69.6 average across 2 concepts
Local operating-model alignment analysis
Best Franchise Opportunities We Assessed in San Antonio, Texas
We compared 14 franchise concepts for San Antonio, Texas. Local business demand was a leading positive mechanism. Service-base space scarcity was a leading operating constraint.
Evaluation set
Why these concepts were evaluated
This is not a ranking of every franchise that may be offered in the city.
Concepts were included when enough operating-model information existed to assign a provisional local-sensitivity profile. Unresolved inputs reduce confidence or remain conditional rather than automatically excluding a concept.
A brand’s participation in our referral network does not add points or change its position.
City-level conclusions
What stood out in our assessment
1.7 points average among 13 affected concepts
0.7 points average reduction among 8 affected concepts
Tested rank range spans 9 positions
Executive conclusion
What the ranking means for San Antonio, Texas
City Wide, Jan-Pro International, and ActionCOACH produced the highest modeled local-alignment scores in the evaluated set. Local business demand was the strongest positive scored mechanism among 10 exposed concepts, adding 1.2 points on average. Service-base space scarcity was the broadest operating constraint, reducing exposed concepts by 0.7 points on average. These scores describe local operating alignment, not expected returns or overall franchise quality; the offered territory and franchise economics still require separate diligence.
How this differs from a directory: the model does not award points for brand popularity, advertising placement, or referral compensation. It tests how documented local conditions interact with each concept’s operating requirements.
Best franchise opportunities assessed
Top 10 local-alignment scores from 14 concepts assessed
“Best” refers to modeled local operating alignment among the concepts assessed—not expected earnings, franchise-system quality, or candidate fit.
| Rank | Franchise | Alignment and tier | Largest advantage | Largest constraint | Evidence confidence |
|---|---|---|---|---|---|
| 1 | City WideFacility managementInvestment: $229,729–$410,730 | 74.1Tier 2 · Favorable modeled alignment | +3.4 ptsTarget-market demand | -0.1 ptsTerritory quality | Moderate evidence confidence |
| 2 | Jan-Pro InternationalCommercial cleaningInvestment: $130,000–$421,500 | 72.8Tier 2 · Favorable modeled alignment | +2.9 ptsTarget-market demand | -0.3 ptsTerritory quality | Moderate evidence confidence |
| 3 | ActionCOACHBusiness coachingInvestment: $71,668–$303,513 | 72.6Tier 2 · Favorable modeled alignment | +2.1 ptsTarget-market demand | -0.1 ptsTerritory quality | Moderate evidence confidence |
| 4 | HomeSmilesProperty maintenance servicesInvestment: $148,110–$201,800 | 72.6Tier 2 · Favorable modeled alignment | +2.8 ptsTarget-market demand | -0.4 ptsTerritory quality | Moderate evidence confidence |
| 5 | FASTSIGNSSigns and graphicsInvestment: $231,226–$386,285 | 71.6Tier 3 · Mixed modeled alignment | +2.6 ptsTarget-market demand | -0.8 ptsReal estate and site feasibility | Moderate evidence confidence |
| 6 | Pillar To Post Home InspectorsHome inspectionInvestment: $102,690–$134,290 | 71.5Tier 3 · Mixed modeled alignment | +1.6 ptsTarget-market demand | -0.3 ptsTerritory quality | Moderate evidence confidence |
| 7 | ZOOM DRAINDrain and sewer serviceInvestment: $266,250–$570,500 | 71.0Tier 3 · Mixed modeled alignment | +1.3 ptsTarget-market demand | -0.8 ptsReal estate and site feasibility | Moderate evidence confidence |
| 8 | Aire ServHVAC installation, repair, and maintenanceInvestment: $113,308–$271,708 | 71.0Tier 3 · Mixed modeled alignment | +1.4 ptsTarget-market demand | -0.8 ptsReal estate and site feasibility | Moderate evidence confidence |
| 9 | Mr. RooterPlumbingInvestment: $152,900–$298,675 | 70.9Tier 3 · Mixed modeled alignment | +1.3 ptsTarget-market demand | -0.6 ptsReal estate and site feasibility | Moderate evidence confidence |
| 10 | Mister Sparky ElectricElectrical | 70.6Tier 3 · Mixed modeled alignment | +0.9 ptsTarget-market demand | -0.4 ptsTerritory quality | Moderate evidence confidence |
Conditions that changed the analysis
What mattered most in San Antonio, Texas
Large metropolitan employment and city business activity support broad local business demand
This relationship affected 10 concepts and added 1.2 points on average among those exposed. Local evidence: Health care and social assistance receipts or revenue in 2022: 18,827,098,000 usd. [4] [8]
Office service and flex space carries a rent premium and limited availability relative to warehouse-distribution space
This relationship affected 8 concepts and reduced 0.7 points on average among those exposed. Local evidence: Overall industrial vacancy, asking rent, leasing, and absorption in Q2 2026: vacancy rate: 11.1; asking rent: 8.83; ytd leasing sqft: 2,090,407; ytd net absorption sqft: 899,260 percent usd per sqft per year and square feet. [14] [15]
San Antonio's population increased 8.0 percent from the 2020 estimate base to 2025, and the 2024 ACS counted 30,082 housing units built in 2020 or later
Growth expands the household and business base, but it does not establish uniform walk-in traffic, route productivity, property availability, or site suitability. Current industrial-format scarcity, high occupancy in tracked shopping centers, active Loop 1604 construction, submarket variation, and property-specific soil and foundation conditions alter how that growth can be served. [4] [5] [14] [16] [18] [26]
Evidence behind the city mechanisms
Large metropolitan employment and city business activity support broad local business demand1 modeled effect
Recent population and housing growth expand the addressable household-service base1 modeled effect
Expansive-clay and slab-foundation conditions can create foundation, inspection, and under-slab service demand1 modeled effect
City and military procurement ecosystems create institutional account and referral pathways3 local facts · 2 modeled effects · 2 sources
- Professional and business services employment in June 2026: 159,300 jobs [8]
- Government employment in June 2026: 184,600 jobs [8]
- Joint Base San Antonio operational contracting scope: mission partner organizations: 267; procurement categories: supplies, services, construction, small business support, plans and programs support organizations and categories [12]
Office service and flex space carries a rent premium and limited availability relative to warehouse-distribution space1 modeled effect
Active Loop 1604 North construction creates route and access risk along the affected corridor1 modeled effect
Industrial vacancy, retail availability, corridor construction, and overlay rules vary materially by submarket1 modeled effect
Compare all assessed concepts
Local impact by franchise concept
14 concepts shown. Expand a concept to see the score-changing factors and their modeled drivers; the full audit ledger stays collapsed.
City Wide
Initial investment: $229,729–$410,730
Rank sensitivity: Stable
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +3.4 pts | |
| Referral ecosystem |
| +0.7 pts |
| Territory quality |
| -0.1 pts |
| Net local movement | +4.12 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +3.4 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.7 |
| Territory quality | -0.1 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 74.12 |
| Published local-market alignment | 74.1 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +3.4 pts
- Tested rank range
- #1–#1
Jan-Pro International
Initial investment: $130,000–$421,500
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +2.9 pts | |
| Territory quality |
| -0.3 pts |
| Referral ecosystem |
| +0.2 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +2.75 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +2.9 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.2 |
| Territory quality | -0.3 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.75 |
| Published local-market alignment | 72.8 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.9 pts
- Tested rank range
- #2–#4
ActionCOACH
Initial investment: $71,668–$303,513
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +2.1 pts | |
| Referral ecosystem |
| +0.6 pts |
| Territory quality |
| -0.1 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +2.60 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +2.1 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.6 |
| Territory quality | -0.1 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.60 |
| Published local-market alignment | 72.6 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.1 pts
- Tested rank range
- #2–#4
HomeSmiles
Initial investment: $148,110–$201,800
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +2.8 pts | |
| Referral ecosystem |
| +0.6 pts |
| Territory quality |
| -0.4 pts |
| Real estate and site feasibility |
| -0.4 pts |
| Net local movement | +2.59 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +2.8 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.4 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.6 |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.59 |
| Published local-market alignment | 72.6 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Adequate
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.8 pts
- Tested rank range
- #2–#5
FASTSIGNS
Initial investment: $231,226–$386,285
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +2.6 pts | |
| Real estate and site feasibility |
| -0.8 pts |
| Territory quality |
| -0.5 pts |
| Referral ecosystem |
| +0.3 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +1.62 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +2.6 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.8 |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.3 |
| Territory quality | -0.5 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.62 |
| Published local-market alignment | 71.6 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.6 pts
- Tested rank range
- #5–#14
Pillar To Post Home Inspectors
Initial investment: $102,690–$134,290
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +1.6 pts | |
| Territory quality |
| -0.3 pts |
| Property replacement-cycle demand |
| +0.3 pts |
| Transportation, routing, and parking | Temporary route disruption EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +1.48 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.6 |
| Property replacement-cycle demand | +0.3 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.3 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.48 |
| Published local-market alignment | 71.5 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.6 pts
- Tested rank range
- #3–#8
ZOOM DRAIN
Initial investment: $266,250–$570,500
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +1.3 pts | |
| Real estate and site feasibility |
| -0.8 pts |
| Property replacement-cycle demand |
| +0.6 pts |
| Territory quality |
| -0.5 pts |
| Referral ecosystem |
| +0.4 pts |
| Net local movement | +1.05 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.3 |
| Property replacement-cycle demand | +0.6 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.8 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.4 |
| Territory quality | -0.5 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.05 |
| Published local-market alignment | 71.0 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.3 pts
- Tested rank range
- #6–#10
Aire Serv
Initial investment: $113,308–$271,708
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +1.4 pts | |
| Real estate and site feasibility |
| -0.8 pts |
| Property replacement-cycle demand |
| +0.8 pts |
| Territory quality |
| -0.4 pts |
| Net local movement | +1.05 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.4 |
| Property replacement-cycle demand | +0.8 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.8 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.05 |
| Published local-market alignment | 71.0 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Adequate
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.4 pts
- Tested rank range
- #7–#10
Mr. Rooter
Initial investment: $152,900–$298,675
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +1.3 pts | |
| Real estate and site feasibility |
| -0.6 pts |
| Property replacement-cycle demand |
| +0.6 pts |
| Territory quality |
| -0.4 pts |
| Net local movement | +0.89 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.3 |
| Property replacement-cycle demand | +0.6 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.6 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.89 |
| Published local-market alignment | 70.9 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.3 pts
- Tested rank range
- #8–#10
Mister Sparky Electric
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand |
| +0.9 pts |
| Property replacement-cycle demand |
| +0.5 pts |
| Territory quality |
| -0.4 pts |
| Real estate and site feasibility |
| -0.4 pts |
| Transportation, routing, and parking | Temporary route disruption EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +0.64 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.9 |
| Property replacement-cycle demand | +0.5 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.4 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.64 |
| Published local-market alignment | 70.6 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +0.9 pts
- Tested rank range
- #7–#11
Tiger Adjusters
Initial investment: $43,050–$159,500
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Target-market demand | +0.6 pts | |
| Territory quality |
| -0.2 pts |
| Net local movement | +0.41 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.6 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.2 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.41 |
| Published local-market alignment | 70.4 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Adequate
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +0.6 pts
- Tested rank range
- #6–#12
Workout Anytime
Initial investment: $1,060,850–$1,840,550
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Territory quality |
| -0.8 pts |
| Target-market demand |
| +0.7 pts |
| Net local movement | -0.10 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.7 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | -0.8 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 69.90 |
| Published local-market alignment | 69.9 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Territory quality -0.8 pts
- Tested rank range
- #11–#14
Rainbow International Restoration
Initial investment: $185,336–$351,900
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Real estate and site feasibility |
| -0.8 pts |
| Referral ecosystem |
| +0.5 pts |
| Territory quality |
| -0.4 pts |
| Property replacement-cycle demand |
| +0.2 pts |
| Target-market demand |
| +0.1 pts |
| Property replacement-cycle demand | Moisture and foundation service demand EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | -0.36 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.1 |
| Property replacement-cycle demand | +0.2 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.8 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.5 |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 69.64 |
| Published local-market alignment | 69.6 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Real estate and site feasibility -0.8 pts
- Tested rank range
- #11–#13
PuroClean
Initial investment: $54,575–$262,145
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
| Local factor | Modeled drivers | Impact |
|---|---|---|
| Real estate and site feasibility |
| -0.8 pts |
| Referral ecosystem |
| +0.5 pts |
| Territory quality |
| -0.4 pts |
| Property replacement-cycle demand |
| +0.2 pts |
| Transportation, routing, and parking | Temporary route disruption EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | -0.50 pts | |
Net uses full-precision effects; displayed factor and driver rows are rounded.
Franchise evidence
Source material assessed
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | Not applicable to this operating model |
| Property replacement-cycle demand | +0.2 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | -0.8 |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.5 |
| Territory quality | -0.4 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 69.50 |
| Published local-market alignment | 69.5 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Adequate
- Factor Research Coverage
- Strong
- Franchise-profile completeness
- Limited
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Real estate and site feasibility -0.8 pts
- Tested rank range
- #11–#14
No franchise concepts match the selected filters.
Worked score example
How we calculated City Wide
This example uses the same ledger shown for every concept and must reconcile exactly to the published score.
Full score ledger
Every factor is classified so a displayed zero is not mistaken for a score-changing effect.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +3.4 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Measured; no meaningful local adjustment |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not applicable to this operating model |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.7 |
| Territory quality | -0.1 |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 74.12 |
| Published local-market alignment | 74.1 |
Factor calculations use full precision. Contributions and published scores are displayed to one decimal place; ranking order uses the full-precision score.
Factor impact
Which local conditions changed scores or rankings?
We neutralized one factor at a time, recalculated every score, and then measured both absolute score movement and changes in rank order.
Target-market demand
We tested how much of the city’s theoretical customer and business demand remained usable after operating friction.
Why concepts react differently
We applied a measurable adjustment to 13 of 14 concepts. When we neutralized the factor and recalculated the table, 13 concepts changed position. FASTSIGNS moved from #5 to #14, the largest movement among concepts directly affected by this factor.
What we observed
- Resident Population Estimate On July 1, 20251,548,422 people
- Population Change From The April 2020 Estimate Base To July 20258 percent
- Estimated Households554,581 households
Concepts helped most
Property replacement-cycle demand
We compared the age and condition of relevant property systems with the services each concept is actually equipped to provide.
Why concepts react differently
We applied a measurable adjustment to 7 of 14 concepts. When we neutralized the factor and recalculated the table, 3 concepts changed position. Aire Serv moved from #8 to #10, the largest movement among concepts directly affected by this factor.
What we observed
- Housing Units Built From 1970 Through 2009units: 344,907; share: 54.82 housing units and percent of total
- Housing Units Built From 1990 Through 2009units: 164,395; share: 26.13 housing units and percent of total
- Foundation Repair Permit And Engineering Requirementspermit required: yes; double fee for work before permit: yes; professional engineer guidance and inspection required: yes requirements
Concepts helped most
Real estate and site feasibility
We applied site and operating-base constraints only to concepts requiring comparable storefront, production, warehouse, or fleet space.
Why concepts react differently
We applied a measurable adjustment to 8 of 14 concepts. When we neutralized the factor and recalculated the table, 9 concepts changed position. HomeSmiles moved from #4 to #2, the largest movement among concepts directly affected by this factor.
What we observed
- Overall Industrial Vacancy, Asking Rent, Leasing, And Absorption In Q2 2026vacancy rate: 11.1; asking rent: 8.83; ytd leasing sqft: 2,090,407; ytd net absorption sqft: 899,260 percent usd per sqft per year and square feet
- Office Service And Flex Inventory, Vacancy, Rent, Leasing, And Construction In Q2 2026inventory sqft: 10,783,592; vacant sqft: 864,493; vacancy rate: 8; weighted net asking rent: 12.49; ytd leasing sqft: 196,344; ytd net absorption sqft: -45,103; under construction sqft: 210,088 square feet percent and usd per sqft per year
- Industrial Vacancy Rate Range Across Reported San Antonio Submarketsminimum: 1.9; minimum submarket: Far Northwest; maximum: 25.7; maximum submarket: Far North Central percent
Concepts challenged most
Referral ecosystem
We tested whether the local professional and institutional referral ecosystem materially separated the assessed concepts.
Why concepts react differently
We applied a measurable adjustment to 8 of 14 concepts. When we neutralized the factor and recalculated the table, 8 concepts changed position. ZOOM DRAIN moved from #7 to #10, the largest movement among concepts directly affected by this factor.
Concepts helped most
Territory quality
We measured whether the territory structure could support the required customer density, service radius, and operating model.
Why concepts react differently
We applied a measurable adjustment to 14 of 14 concepts. When we neutralized the factor and recalculated the table, 4 concepts changed position. HomeSmiles moved from #4 to #3, the largest movement among concepts directly affected by this factor.
What we observed
- Loop 1604 North Expansion Scopebudget: 1,400,000,000; corridor length: 23; segments: 6 usd miles and segments
- Gc 1 Hill Country Gateway Corridor Design Controls And Setback Thresholdscorridor reach: IH-10 corridor with a major-highway node at Loop 1604; setback applicability distance from ih10 right of way: 90; minimum front setback along ih10: 60; minimum side setback: 20; other controls: landscaping, parking screening, fencing, building materials, exterior colors feet and requirement categories
- Industrial Vacancy Rate Range Across Reported San Antonio Submarketsminimum: 1.9; minimum submarket: Far Northwest; maximum: 25.7; maximum submarket: Far North Central percent
Concepts challenged most
- Competitive environmentNo material score adjustment
- Labor and staffing frictionNo material score adjustment
- Transportation, routing, and parkingNo material score adjustment
- Sales and customer acquisitionNo material score adjustment
- Regulatory and operating frictionNo material score adjustment
Rank stability
Which positions depend most on individual assumptions?
The line shows the best and worst rank reached when one factor was removed from every concept. A narrow range indicates a more stable position.
Neutralizing a factor removes it from every concept. A concept can move down even when its own score improves because competitors may benefit more.
Score-changing factors
Factors that changed the calculated scores
The graph includes the top 14 concepts by local-alignment score. Only nonzero score contributions are plotted. A factor is removed when every displayed concept received 0.0 points from it. Hover or focus a concept name to highlight all of its remaining data points.
View the chart data as a table
| Concept | Target-market demand | Property replacement-cycle demand | Real estate and site feasibility | Referral ecosystem | Territory quality |
|---|---|---|---|---|---|
| #1 City Wide | +3.4 pts | — | — | +0.7 pts | -0.1 pts |
| #2 Jan-Pro International | +2.9 pts | — | — | +0.2 pts | -0.3 pts |
| #3 ActionCOACH | +2.1 pts | — | — | +0.6 pts | -0.1 pts |
| #4 HomeSmiles | +2.8 pts | — | -0.4 pts | +0.6 pts | -0.4 pts |
| #5 FASTSIGNS | +2.6 pts | — | -0.8 pts | +0.3 pts | -0.5 pts |
| #6 Pillar To Post Home Inspectors | +1.6 pts | +0.3 pts | — | — | -0.3 pts |
| #7 ZOOM DRAIN | +1.3 pts | +0.6 pts | -0.8 pts | +0.4 pts | -0.5 pts |
| #8 Aire Serv | +1.4 pts | +0.8 pts | -0.8 pts | — | -0.4 pts |
| #9 Mr. Rooter | +1.3 pts | +0.6 pts | -0.6 pts | — | -0.4 pts |
| #10 Mister Sparky Electric | +0.9 pts | +0.5 pts | -0.4 pts | — | -0.4 pts |
| #11 Tiger Adjusters | +0.6 pts | — | — | — | -0.2 pts |
| #12 Workout Anytime | +0.7 pts | — | — | — | -0.8 pts |
| #13 Rainbow International Restoration | +0.1 pts | +0.2 pts | -0.8 pts | +0.5 pts | -0.4 pts |
| #14 PuroClean | — | +0.2 pts | -0.8 pts | +0.5 pts | -0.4 pts |
Interpretation
How to interpret the result
City Wide, Jan-Pro International, ActionCOACH led because their operating requirements captured more of the local support from target-market demand while remaining less exposed to real estate and site feasibility. The same city condition can help one operating model and constrain another, so score differences should be read through each concept's factor pattern rather than as a universal franchise-quality verdict. The ordering is most assumption-sensitive for FASTSIGNS, Pillar To Post Home Inspectors, ZOOM DRAIN; their ranks move more widely when individual factors are neutralized.
Local evidence assessed for modeling
Category comparisons
Best franchise categories we assessed in San Antonio, Texas
Category summaries are shown only when at least two concepts qualified. Two-concept comparisons are explicitly labeled as limited.
Limited comparison: Restoration franchise opportunities assessed in San Antonio, Texas
2 Restoration concepts qualified for comparison, with scores ranging from 69.5 to 69.6. Rainbow International Restoration ranked highest at 69.6. Referral ecosystem added 0.5 points on average among the affected concepts. Real estate and site feasibility reduced the exposed concepts by 0.8 points on average.
Interpret cautiously: A 0.1-point spread is too small to support a strong brand-level conclusion from city alignment alone.
- Concepts compared
- 2
- Score range
- 69.5–69.6
- Category average
- 69.6
Metric registry
The 39 local metrics behind this analysis
The registry shows each public metric’s raw value, period, geography, source, and its actual role in the compiled analysis.
View all local metrics
| Metric | Raw value | Period | Geography | Role in analysis | Source |
|---|---|---|---|---|---|
| Resident population estimate on July 1, 2025 | 1,548,422people | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Used in scoring | [4] |
| Population change from the April 2020 estimate base to July 2025 | 8percent | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Used in scoring | [4] |
| Estimated households | 554,581households | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Used in scoring | [4] |
| Owner-occupied housing-unit rate | 52.2percent of occupied housing units | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Context only | [4] |
| Land area in 2020 | 498.84square miles | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Context only | [4] |
| Mean travel time to work | 24.5minutes | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas workers age 16 and over | Context only | [4] |
| Health care and social assistance receipts or revenue in 2022 | 18,827,098,000usd | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Used in scoring | [4] |
| Total retail sales in 2022 | 34,277,501,000usd | July 1, 2025 population estimate; 2020-2024 ACS-derived characteristics; 2022 business receipts | San Antonio, Texas | Context only | [4] |
| Estimated total housing units in 2024 | 629,160housing units | 2024 American Community Survey 1-year estimates | San Antonio, Texas | Context only | [5] |
| Housing units built in 2020 or later | 30,082housing units | 2024 American Community Survey 1-year estimates | San Antonio, Texas housing stock | Used in scoring | [5] |
| Share of housing units built in 2020 or later | 4.78percent of housing units | 2024 American Community Survey 1-year estimates | San Antonio, Texas housing stock | Context only | [5] |
| Housing units built before 1960 | units: 114,474; share: 18.19housing units and percent of total | 2024 American Community Survey 1-year estimates | San Antonio, Texas housing stock | Context only | [5] |
| Housing units built from 1970 through 2009 | units: 344,907; share: 54.82housing units and percent of total | 2024 American Community Survey 1-year estimates | San Antonio, Texas housing stock | Used in scoring | [5] |
| Housing units built from 1990 through 2009 | units: 164,395; share: 26.13housing units and percent of total | 2024 American Community Survey 1-year estimates | San Antonio, Texas housing stock | Used in scoring | [5] |
| Owner-occupied share of occupied housing units in 2024 | owner occupied units: 295,530; occupied units: 568,979; share: 51.94housing units and percent | 2024 American Community Survey 1-year estimates | San Antonio, Texas | Used in scoring | [6] |
| Workers driving alone to work in 2024 | workers: 506,465; all workers: 742,336; share: 68.23workers and percent | 2024 American Community Survey 1-year estimates | San Antonio, Texas workers age 16 and over | Context only | [7] |
| Workers working from home in 2024 | workers: 82,573; all workers: 742,336; share: 11.12workers and percent | 2024 American Community Survey 1-year estimates | San Antonio, Texas workers age 16 and over | Context only | [7] |
| Total nonfarm employment in June 2026 | 1,196,800jobs | June 2026 preliminary labor-force and nonfarm-employment data extracted July 31, 2026 | San Antonio-New Braunfels, Texas | Used in scoring | [8] |
| Professional and business services employment in June 2026 | 159,300jobs | June 2026 preliminary labor-force and nonfarm-employment data extracted July 31, 2026 | San Antonio-New Braunfels, Texas | Used in scoring | [8] |
| Education and health services employment in June 2026 | 183,400jobs | June 2026 preliminary labor-force and nonfarm-employment data extracted July 31, 2026 | San Antonio-New Braunfels, Texas | Used in scoring | [8] |
| Government employment in June 2026 | 184,600jobs | June 2026 preliminary labor-force and nonfarm-employment data extracted July 31, 2026 | San Antonio-New Braunfels, Texas | Supports modeled relationship | [8] |
| Unemployment rate in June 2026 | 4.8percent not seasonally adjusted preliminary | June 2026 preliminary labor-force and nonfarm-employment data extracted July 31, 2026 | San Antonio-New Braunfels, Texas | Context only | [8] |
| Mean hourly wage across all occupations compared with the national mean | san antonio msa: 28.58; united states: 32.66usd per hour | May 2024 | San Antonio-New Braunfels, Texas | Context only | [9] |
| Mean hourly wages for selected franchise-relevant occupational groups compared with national means | food preparation and serving: san antonio msa: 15.1, united states: 17.32; building and grounds cleaning and maintenance: san antonio msa: 16.34, united states: 19.01; office and administrative support: san antonio msa: 22.35, united states: 24.12; construction and extraction: san antonio msa: 25.08, united states: 30.73; installation maintenance and repair: san antonio msa: 27.17, united states: 29.63usd per hour | May 2024 | San Antonio-New Braunfels, Texas | Context only | [9] |
| Institution-reported regional healthcare and biosciences ecosystem scale | economic contribution: 43,000,000,000; employment share: 20; university connected employees: 10,000usd percent and employees | Current institutional and regional-sector description published in July 2026 | San Antonio healthcare and biosciences ecosystem | Used in scoring | [10] |
| Joint Base San Antonio personnel, mission partners, locations, and managed infrastructure | full time personnel: 80,000; mission partners minimum: 250; geographic locations: 11; managed infrastructure value: 37,000,000,000people entities locations and usd | July-August 2024 institutional scale | Joint Base San Antonio | Context only | [11] |
| Joint Base San Antonio operational contracting scope | mission partner organizations: 267; procurement categories: supplies, services, construction, small business support, plans and programs supportorganizations and categories | Current contracting guidance accessed August 2026 | Joint Base San Antonio 502d Contracting Squadron | Supports modeled relationship | [12] |
| City vendor registration and covered service categories | registration system: San Antonio e-Procurement System (SAePS); covered services: janitorial, landscaping, electrical, plumbing, HVAC; credential target: within 48 business hours after validationprocess and categories | Current vendor-registration guidance accessed August 2026 | City of San Antonio | Supports modeled relationship | [13] |
| Overall industrial vacancy, asking rent, leasing, and absorption in Q2 2026 | vacancy rate: 11.1; asking rent: 8.83; ytd leasing sqft: 2,090,407; ytd net absorption sqft: 899,260percent usd per sqft per year and square feet | Second quarter and year-to-date 2026 | San Antonio industrial market | Used in scoring | [14] [15] |
| Office service and flex inventory, vacancy, rent, leasing, and construction in Q2 2026 | inventory sqft: 10,783,592; vacant sqft: 864,493; vacancy rate: 8; weighted net asking rent: 12.49; ytd leasing sqft: 196,344; ytd net absorption sqft: -45,103; under construction sqft: 210,088square feet percent and usd per sqft per year | Second quarter and year-to-date 2026 | San Antonio office service and flex market | Used in scoring | [14] |
| Industrial vacancy-rate range across reported San Antonio submarkets | minimum: 1.9; minimum submarket: Far Northwest; maximum: 25.7; maximum submarket: Far North Centralpercent | Second quarter and year-to-date 2026 | San Antonio industrial market submarkets | Used in scoring | [14] |
| Retail occupancy, tracked inventory, and 2025 deliveries | occupancy rate: 95.3; tracked inventory sqft: 49,600,000; new and expanded deliveries sqft: 561,000; anchor share of new space: 66percent and square feet | Year-end 2025 | San Antonio multi-tenant shopping centers of at least 25,000 square feet | Used in scoring | [16] |
| Loop 1604 North Expansion scope | budget: 1,400,000,000; corridor length: 23; segments: 6usd miles and segments | Current project scope accessed August 2026 | Loop 1604 North Expansion in northern Bexar County | Used in scoring | [17] [18] |
| Loop 1604 North Expansion segment completion schedule | segment 1: 2,026; segment 2: 2,028; segment 3: 2,026; segment 4: 2,028; segment 5: 2,028; segment 6: 2,029estimated completion year | Current segment schedule accessed August 2026 | Loop 1604 North Expansion segments 1-6 | Conditional relationship | [18] [19] |
| SAWS water and wastewater impact-fee components per equivalent dwelling unit | water supply: 2,592; water delivery flow: 1,368; water system development: low elevation: 1,510, middle elevation: 1,744, high elevation: 2,027; wastewater treatment: medio creek: 1,527, clouse leon creek: 1,105; wastewater collection: medio creek: 1,836, upper medina: 1,702, lower medina: 768, upper collection: 4,436, middle collection: 2,792, lower collection: 1,138usd per equivalent dwelling unit | Fee schedule effective July 1, 2024 | Applicable SAWS water and wastewater systems | Context only | [20] [2] |
| GC-1 Hill Country Gateway Corridor design controls and setback thresholds | corridor reach: IH-10 corridor with a major-highway node at Loop 1604; setback applicability distance from ih10 right of way: 90; minimum front setback along ih10: 60; minimum side setback: 20; other controls: landscaping, parking screening, fencing, building materials, exterior colorsfeet and requirement categories | Current overlay guidance accessed August 2026 | GC-1 Hill Country Gateway Corridor | Used in scoring | [21] [22] [23] |
| Foundation-repair permit and engineering requirements | permit required: yes; double fee for work before permit: yes; professional engineer guidance and inspection required: yesrequirements | Revision effective April 7, 2025 | City of San Antonio | Used in scoring | [24] |
| Under-slab plumbing repair inspection and engineering requirements | city plumbing inspection or engineer letter: yes; structural evaluation required unless exception met: yes; tunneling safety requirements: yesrequirements | Revision effective April 2025 | City of San Antonio | Used in scoring | [25] |
| Expansive-clay volume change can affect slab-on-grade foundations | UT San Antonio research evaluated void-space technology intended to isolate slab-on-grade foundations from expansive-soil volume change.documented engineering mechanism | Undated repository record accessed August 2026 | Slab-on-grade foundations on expansive clay; local property exposure requires site confirmation | Conditional relationship | [26] [1] |
How to use the ranking
What the model can and cannot establish
- Scores measure local operating alignment, not expected financial performance or franchise-system quality.
- Citywide evidence may not describe the exact site or territory ultimately offered.
- Conditional effects are shown for diligence but do not change the published score until their applicability is established.
Methodology
How the local-alignment ranking is calculated
Measure the city
Collect reusable local metrics with source, period, geography, and confidence fields.
Profile each operating model
Map each franchise to controlled operating attributes and local sensitivities.
Apply scoreable effects
Score only effects whose applicability is established at the report’s current geographic and operating scope.
Preserve conditional effects
Keep location- or territory-dependent issues visible for diligence without automatically changing the score.
Test rank sensitivity
Remove one factor at a time from every concept and rerank using full-precision scores.
Generate public output
Create the ranking, factor-status ledger, visuals, metric registry, and automated quality report from the same data.
How the common baseline becomes a city-specific score
Every concept starts from the same 70.0 reference point, so differences come only from modeled local interactions. In this city, City Wide reached 74.12 after target-market demand +3.4 pts, referral ecosystem +0.7 pts, and territory quality -0.1 pts. The current model caps total local movement at ±18.0 points. The score is not a percentage, probability, or estimate of investment quality.
Score tiers
How factor rows are classified
“Best” means the strongest modeled local operating alignment among the franchise concepts assessed on this page.
Model governance
How this report is calculated and corrected
Calculation controls
- Model designer
- Thomas Jepsen
No concept’s final score is manually raised or lowered after calculation. Reports are checked for source scope, classification, arithmetic, unsupported claims, duplication, and readability before publication.
Model history
Model updates are versioned and dated, documenting material changes to scoring, evidence handling, methodology, governance, and presentation across published reports.
Corrections policy
Corrected source, geography, or operating-profile evidence triggers a full compiler rerun so every dependent score and visual is recalculated.
Source registry
Local evidence supporting this report
The city page keeps the local sources used for its visible findings and metrics. Franchise-source provenance stays with the underlying franchise research rather than being duplicated across every city page.
- 1The Utility Delta: A Structural Audit of Ten U.S. MarketsInternal or supplied research; not publicly accessible.
Used for: Expansive-clay volume change can affect slab-on-grade foundations
- 2Structural Constraints and Hidden Costs: A Forensic Municipal AuditInternal or supplied research; not publicly accessible.
Used for: SAWS water and wastewater impact-fee components per equivalent dwelling unit
- 3Franchise data - 2 - riverside through charlotte(6).csvInternal or supplied research; not publicly accessible.
- 4QuickFacts: San Antonio city, Texas
Used for: Resident population estimate on July 1, 2025, Population change from the April 2020 estimate base to July 2025, Estimated households, Owner-occupied housing-unit rate, and Land area in 2020
- 5ACS 2024 1-Year Detailed Table B25034: Year Structure Built
Used for: Estimated total housing units in 2024, Housing units built in 2020 or later, Share of housing units built in 2020 or later, Housing units built before 1960, and Housing units built from 1970 through 2009
- 6ACS 2024 1-Year Detailed Table B25003: Tenure
Used for: Owner-occupied share of occupied housing units in 2024
- 7ACS 2024 1-Year Detailed Table B08301: Means of Transportation to Work
Used for: Workers driving alone to work in 2024 and Workers working from home in 2024
- 8San Antonio-New Braunfels, TX Economy at a Glance
Used for: Total nonfarm employment in June 2026, Professional and business services employment in June 2026, Education and health services employment in June 2026, Government employment in June 2026, and Unemployment rate in June 2026
- 9Occupational Employment and Wages in San Antonio-New Braunfels — May 2024
Used for: Mean hourly wage across all occupations compared with the national mean and Mean hourly wages for selected franchise-relevant occupational groups compared with national means
- 10How UT San Antonio is fueling the state's workforce of the future
Used for: Institution-reported regional healthcare and biosciences ecosystem scale
- 11Joint Base San Antonio, 502d Air Base Wing welcomes new commander
Used for: Joint Base San Antonio personnel, mission partners, locations, and managed infrastructure
- 12Doing Business with the 502d Contracting Squadron at Joint Base San Antonio
Used for: Joint Base San Antonio operational contracting scope
- 13Become a Vendor
Used for: City vendor registration and covered service categories
- 14San Antonio Industrial MarketBeat Q2 2026
Used for: Overall industrial vacancy, asking rent, leasing, and absorption in Q2 2026, Office service and flex inventory, vacancy, rent, leasing, and construction in Q2 2026, and Industrial vacancy-rate range across reported San Antonio submarkets
- 15San Antonio Industrial Figures Q2 2026
Used for: Overall industrial vacancy, asking rent, leasing, and absorption in Q2 2026
- 16Herb Weitzman weighs in: Texas retail is firing on all cylinders
Used for: Retail occupancy, tracked inventory, and 2025 deliveries
- 17Loop 1604 North Expansion
Used for: Loop 1604 North Expansion scope
- 18Loop 1604 North Expansion: Project segments
Used for: Loop 1604 North Expansion scope and Loop 1604 North Expansion segment completion schedule
- 19Loop 1604 North Expansion: Traffic impacts
Used for: Loop 1604 North Expansion segment completion schedule
- 20Developer Impact Fees
Used for: SAWS water and wastewater impact-fee components per equivalent dwelling unit
- 21Zoning Overlays
Used for: GC-1 Hill Country Gateway Corridor design controls and setback thresholds
- 22Hill Country Gateway Corridor District Plan Site Development Standards
Used for: GC-1 Hill Country Gateway Corridor design controls and setback thresholds
- 23RID 2025-001: Setbacks in Corridor Overlay Districts
Used for: GC-1 Hill Country Gateway Corridor design controls and setback thresholds
- 24Information Bulletin 172: Residential and Commercial Foundation Repair Permits
Used for: Foundation-repair permit and engineering requirements
- 25Information Bulletin 176: Plumbing Installation and Inspections / Repairs Within Tunneling Below Foundations
Used for: Under-slab plumbing repair inspection and engineering requirements
- 26An Evaluation of Using Void Box for Slab-On-Grade Foundation on Expansive Clay
Used for: Expansive-clay volume change can affect slab-on-grade foundations
Before contacting a franchisor
Complete the next layer of due diligence
- Confirm the exact protected territory and neighboring units.
- Review the current Franchise Disclosure Document.
- Validate local staffing, licensing, insurance, and service-base assumptions.
- Obtain location, vehicle, buildout, or working-capital estimates.
- Speak with current and former franchisees.
- Build a candidate-specific financial scenario.
Apply the analysis to your situation
Review how these market findings apply to your budget, role, and proposed territory.
The city score does not include your experience, capital structure, time commitment, financing, or exact territory.















































































