LoopyLuci Local SEO and Google Business Profile
Optimizing local search presence and Google Business Profile (formerly Google My Business) for businesses with physical locations.
When to Use
- Managing a business with a physical location
- Optimizing Google Business Profile for local search rankings
- Building local citations and NAP consistency
- Getting more customers from Google Maps and local search
- Managing reviews and local reputation
GBP Optimization Checklist
GBP_SETUP = {
'business_name': 'Exact legal name (consistent everywhere)',
'category': 'Primary category + up to 10 additional categories',
'address': 'Physical address (no PO boxes for GBP)',
'service_area': 'Service area if you don't serve at location',
'phone': 'Local number (not call center / toll-free)',
'website': 'Business website URL',
'hours': 'Regular and special/holiday hours',
'description': '750-character business description with keywords',
'photos': 'Interior, exterior, team, products (100+ recommended)',
'attributes': 'Black-owned, LGBTQ+ friendly, women-led, etc.',
'services': 'List of services/products offered',
'menus': 'For restaurants — online menu',
'booking': 'Booking button if applicable (appointment types)',
'questions': 'Q&A section — proactively answer common questions',
'posts': 'Weekly GBP posts (offers, events, updates)',
'reviews': 'Respond to every review (positive + negative)',
}
def gbp_audit_score(profile: Dict) -> Dict:
"""Score a GBP profile's completeness (100-point scale)."""
score = 0
missing = []
checks = [
('name', 5), ('category', 10), ('address', 10),
('phone', 10), ('website', 5), ('hours', 10),
('description', 5), ('photos', 10), ('services', 5),
]
for field, points in checks:
if profile.get(field):
score += points
else:
missing.append(field)
# Review response rate bonus
total_reviews = len(profile.get('reviews', []))
responded = sum(1 for r in profile.get('reviews', []) if r.get('responded'))
if total_reviews > 0 and responded / total_reviews >= 0.5:
score += 10
# Posting frequency bonus
posts_last_30 = profile.get('posts_last_30_days', 0)
if posts_last_30 >= 4:
score += 10
elif posts_last_30 >= 2:
score += 5
# Photo count bonus
photo_count = profile.get('photo_count', 0)
if photo_count >= 100: score += 10
elif photo_count >= 50: score += 5
return {
'score': min(score, 100),
'missing_elements': missing,
'rating': 'Excellent' if score >= 80 else 'Good' if score >= 60 else 'Needs work',
'recommendations': [f"Add: {m}" for m in missing],
}
Local Citation Building
CITATION_SITES = {
'tier_1': [
'Google Business Profile', 'Bing Places', 'Apple Maps',
'Facebook', 'Yelp', 'Yellow Pages',
],
'tier_2': [
'MapQuest', 'Superpages', 'Citysearch', 'Hotfrog',
'Merchant Circle', 'Foursquare', 'Manta',
],
'niche_specific': {
'restaurant': ['TripAdvisor', 'OpenTable', 'Zomato', 'MenuPages'],
'healthcare': ['Healthgrades', 'Zocdoc', 'Vitals', 'RateMDs'],
'legal': ['Avvo', 'Martindale', 'FindLaw', 'Lawyers.com'],
'home_services': ['Angi (Angies List)', 'HomeAdvisor', 'Houzz', 'Porch'],
'real_estate': ['Zillow', 'Realtor.com', 'Trulia', 'Redfin'],
},
}
class CitationBuilder:
"""Manage NAP consistency across citations."""
def __init__(self, business_name: str, address: str, phone: str, website: str):
self.nap = {
'name': business_name,
'address': address,
'phone': phone,
'website': website,
}
self.citations = []
def add_citation(self, site: str, url: str,
nap_match: str = 'exact', status: str = 'pending'):
self.citations.append({
'site': site, 'url': url,
'nap_match': nap_match, # exact, partial, mismatch
'status': status,
'last_verified': None,
})
def get_consistency_report(self) -> Dict:
exact = sum(1 for c in self.citations if c['nap_match'] == 'exact')
partial = sum(1 for c in self.citations if c['nap_match'] == 'partial')
mismatched = sum(1 for c in self.citations if c['nap_match'] == 'mismatch')
pending = sum(1 for c in self.citations if c['status'] == 'pending')
return {
'total_citations': len(self.citations),
'exact_match': exact,
'partial_match': partial,
'mismatch': mismatched,
'pending': pending,
'consistency_score': round(exact / max(len(self.citations), 1) * 100, 1),
}
Local Ranking Factors
LOCAL_RANKING_FACTORS = {
'proximity': {
'weight': 'High',
'description': 'Distance between searcher and business location',
'influence': 'You can't change proximity, but can target specific areas',
},
'gbp_signals': {
'weight': 'Very High',
'description': 'Category, attributes, verification, completeness',
'influence': 'Optimize every GBP field; post weekly; respond to reviews',
},
'reviews': {
'weight': 'High',
'description': 'Quantity, recency, diversity, and sentiment of reviews',
'influence': 'Encourage reviews, respond to all, never buy fake reviews',
},
'citations': {
'weight': 'Medium',
'description': 'Number and consistency of NAP across the web',
'influence': 'Build tier 1 citations first; audit consistency quarterly',
},
'backlinks': {
'weight': 'Medium',
'description': 'Quality and relevance of backlinks to your site',
'influence': 'Local backlinks (chambers, sponsors, partners) are most valuable',
},
'website_signals': {
'weight': 'Medium',
'description': 'On-page local SEO (title, H1, schema, content)',
'influence': 'Include city/region in title, headings, and content',
},
'social_signals': {
'weight': 'Low',
'description': 'Social media presence and engagement',
'influence': 'Active social profiles with consistent NAP',
},
}
def local_seo_audit(business: Dict) -> List[str]:
"""Generate local SEO recommendations."""
recs = []
if not business.get('gbp_claimed'):
recs.append("Claim and verify your Google Business Profile")
if business.get('gbp_category_count', 0) < 3:
recs.append("Add more relevant categories to GBP (up to 10)")
if business.get('gbp_photos', 0) < 50:
recs.append(f"Add more photos to GBP (currently {business.get('gbp_photos', 0)}, target 100+)")
if business.get('gbp_posts_30d', 0) < 4:
recs.append("Post to GBP at least once per week (services, offers, events)")
if business.get('review_count', 0) < 10:
recs.append("Implement a review generation strategy (target 10+ reviews)")
if business.get('review_response_rate', 0) < 0.5:
recs.append("Respond to ALL reviews — positive and negative")
return recs
Common Pitfalls
- NAP inconsistency — different address formats across citations confuse Google
- Unclaimed GBP — Google populates unclaimed profiles with unreliable data; claim yours
- Buying fake reviews — Google detects and penalizes; legitimate review generation only
- Abandoned profile — old posts, unresponded reviews, outdated hours hurt rankings
- Wrong category — primary category is the #1 ranking signal; choose carefully
- No review strategy — customers need to be asked; make it easy to leave a review
Verification Checklist
- Google Business Profile claimed and verified
- All NAP fields complete and accurate
- Primary + secondary categories selected
- 100+ high-quality photos uploaded
- Business description written (750 chars, keyword-rich)
- Products/services listed
- Weekly GBP posts published
- All reviews responded to within 48 hours
- Top 10 citation sites checked for NAP consistency
- Local schema markup on website
See Also
- seo-search-engine-optimization — broader SEO strategy
- website-analytics-tracking — tracking local search performance
- digital-marketing-strategy — local SEO in marketing mix
- cms-website-management — local SEO on website