TL;DR: Classic keyword lists miss how modern search and AI assistants think—in entities (things, places, attributes, actions). Build a service entity map, expand with modifiers (situations, tools, outcomes), then bind to cities and questions to produce a concrete page plan and FAQ inventory that converts.

Quick Answer

“Entity-first” means you model your business as things with attributes and relationships (service types, sub-services, tools, problems, outcomes, locations, regulations, brands). Instead of brainstorming random terms, you:

Inventory entities you perform and prove (jobs, photos, reviews).
Attach modifiers (emergency, same-day, pricing, symptoms, tools).
Bind each entity to cities/neighborhoods you actually serve.
Generate Answer-first pages (Service + City), supporting FAQ clusters, and a publishing backlog with internal link rules.

Why Entity-First Now (2025)

AI Overviews & assistants extract and cross-reference entities, not just strings.
Local ranking signals reward relevance backed by consistent wording across GBP services, on-page copy, reviews, and images.
Conversion improves when copy mirrors the exact problem, tool, and outcome a homeowner expects (“German roach gel bait in Jupiter kitchen—10 days to clear”).

The Entity Map Workshop (90 Minutes, Team Exercise)

Invite: owner/GM, dispatcher/CSR, 1–2 senior techs, marketing lead. Whiteboard five columns and fill top items (10–20 each):

Column	What to list	Examples (Pest)	Examples (Water)	Examples (Handyman)
Service Entities	Core services and named sub-services	pest control service; ant control; German cockroach treatment; rodent exclusion; mosquito reduction	water damage restoration; emergency extraction; structural drying; moisture mapping; mold removal	handyman; sliding door replacement; drywall repair; TV mounting
Problem/Symptom Entities	Homeowner language	ants in kitchen; droppings in attic; bites in yard	wet carpet; ceiling stain; musty smell	door won’t slide; cracked drywall; outlet loose
Tool/Method Entities	Gear, chemicals, standards	B&G sprayer; gel baits; IPM; 25(b) products; bait stations	LGR dehumidifiers; thermal imaging; moisture meters	track/roller kits; stud finders; GFCI
Outcome Entities	Results homeowners feel	kitchen cleared in 10 days; zero mice after 2 weeks; fewer mosquitoes	structure dry in 48–72h; no odor; pass meter reading	door slides smoothly; wall flush; safe outlet
Geo Entities	Cities, ZIPs, neighborhoods	Jupiter, Abacoa, Tequesta	Encinitas, Leucadia, San Marcos	Carlsbad, Bressi Ranch, Calavera Hills

Circle anything you can prove with photos, notes, or reviews. Those are priority entities.

Modifiers: The Multipliers That Create Real Queries

Attach modifiers to each service entity to generate long-tail opportunities:

Urgency/Timing: emergency, 24/7, same-day, weekend, after-hours
Audience/Setting: apartment, HOA, single-family, landlord, commercial suite
Scope/Severity: heavy infestation, minor leak, large sliding door, upstairs pipe burst
Constraints: pet-safe, infant-safe, eco-friendly, no odor, access limited
Money: cost, price, estimate, financing, insurance, deductible
Compliance: warranty, code, permit, insurance claim, photos for adjuster
Outcome: how long to clear, how long to dry, how to prevent recurrence

Rule: Choose 3–5 modifiers per service entity. Combine with your top 5 cities for 15–25 “money queries” per service—enough to fill a quarter.

The 3-Layer Cluster Model

Layer 1: Service Hubs (national/brand-level evergreen):
/services/pest-control/ → defines entities, methods, safety, proof.

Layer 2: City Hubs (local positioning):
/service-areas/jupiter/ → how your offer meets local conditions, neighborhoods, climate.

Layer 3: Service + City Answer Pages (intent pages you want to rank & convert):
/ant-control-jupiter/, /water-damage-restoration-encinitas/, /sliding-door-replacement-carlsbad/.

Each Service + City page spawns FAQs and supporting posts (pricing, timelines, prevention). Internally link up to hubs and across to sibling pages.

From Entity Map → Page Plan (Worked Examples)

Example 1 — Pest Control (Jupiter)

Service entity: German cockroach treatment
Modifiers: pet-safe, kitchen, car, 10–14 day clear, follow-up
Geo: Jupiter, Abacoa, Tequesta
Pages/Posts
/german-cockroach-treatment-jupiter/ (primary)
FAQ posts: “Do I need to empty cabinets?”, “How long until roaches disappear?”, “Is gel bait safe for pets?”
Support: “German roaches in cars—what works and why traps don’t”
Proof assets: annotated job photos, review snippets naming German roach + Jupiter.

Example 2 — Water Restoration (Encinitas)

Service entity: emergency water extraction
Modifiers: upstairs leak, 48–72h dry, insurance photos, 24/7
Geo: Encinitas, Leucadia, Cardiff
Pages/Posts
/emergency-water-extraction-encinitas/ (primary)
“How fast should drywall read on a moisture meter?”
“Insurance photos checklist after a leak”
Proof assets: meter-reading table over time, before/after ceiling stain.

Example 3 — Handyman (Carlsbad)

Service entity: sliding door replacement
Modifiers: coastal corrosion, heavy glass, track/roller kits, same-week
Geo: Carlsbad, Bressi Ranch, Calavera Hills
Pages/Posts
/sliding-door-replacement-carlsbad/ (primary)
“Do I need a permit for slider replacement in Carlsbad?”
“Roller vs. track replacement—how to decide”
Proof assets: 30-sec clip of smooth slide + short caption.

Query Canvas (Fill-In Grid for Your Team)

Use this table to generate “real” queries that map to your pages:

Service entity	Modifier	Geo	Human phrasing (paste into notes)	Target page	Evidence we have
German roach treatment	pet-safe; kitchen	Jupiter	“pet safe roach gel for kitchen Jupiter”	/german-cockroach-treatment-jupiter/	photos, 2 reviews
Emergency extraction	upstairs; 24/7	Encinitas	“emergency water cleanup encinitas upstairs bathroom”	/emergency-water-extraction-encinitas/	meter logs, before/after
Sliding door replacement	heavy glass; track	Carlsbad	“heavy sliding door track replacement carlsbad”	/sliding-door-replacement-carlsbad/	video, invoice

Building the FAQ Inventory (Entity → Question Patterns)

For each Service + City page, create 6–10 FAQs using these patterns:

Timing: “How long until [outcome] after [service] in [City]?”
Safety: “Is [method/tool] safe around [children/pets]?”
Cost: “What does [service] cost in [City], and what changes the price?”
Prep: “Do I need to [prep action] before the visit?”
Prevention: “How do we prevent [problem] from returning?”
Edge case: “What if it’s [apartment/HOA/older home]?”

Add each FAQ to a backlog doc and track proof needed (photo, data point, quote).

Copy Blocks That Encode Entities (Paste-Ready)

Service + City opener (first 60–80 words)

We provide [service entity] in [City] using [method/tool] for [problem]. Most homes see [outcome metric + timeframe] when we follow [process short name] and [safety constraint]. Call for [urgency modifier] scheduling.

Result caption (under photo)

[Service] – [Neighborhood]: [tool/method] applied to [location], [before metric] → [after metric] in [timeframe].

Review prompt (neutral)

“If helpful, mention the service we performed and your city—that helps neighbors considering similar work.”

Internal Linking Rules (Keep It Literal)

Up: Service + City → /services/[service]/ and /service-areas/[city]/
Across: Service + City ↔ sibling Service + City in adjacent neighborhoods
Down: Service + City → case studies, pricing explainers, FAQs
Anchors: Use exact phrases (“water damage restoration in Encinitas”)—skip clever synonyms.

Prioritization Framework: ICE for Local Entities

Score each Service + City opportunity:

Factor	What it means	Scale
Impact	Likely calls/revenue if the page ranks	1–5
Confidence	Proof available (photos, reviews, data)	1–5
Ease	Time to produce page + FAQs + media	1–5

Work on the highest total first. This avoids publishing thin, proof-less pages.

Editorial & Evidence Checklist (Per Page)

Entity-rich intro: service, city, method/tool, outcome metric.
Quick Answer paragraph near the top (2–4 sentences).
Steps list and a decision tree or “When to escalate.”
Pricing range + variables.
At least two proof assets (photo/video + caption with entities).
6–10 FAQs derived from entity patterns.
Internal links up/across/down set correctly.
Language mirrors GBP services and attributes.

Publishing Cadence (Eight Weeks)

Week 1–2 → Build two Service + City pages with full FAQs and proof.
Week 3–4 → Add two more Service + City pages + pricing explainer post.
Week 5–6 → Publish five FAQs as short posts (interlink back).
Week 7–8 → Add two case studies with before/after visuals and meter data.

Measuring What Matters

Impressions & CTR for Service + City pages in GSC.
GBP justifications appearing more often (“Their website says…”).
Calls/messages from those pages (UTM + call tracking).
Review topic coverage matching target entities (“German roach,” “structural drying”).

Common Pitfalls (and How to Avoid Them)

Keyword spreadsheets with synonyms only → Replace with entity map + modifiers + geo binding.
Publishing city pages without proof → Delay until you have photos, notes, or review fragments.
Over-broad service areas → Focus on cities where crews already work; expand once prominence grows.
Inconsistent wording across GBP and site → Mirror the exact service names and attributes.

Quick Start Sprint (48–72 Hours)

Run the Entity Map Workshop; select top 3 service entities.
Pick 5 modifiers and 5 cities; fill the Query Canvas.
Draft two Service + City pages with 6–10 FAQs each.
Collect proof (2 photos per page + 1 short clip).
Ship and interlink; review metrics in 2 weeks.

FAQs

Isn’t this just long-tail keyword research with extra steps?
No. Entity-first ties words to things you can prove and cities you serve, which AI and Google can corroborate.

What if my crew does many services?
Prioritize by Impact × Confidence × Ease and publish the top four Service + City pages first.

Do I need a pricing page for every service?
A central pricing explainer is fine; each Service + City page should still list a range and variables.

Can I reuse the same FAQs across cities?
Yes—rewrite the opener and examples to reference the local context and proof.

Entity-First Keyword Research 2025: From Services → Cities → Questions → Conversions