidence, date filter for any "recent / latest" claim, no fallback to WebSearch without flagging the data gap.

Worked examples + tool catalog: .claude/skills/meta-skills/exa/.

GBP review strategy

Analyzes competitor review velocity, keyword mentions in reviews, neighborhood mentions, and recurring complaints. Then generates review response templates (5-star, 4-star, 3-star, 1-2 star) with 3 variations each that naturally incorporate service + location keywords. Covers article prompts #3 (competitor review teardown) and #4 (review response strategy) from the local SEO playbook.

---

Doctrine inherited (Step 7 — 0626 rollout, locked 2026-06-04)

Output complies with:

• output-tenets.md, output-simplicity.md
• Step 6 calibration: see [[feedback_execution_doctrine_refinements_step6]]

Refinements applied to this skill:

Code	Refinement	How it lands in gbp-suite
R1	Source placement	Review response templates → end-customer-facing (posted publicly on GBP). No source tags.
R2	Single-doc-with-toggles	Multi-template pack ships as one doc with toggle per star tier.
R3	Product-update tone	Responses frame as "we appreciate / we hear / we ship X" — operator-direct, never "we are thrilled."
R6	CTA hierarchy	Response close → product-action (visit again, contact us) per customer-facing service business.
R7	FAQ titles + no sources block	Competitor-review teardown article uses FAQ title pattern ("What review patterns work for [vertical]?").
R8	Entity-name headings	Section headings repeat business name where applicable.
R9	Action-oriented section names	Response template names verb-led.

---

Process Flowchart

┌──────────────────────────────────────────────────────────────┐
│ GBP REVIEW STRATEGY PROCESS │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ INPUT VALIDATION │
│ Required: │
│ □ Client GBP URL │
│ □ 2-3 competitor GBP URLs │
│ □ Target keywords (3+) │
│ □ Service areas (neighborhoods/cities) │
│ Optional: Current review count, response rate baseline │
│ → If missing: Ask for GBP URLs and target keywords │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ PHASE 1: REVIEW DATA EXTRACTION │
│ □ Scrape last 50 reviews per listing (client + competitors) │
│ □ Extract: total count, avg rating, 30/60/90 day velocity │
│ □ Extract: mentioned services, neighborhoods, complaints │
│ ✓ Checkpoint: Review data captured for all listings │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ PHASE 2: VELOCITY ANALYSIS │
│ □ Calculate reviews/month for each listing (30/60/90 day) │
│ □ Identify top competitor by velocity │
│ □ Calculate reviews/month needed to catch top competitor │
│ □ Estimate time-to-parity at target velocity │
│ ✓ Checkpoint: Velocity gap quantified with catch-up target │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ PHASE 3: RESPONSE AUDIT │
│ □ Analyze owner responses: response rate, avg response time │
│ □ Check keyword usage in existing responses │
│ □ Evaluate tone and negative review handling │
│ □ Compare response quality across all listings │
│ ✓ Checkpoint: Response gaps identified vs. competitors │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ PHASE 4: TEMPLATE GENERATION │
│ □ Create 5-star templates (3 variations) │
│ □ Create 4-star templates (3 variations) │
│ □ Create 3-star templates (3 variations) │
│ □ Create 1-2 star templates (3 variations) │
│ □ Each template includes service keywords + location mention │
│ ✓ Checkpoint: 12 templates ready, keywords naturally placed │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌──────────────────────────────────────────────────────────────┐
│ PHASE 5: STRATEGY DOCUMENT │
│ □ Set monthly review velocity target │
│ □ Identify where/when to ask for reviews │
│ □ Define what to ask customers to mention (service + area) │
│ □ Create 90-day review growth roadmap │
│ ✓ Checkpoint: Actionable strategy with measurable targets │
└──────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌────────────────────────────────────┬─────────────────────────┐
│ REVIEW GATE: Level 1 (Quick) │ CHAIN SUGGESTIONS │
├────────────────────────────────────┼─────────────────────────┤
│ Present: Velocity analysis, │ → gbp-content-engine │
│ response audit, 12 templates, │ → gbp-listing-opt │
│ strategy doc │ → content-strategy │
│ Actions: [Approve] [Adjust] │ → Export to Google Docs │
│ [Add competitors] │ │
└────────────────────────────────────┴─────────────────────────┘

---

Claude Code Triggers

Invoke this skill when user says:

• "Review strategy for [business]"
• "Review teardown"
• "Competitor review analysis"
• "Review response templates"
• "How do I get more reviews?"
• "Review velocity analysis"
• "Help me respond to reviews"
• "Google review strategy"
• "Review gap analysis"

Do NOT invoke when:

• User wants full local SEO audit (use /local-seo-audit orchestrator)
• User wants GBP category or attribute analysis (use /gbp-category-audit)
• User wants GBP posts or photo strategy (use /gbp-content-engine)
• User wants services section or description optimization (use /gbp-listing-optimization)

---

Input Requirements

Required Inputs

Input	Description	Source
Client GBP URL	Google Maps/Business link for the client	User provides
Competitor GBP URLs	2-3 top competitor listings	User provides or researched
Target keywords	3+ service-related keywords to rank for	User provides
Service areas	Neighborhoods/cities served	User provides

Optional Inputs (improve quality)

Input	How It Helps
Current review count	Baseline for velocity calculations without scraping
Response rate baseline	Skip response audit if already known
Business owner name	Personalize response templates
Core services list	Ensure templates cover all service lines
Previous review solicitation methods	Build on what's already working

Input Validation Checklist

Before proceeding, verify:

• Client GBP URL is accessible and has reviews
• At least 2 competitor GBP URLs provided
• At least 3 target keywords specified
• Service areas defined (neighborhoods or cities)

If inputs are missing: Ask for client GBP URL first. Offer to research competitors via Exa/Firecrawl if user doesn't have competitor URLs.

---

Process (Step-by-Step)

Phase 1: Review data extraction

Purpose: Scrape and structure review data from client and competitor GBP listings.

Steps:

1. Step 1.1: Scrape client reviews

   • Pull last 50 reviews from client GBP URL
   • Extract: reviewer name, rating, date, review text, owner response (if any)
   • Output: Client review dataset

2. Step 1.2: Scrape competitor reviews

   • Pull last 50 reviews per competitor GBP URL (2-3 competitors)
   • Extract same fields as client
   • Output: Competitor review datasets

3. Step 1.3: Parse review content

   • For each listing, extract:
     • Total review count and average rating
     • Services mentioned (map to target keywords)
     • Neighborhoods/locations mentioned
     • Recurring complaints (grouped by theme)
     • Recurring praise (grouped by theme)
   • Output: Parsed review content analysis per listing

Phase 1 Checkpoint:

• Review data captured for client + all competitors
• Services, neighborhoods, and complaints extracted
• Data is sourced — no invented review counts or ratings

Phase 2: Velocity analysis

Purpose: Quantify review generation speed and calculate the gap to close.

Steps:

1. Step 2.1: Calculate review velocity per listing

   • Count reviews in last 30, 60, and 90 days for each listing
   • Calculate reviews/month average for each window
   • Output: Velocity table (listing x time window)

2. Step 2.2: Identify velocity gap

   • Rank all listings by 90-day velocity
   • Calculate gap between client and top competitor
   • Output: Gap measurement (reviews/month behind)

3. Step 2.3: Calculate catch-up projections

   • Reviews/month needed to reach parity with top competitor in 6, 9, and 12 months
   • Factor in competitor's ongoing velocity (they don't stop)
   • Output: Time-to-parity projections at different velocity targets

Phase 2 Checkpoint:

• Velocity calculated for all listings across 30/60/90 day windows
• Gap quantified with specific catch-up numbers
• Projections account for competitor's ongoing velocity

Phase 3: Response audit

Purpose: Evaluate how well each business responds to reviews and identify gaps.

Steps:

1. Step 3.1: Calculate response metrics

   • Response rate (% of reviews with owner reply)
   • Average response time (if timestamps available, otherwise note as [UNAVAILABLE])
   • Output: Response rate comparison table

2. Step 3.2: Analyze response quality

   • Check for target keyword usage in responses
   • Check for location/neighborhood mentions in responses
   • Evaluate tone: professional, personal, template-feeling, defensive
   • Assess negative review handling: apologetic, defensive, solution-oriented, ignored
   • Output: Response quality assessment per listing

3. Step 3.3: Identify response patterns

   • Does competitor use templates? (look for repeated phrases)
   • Do responses mention specific services or staff?
   • Do responses include calls-to-action (come back, try X)?
   • Output: Response pattern analysis

Phase 3 Checkpoint:

• Response rate and quality compared across all listings
• Keyword usage in responses quantified
• Best practices identified from top-performing competitor

Phase 4: Template generation

Purpose: Create 12 review response templates (4 tiers x 3 variations) with embedded keywords.

Steps:

1. Step 4.1: Define template structure

   • Each template must naturally include:
     • At least 1 target service keyword
     • At least 1 location/neighborhood mention
     • Personal touch (reference specifics from review)
     • Forward-looking statement (invitation to return, try another service)
   • Output: Template structure guidelines

2. Step 4.2: Create 5-star response templates (3 variations)

   • Variation A: Service-focused (highlights the specific service praised)
   • Variation B: Team-focused (credits staff, builds personal connection)
   • Variation C: Community-focused (emphasizes neighborhood/local pride)
   • Output: 3 x 5-star templates

3. Step 4.3: Create 4-star response templates (3 variations)

   • Variation A: Grateful + improvement-curious (asks what would make it 5 stars)
   • Variation B: Service expansion (mentions related services they might enjoy)
   • Variation C: Loyalty-building (offers reason to return)
   • Output: 3 x 4-star templates

4. Step 4.4: Create 3-star response templates (3 variations)

   • Variation A: Empathetic + action-oriented (acknowledge gap, state fix)
   • Variation B: Dialogue-opening (invite offline conversation)
   • Variation C: Improvement commitment (specific steps being taken)
   • Output: 3 x 3-star templates

5. Step 4.5: Create 1-2 star response templates (3 variations)

   • Variation A: Empathetic + escalation (apologize, provide direct contact)
   • Variation B: Fact-based + resolution (address specific issue, state resolution)
   • Variation C: Service recovery (offer to make it right, specific next step)
   • Never: defensive, dismissive, or argumentative tone
   • Output: 3 x 1-2 star templates

Phase 4 Checkpoint:

• 12 templates total (4 tiers x 3 variations)
• Every template includes at least 1 service keyword naturally
• Every template includes at least 1 location mention naturally
• Negative review templates are empathetic, never defensive
• Templates have [BRACKET] placeholders for personalization

Phase 5: Strategy document

Purpose: Create an actionable review growth plan with measurable targets.

Steps:

1. Step 5.1: Set monthly velocity target

   • Based on Phase 2 catch-up projections
   • Recommend realistic velocity (with reasoning)
   • Output: Monthly review target with justification

2. Step 5.2: Map review solicitation touchpoints

   • In-person: after service completion, at checkout
   • Digital: follow-up email/SMS, thank-you page, QR codes
   • Timing: optimal ask window (24-48 hours post-service)
   • Output: Touchpoint map with timing

3. Step 5.3: Define review content guidance

   • What to ask customers to mention: specific service, neighborhood, staff name
   • How to frame the ask (natural, not scripted)
   • Example scripts for staff to use when asking
   • Output: Content guidance with example ask scripts

4. Step 5.4: Create 90-day roadmap

   • Month 1: Set up systems (templates, ask scripts, QR codes)
   • Month 2: Launch review solicitation at all touchpoints
   • Month 3: Measure velocity, adjust approach, respond to all new reviews
   • Output: 90-day action plan

Phase 5 Checkpoint:

• Velocity target set with time-to-parity math
• Touchpoints identified with timing guidance
• Customer ask scripts provided
• 90-day roadmap with measurable milestones

---

GBP Review Strategy: [Business Name]

GBP URL: [URL] Date assessed: [Date] Competitors analyzed: [Competitor 1], [Competitor 2], [Competitor 3] Assessor: Genesys Growth

---

Review Velocity Comparison

Metric	[Client]	[Competitor 1]	[Competitor 2]	[Competitor 3]
Total reviews	X	X	X	X
Average rating	X.X	X.X	X.X	X.X
Reviews (last 30 days)	X	X	X	X
Reviews (last 60 days)	X	X	X	X
Reviews (last 90 days)	X	X	X	X
Velocity (reviews/month)	X	X	X	X

Gap to #1: [X] reviews/month behind [Competitor Name] Time to parity: ~[X] months at [Y] reviews/month target

---

Review Content Analysis

Services mentioned in reviews

Service keyword	[Client]	[Comp 1]	[Comp 2]	[Comp 3]
[Keyword 1]	X mentions	X mentions	X mentions	X mentions
[Keyword 2]	X mentions	X mentions	X mentions	X mentions
[Keyword 3]	X mentions	X mentions	X mentions	X mentions

Neighborhoods mentioned in reviews

Location	[Client]	[Comp 1]	[Comp 2]	[Comp 3]
[Area 1]	X mentions	X mentions	X mentions	X mentions
[Area 2]	X mentions	X mentions	X mentions	X mentions

Recurring complaints (by theme)

Complaint theme	[Client]	[Comp 1]	[Comp 2]	[Comp 3]
[Theme 1]	X occurrences	X	X	X
[Theme 2]	X occurrences	X	X	X

---

Response Audit

Metric	[Client]	[Comp 1]	[Comp 2]	[Comp 3]
Response rate	X%	X%	X%	X%
Avg response time	[X days / UNAVAILABLE]	[X days]	[X days]	[X days]
Keyword usage in responses	[Yes/No]	[Yes/No]	[Yes/No]	[Yes/No]
Location mentions in responses	[Yes/No]	[Yes/No]	[Yes/No]	[Yes/No]
Negative review handling	[Approach]	[Approach]	[Approach]	[Approach]

Key gaps:

• [Gap 1]
• [Gap 2]
• [Gap 3]

---

Review Response Templates

5-star responses

Variation A — Service-focused:

[Template with [SERVICE KEYWORD], [LOCATION], [REVIEWER NAME], [SPECIFIC DETAIL] placeholders]

Variation B — Team-focused:

[Template]

Variation C — Community-focused:

[Template]

---

4-star responses

Variation A — Grateful + improvement-curious:

[Template]

Variation B — Service expansion:

[Template]

Variation C — Loyalty-building:

[Template]

---

3-star responses

Variation A — Empathetic + action-oriented:

[Template]

Variation B — Dialogue-opening:

[Template]

Variation C — Improvement commitment:

[Template]

---

1-2 star responses

Variation A — Empathetic + escalation:

[Template]

Variation B — Fact-based + resolution:

[Template]

Variation C — Service recovery:

[Template]

---

Review Growth Strategy

Monthly velocity target

• Target: [X] reviews/month
• Current: [X] reviews/month
• Gap: [X] reviews/month
• Time to parity with [Competitor]: ~[X] months

Where to ask for reviews

Touchpoint	When	Method	Expected yield
[Touchpoint 1]	[Timing]	[Method]	[Est. reviews/month]
[Touchpoint 2]	[Timing]	[Method]	[Est. reviews/month]
[Touchpoint 3]	[Timing]	[Method]	[Est. reviews/month]

What to ask customers to mention

• Service: [Specific service they received]
• Location: [Neighborhood or area name]
• Experience: [Specific aspect of service]

Staff ask scripts

Script 1 (in-person, post-service):

"[Natural ask script with specific service + location mention guidance]"

Script 2 (follow-up text/email):

"[Natural digital follow-up script]"

90-day roadmap

Month	Focus	Actions	Target
1	Setup	[Actions]	[Target]
2	Launch	[Actions]	[Target]
3	Optimize	[Actions]	[Target]

---

Iteration Prompts

1. "Want me to add more competitors to the velocity analysis?"
2. "Should I create review solicitation email/SMS sequences?"
3. "Want me to run the GBP content engine to complement this review strategy?"
4. "Should I export this to Google Docs for the client?"

---

## Anti-Hallucination Guardrails

1. **Only report what was scraped.** If review data can't be extracted for a listing, mark as "[UNAVAILABLE: could not scrape reviews for [listing]]" — don't estimate.
2. **No invented review counts or ratings.** Every number in velocity tables must come from scraped data or user-provided data.
3. **Velocity math must be shown.** Show the calculation behind reviews/month and time-to-parity projections so user can verify.
4. **Response templates are templates, not real responses.** Clearly mark all placeholders with [BRACKETS] and never include real customer names or review content in templates.
5. **Complaint themes must come from actual reviews.** Don't invent complaint categories — only report themes that appear in scraped review text.
6. **Review data is point-in-time.** Note the scrape date on all data tables — review counts change daily.
7. **Time-to-parity is an estimate.** Tag all projections with [ESTIMATED: based on current velocity trends] — competitors can change their velocity too.

---

## Quality Checklist (Pre-Delivery)

### Data quality
- [ ] Review data scraped for client + all competitors (or marked [UNAVAILABLE])
- [ ] Velocity calculated from actual review dates, not estimated
- [ ] All numbers traceable to scraped data
- [ ] Scrape date noted on all data tables

### Analysis quality
- [ ] Velocity comparison table complete (30/60/90 day)
- [ ] Service keyword mentions extracted and compared
- [ ] Neighborhood mentions extracted and compared
- [ ] Recurring complaints grouped by theme with counts
- [ ] Response audit covers rate, time, keywords, tone

### Template quality
- [ ] 12 templates total (4 tiers x 3 variations)
- [ ] Every template includes at least 1 service keyword naturally
- [ ] Every template includes at least 1 location mention naturally
- [ ] Negative review templates are empathetic, never defensive
- [ ] All placeholders clearly marked with [BRACKETS]
- [ ] Templates sound human, not robotic or over-optimized

### Strategy quality
- [ ] Monthly velocity target set with catch-up math
- [ ] Touchpoints identified with timing and method
- [ ] Customer ask scripts provided (in-person + digital)
- [ ] 90-day roadmap with measurable milestones
- [ ] Strategy is realistic for business size and type

---

## Post-Output: Iteration Prompts

After delivering output, proactively offer these iteration options:

### Refinement prompts
1. "Want me to adjust the velocity target based on your capacity?"
2. "Should I customize the templates for a specific service line?"
3. "Want me to add more competitors to the analysis?"

### Expansion prompts
1. "Want me to create review solicitation email/SMS sequences?"
2. "Should I run /gbp-content-engine to build a posts strategy that reinforces review themes?"
3. "Want me to create a review monitoring dashboard spec?"

### Quality prompts
1. "Want me to test the response templates against your actual recent reviews?"
2. "Should I analyze seasonal patterns in your review velocity?"
3. "Want me to identify which competitor response patterns correlate with higher ratings?"

---

## MCP Data Integration

**Level:** 0 — Context (heavy data gathering, competitive analysis)

### Primary tools

| Source | What to pull | Tool | When |
|--------|-------------|------|------|
| **Apify** | Structured Google Maps review data | `call-actor` (Google Maps Reviews actor) | Primary extraction method |
| **Firecrawl** | GBP listing pages (fallback) | `firecrawl_scrape` | When Apify unavailable or for supplementary data |
| **Exa** | Competitor discovery if URLs not provided | `web_search_exa` | When user doesn't have competitor GBP URLs |

### Apify integration

```javascript
// Google Maps Reviews actor — extract last 50 reviews per listing
call-actor({
  actorId: "compass/google-maps-reviews-scraper",
  input: {
    startUrls: ["[GBP_URL]"],
    maxReviews: 50,
    reviewsSort: "newest"
  }
})

What Apify provides:

• Review text, rating, date, reviewer name
• Owner response text and timestamp
• Total review count and average rating
• Structured data ready for analysis

Fallback (no MCP)