70.7 average across 2 concepts
Local operating-model alignment analysis
Best Franchise Opportunities We Assessed in Pittsburgh, Pennsylvania
We compared 14 franchise concepts for Pittsburgh, Pennsylvania. Local business demand was a leading positive mechanism. Legacy-system service complexity 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
0.9 points average among 10 affected concepts
0.6 points average reduction among 7 affected concepts
Tested rank range spans 7 positions
Executive conclusion
What the ranking means for Pittsburgh, Pennsylvania
City Wide, ActionCOACH, and FASTSIGNS 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 0.9 points on average. One important asymmetry was that the same local condition supported replacement and repair demand while also creating legacy-system service complexity. 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 | 72.7Tier 2 · Favorable modeled alignment | +1.9 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
| 2 | ActionCOACHBusiness coachingInvestment: $71,668–$303,513 | 72.2Tier 2 · Favorable modeled alignment | +1.5 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
| 3 | FASTSIGNSSigns and graphicsInvestment: $231,226–$386,285 | 72.0Tier 2 · Favorable modeled alignment | +1.7 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
| 4 | Jan-Pro InternationalCommercial cleaningInvestment: $130,000–$421,500 | 71.8Tier 3 · Mixed modeled alignment | +1.6 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
| 5 | HomeSmilesProperty maintenance servicesInvestment: $148,110–$201,800 | 71.6Tier 3 · Mixed modeled alignment | +1.0 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
| 6 | Rainbow International RestorationRestorationInvestment: $185,336–$351,900 | 70.7Tier 3 · Mixed modeled alignment | +0.5 ptsReferral ecosystem | -0.4 ptsLabor and staffing friction | Moderate evidence confidence |
| 7 | PuroCleanRestorationInvestment: $54,575–$262,145 | 70.7Tier 3 · Mixed modeled alignment | +0.6 ptsReferral ecosystem | -0.4 ptsLabor and staffing friction | Moderate evidence confidence |
| 8 | ZOOM DRAINDrain and sewer serviceInvestment: $266,250–$570,500 | 70.7Tier 3 · Mixed modeled alignment | +0.7 ptsProperty replacement-cycle demand | -0.8 ptsLabor and staffing friction | Moderate evidence confidence |
| 9 | Pillar To Post Home InspectorsHome inspectionInvestment: $102,690–$134,290 | 70.3Tier 3 · Mixed modeled alignment | +0.3 ptsProperty replacement-cycle demand | -0.1 ptsLabor and staffing friction | Moderate evidence confidence |
| 10 | Tiger AdjustersPublic insurance adjustingInvestment: $43,050–$159,500 | 70.2Tier 3 · Mixed modeled alignment | +0.2 ptsTarget-market demand | No material negative local adjustment | Moderate evidence confidence |
Conditions that changed the analysis
What mattered most in Pittsburgh, Pennsylvania
City households and a large county employment and establishment base support broad local account demand
This relationship affected 10 concepts and added 0.9 points on average among those exposed. Local evidence: Employer establishments in the primary county containing Pittsburgh: 33,812 establishments. [6]
Large pre-1980 and pre-1940 housing cohorts support replacement demand while increasing diagnostic and trade complexity
The same local condition created complementary effects: replacement and repair demand supported exposed concepts while legacy-system service complexity constrained others. [5] [7]
asset-light-b2b
This operating-model cluster separated from the broader set because its exposure to local support and constraints differed. The strongest positive factor was target-market demand, while the main constraint was property replacement-cycle demand. [6] [4] [17] [16] [3] [1] [18]
Evidence behind the city mechanisms
City households and a large county employment and establishment base support broad local account demand1 modeled effect
Large pre-1980 and pre-1940 housing cohorts support replacement demand while increasing diagnostic and trade complexity3 local facts · 2 modeled effects · 2 sources
- Total housing units in the 2024 ACS 1-year estimate: 167,913 housing units [5]
- Share of charted housing units constructed in 1939 or earlier: 46.3 percent of charted housing units [7]
- Multifamily rental share of new construction over the decade described by the 2022 assessment: 90 percent of new construction [7]
Large university and health-system institutions create concentrated professional and institutional referral ecosystems3 local facts · 2 modeled effects · 2 sources
- University of Pittsburgh Pittsburgh-campus headcount enrollment in Fall 2025: 31,237 students [16]
- University of Pittsburgh Pittsburgh-campus employees in Fall 2025: 14,888 employees [16]
- Carnegie Mellon University reported students, faculty, and staff in Fall 2025: students: 16,582; faculty: 1,615; staff: 5,164 people by role [17]
Designated Smart Loading Zones add time-limited curb rules and location-specific payment requirements for service stops1 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 |
| +1.9 pts |
| Referral ecosystem |
| +0.8 pts |
| Net local movement | +2.65 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.9 |
| 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 included in the score |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.8 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.65 |
| Published local-market alignment | 72.7 |
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 +1.9 pts
- Tested rank range
- #1–#1
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 |
| +1.5 pts |
| Referral ecosystem |
| +0.7 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +2.16 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.5 |
| 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 included in the score |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.7 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.16 |
| Published local-market alignment | 72.2 |
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 +1.5 pts
- Tested rank range
- #2–#4
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 |
| +1.7 pts |
| Referral ecosystem |
| +0.3 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +2.03 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.7 |
| 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 included in the score |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.3 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.03 |
| Published local-market alignment | 72.0 |
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 +1.7 pts
- Tested rank range
- #2–#6
Jan-Pro International
Initial investment: $130,000–$421,500
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 |
| +1.6 pts |
| Referral ecosystem |
| +0.2 pts |
| Sales and customer acquisition | Institutional procurement-cycle friction EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +1.81 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.6 |
| 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 included in the score |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.2 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.81 |
| Published local-market alignment | 71.8 |
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 +1.6 pts
- Tested rank range
- #3–#8
HomeSmiles
Initial investment: $148,110–$201,800
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 |
| +1.0 pts |
| Referral ecosystem |
| +0.6 pts |
| Net local movement | +1.60 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.0 |
| 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 included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.6 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 71.60 |
| 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
- Adequate
- Source-evidence confidence
- Strong
- Geographic applicability
- Limited
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.0 pts
- Tested rank range
- #5–#5
Rainbow International Restoration
Initial investment: $185,336–$351,900
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 |
|---|---|---|
| Referral ecosystem |
| +0.5 pts |
| Property replacement-cycle demand |
| +0.5 pts |
| Labor and staffing friction |
| -0.4 pts |
| Net local movement | +0.72 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | Not applicable to this operating model |
| Property replacement-cycle demand | +0.5 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.4 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.5 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.72 |
| Published local-market alignment | 70.7 |
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
- Referral ecosystem +0.5 pts
- Tested rank range
- #2–#9
PuroClean
Initial investment: $54,575–$262,145
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 |
|---|---|---|
| Referral ecosystem |
| +0.6 pts |
| Property replacement-cycle demand |
| +0.5 pts |
| Labor and staffing friction |
| -0.4 pts |
| Transportation, routing, and parking | Route and curb productivity pressure EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +0.71 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | Not applicable to this operating model |
| Property replacement-cycle demand | +0.5 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.4 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.6 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.71 |
| Published local-market alignment | 70.7 |
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
- Referral ecosystem +0.6 pts
- Tested rank range
- #3–#10
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 |
|---|---|---|
| Labor and staffing friction |
| -0.8 pts |
| Property replacement-cycle demand |
| +0.7 pts |
| Referral ecosystem |
| +0.4 pts |
| Target-market demand |
| +0.4 pts |
| Transportation, routing, and parking | Route and curb productivity pressure EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +0.69 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.4 |
| Property replacement-cycle demand | +0.7 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.8 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | +0.4 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.69 |
| Published local-market alignment | 70.7 |
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
- Labor and staffing friction -0.8 pts
- Tested rank range
- #6–#11
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 |
|---|---|---|
| Property replacement-cycle demand |
| +0.3 pts |
| Target-market demand |
| +0.1 pts |
| Labor and staffing friction |
| -0.1 pts |
| Net local movement | +0.33 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.1 |
| Property replacement-cycle demand | +0.3 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.1 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.33 |
| Published local-market alignment | 70.3 |
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
- Property replacement-cycle demand +0.3 pts
- Tested rank range
- #6–#12
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 |
| +0.2 pts |
| Net local movement | +0.22 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.2 |
| 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 included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.22 |
| Published local-market alignment | 70.2 |
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 +0.2 pts
- Tested rank range
- #6–#13
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 |
|---|---|---|
| Labor and staffing friction |
| -0.9 pts |
| Property replacement-cycle demand |
| +0.7 pts |
| Target-market demand |
| +0.3 pts |
| Transportation, routing, and parking | Route and curb productivity pressure EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +0.11 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.3 |
| Property replacement-cycle demand | +0.7 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.9 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.11 |
| Published local-market alignment | 70.1 |
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
- Labor and staffing friction -0.9 pts
- Tested rank range
- #9–#12
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 |
|---|---|---|
| Labor and staffing friction |
| -0.9 pts |
| Property replacement-cycle demand |
| +0.7 pts |
| Target-market demand |
| +0.3 pts |
| Transportation, routing, and parking | Route and curb productivity pressure EvidenceConditional — applicability must be confirmed | Not scored |
| Net local movement | +0.05 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +0.3 |
| Property replacement-cycle demand | +0.7 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.9 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.05 |
| Published local-market alignment | 70.0 |
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
- Labor and staffing friction -0.9 pts
- Tested rank range
- #10–#13
Workout Anytime
Initial investment: $1,060,850–$1,840,550
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local factors only. Evidence links open the underlying city finding.
No material scored local adjustment was identified for this concept.
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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | Not applicable to this operating model |
| 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 included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 70.00 |
| Published local-market alignment | 70.0 |
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
- 0.0 pts
- Tested rank range
- #10–#14
Mister Sparky Electric
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 |
|---|---|---|
| Labor and staffing friction |
| -1.0 pts |
| Property replacement-cycle demand |
| +0.6 pts |
| Net local movement | -0.34 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | Not applicable to this operating model |
| Property replacement-cycle demand | +0.6 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -1.0 |
| Transportation, routing, and parking | Depends on the specific site, territory, or operating condition |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Not included in the score |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 69.66 |
| Published local-market alignment | 69.7 |
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
- Labor and staffing friction -1.0 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 confused with missing, conditional, or non-applicable evidence.
| Neutral model baseline | 70.0 |
|---|---|
| Target-market demand | +1.9 |
| 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 included in the score |
| Sales and customer acquisition | Depends on the specific site, territory, or operating condition |
| Referral ecosystem | +0.8 |
| Territory quality | Depends on the specific site, territory, or operating condition |
| Regulatory and operating friction | Depends on the specific site, territory, or operating condition |
| Full-precision calculated score | 72.65 |
| Published local-market alignment | 72.7 |
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 10 of 14 concepts. When we neutralized the factor and recalculated the table, 9 concepts changed position. FASTSIGNS moved from #3 to #7, the largest movement among concepts directly affected by this factor.
What we observed
- Resident Population Estimate On July 1, 2025307,632 people
- Estimated Households In The 2020 2024 Period138,188 households
- Employer Establishments In The Primary County Containing Pittsburgh33,812 establishments
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, 8 concepts changed position. ZOOM DRAIN moved from #8 to #11, the largest movement among concepts directly affected by this factor.
Concepts helped most
Labor and staffing friction
We compared each concept’s frontline and specialist staffing requirements with the local labor environment.
Why concepts react differently
We applied a measurable adjustment to 7 of 14 concepts. When we neutralized the factor and recalculated the table, 8 concepts changed position. Mister Sparky Electric moved from #14 to #11, the largest movement among concepts directly affected by this factor.
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. Rainbow International Restoration moved from #6 to #9, the largest movement among concepts directly affected by this factor.
Concepts helped most
- Competitive environmentNo material score adjustment
- Transportation, routing, and parkingNo material score adjustment
- Real estate and site feasibilityNo material score adjustment
- Sales and customer acquisitionNo material score adjustment
- Territory qualityNo 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.
Original factor comparison
How each factor affected the highest-rated franchise concepts
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 | Labor and staffing friction | Referral ecosystem |
|---|---|---|---|---|
| #1 City Wide | +1.9 pts | — | — | +0.8 pts |
| #2 ActionCOACH | +1.5 pts | — | — | +0.7 pts |
| #3 FASTSIGNS | +1.7 pts | — | — | +0.3 pts |
| #4 Jan-Pro International | +1.6 pts | — | — | +0.2 pts |
| #5 HomeSmiles | +1.0 pts | — | — | +0.6 pts |
| #6 Rainbow International Restoration | — | +0.5 pts | -0.4 pts | +0.5 pts |
| #7 PuroClean | — | +0.5 pts | -0.4 pts | +0.6 pts |
| #8 ZOOM DRAIN | +0.4 pts | +0.7 pts | -0.8 pts | +0.4 pts |
| #9 Pillar To Post Home Inspectors | +0.1 pts | +0.3 pts | -0.1 pts | — |
| #10 Tiger Adjusters | +0.2 pts | — | — | — |
| #11 Mr. Rooter | +0.3 pts | +0.7 pts | -0.9 pts | — |
| #12 Aire Serv | +0.3 pts | +0.7 pts | -0.9 pts | — |
| #13 Workout Anytime | — | — | — | — |
| #14 Mister Sparky Electric | — | +0.6 pts | -1.0 pts | — |
Interpretation
How to interpret the result
City Wide, ActionCOACH, FASTSIGNS led because their operating requirements captured more of the local support from target-market demand while remaining less exposed to labor and staffing friction. 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, Jan-Pro International, Rainbow International Restoration; their ranks move more widely when individual factors are neutralized.
Category comparisons
Best franchise categories we assessed in Pittsburgh, Pennsylvania
Category summaries are shown only when at least two concepts qualified. Two-concept comparisons are explicitly labeled as limited.
Best Restoration franchise opportunities we assessed in Pittsburgh, Pennsylvania
2 Restoration concepts qualified for comparison, with scores ranging from 70.7 to 70.7. Rainbow International Restoration ranked highest at 70.7. Referral ecosystem added 0.6 points on average among the affected concepts. Labor and staffing friction reduced the exposed concepts by 0.4 points on average.
Interpret cautiously: A 0.0-point spread is too small to support a strong brand-level conclusion from city alignment alone.
- Concepts compared
- 2
- Score range
- 70.7–70.7
- Category average
- 70.7
Metric registry
The 26 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 | 307,632people | July 1, 2025 population estimate; 2020-2024 ACS characteristics; 2022 economic census measures | Pittsburgh, Pennsylvania | Used in scoring | [4] |
| Population change from the April 2020 estimate base to July 2025 | 1.5percent | July 1, 2025 population estimate; 2020-2024 ACS characteristics; 2022 economic census measures | Pittsburgh, Pennsylvania | Context only | [4] |
| Estimated households in the 2020-2024 period | 138,188households | July 1, 2025 population estimate; 2020-2024 ACS characteristics; 2022 economic census measures | Pittsburgh, Pennsylvania | Used in scoring | [4] |
| Owner-occupied housing unit rate | 47.7percent of occupied housing units | July 1, 2025 population estimate; 2020-2024 ACS characteristics; 2022 economic census measures | Pittsburgh, Pennsylvania | Context only | [4] |
| Persons in poverty | 20.1percent of population | July 1, 2025 population estimate; 2020-2024 ACS characteristics; 2022 economic census measures | Pittsburgh, Pennsylvania | Context only | [4] |
| Total housing units in the 2024 ACS 1-year estimate | 167,913housing units | 2024 American Community Survey 1-year estimates and 2020 Decennial Census | Pittsburgh, Pennsylvania | Supports modeled relationship | [5] |
| Employer establishments in the primary county containing Pittsburgh | 33,812establishments | Calendar year 2023 business establishments, employment, payroll, and 2025 population estimate | Allegheny County, Pennsylvania | Used in scoring | [6] |
| Employment in employer establishments in the primary county containing Pittsburgh | 709,774jobs | Calendar year 2023 business establishments, employment, payroll, and 2025 population estimate | Allegheny County, Pennsylvania | Used in scoring | [6] |
| Housing units constructed in 1939 or earlier | 66,149housing units | American Community Survey and CoStar data assembled for the January 2022 assessment | Pittsburgh, Pennsylvania | Supports modeled relationship | [7] [1] |
| Share of charted housing units constructed in 1939 or earlier | 46.3percent of charted housing units | American Community Survey and CoStar data assembled for the January 2022 assessment | Pittsburgh, Pennsylvania | Supports modeled relationship | [7] |
| Share of charted housing units constructed before 1980 | 83.2percent of charted housing units | American Community Survey and CoStar data assembled for the January 2022 assessment | Pittsburgh, Pennsylvania | Supports modeled relationship | [7] [1] |
| Multifamily rental share of new construction over the decade described by the 2022 assessment | 90percent of new construction | American Community Survey and CoStar data assembled for the January 2022 assessment | Pittsburgh, Pennsylvania | Supports modeled relationship | [7] |
| University of Pittsburgh Pittsburgh-campus headcount enrollment in Fall 2025 | 31,237students | Fall Term 2025 and fiscal year 2025 | University of Pittsburgh, Pittsburgh campus | Supports modeled relationship | [16] |
| University of Pittsburgh Pittsburgh-campus employees in Fall 2025 | 14,888employees | Fall Term 2025 and fiscal year 2025 | University of Pittsburgh, Pittsburgh campus | Supports modeled relationship | [16] |
| Carnegie Mellon University reported students, faculty, and staff in Fall 2025 | students: 16,582; faculty: 1,615; staff: 5,164people by role | Fall 2025 | Carnegie Mellon University; main campus in Pittsburgh | Supports modeled relationship | [17] |
| UPMC reported system employment and facilities | employees: 100,000; hospitals more than: 40; outpatient sites: 800system scale metrics | Calendar year and fiscal year 2025 figures | UPMC, headquartered in Pittsburgh | Supports modeled relationship | [18] |
| Mean hourly wages for selected occupational groups | all occupations: 31.36; food preparation and serving: 16.46; healthcare support: 17.66; building and grounds cleaning and maintenance: 18.69; construction and extraction: 32.06; installation maintenance and repair: 29.13; office and administrative support: 23.44usd per hour | May 2025 | Pittsburgh, Pennsylvania MSA | Context only | [8] [2] |
| Pittsburgh-area wage differences from national means for selected occupational groups | all occupations: -2.18; food preparation and serving: -1.4; healthcare support: -1.96; building and grounds cleaning and maintenance: -0.97; construction and extraction: 0.64; installation maintenance and repair: -1.31; office and administrative support: -1.35usd per hour difference pittsburgh minus us | May 2025 | Pittsburgh, Pennsylvania MSA | Context only | [8] |
| Current Smart Loading Zone operating rules | grace period minutes: 15; enforcement days: Monday-Saturday; enforcement hours: 8:00-18:00; post grace registration and payment required: yes; rates vary by neighborhood: yesrule attributes | Current operating rules accessed August 2026; pilot results January 2022 through December 2024 | Pittsburgh Smart Loading Zones | Conditional relationship | [9] [3] |
| Reported Smart Loading Zone pilot outcomes from January 2022 through December 2024 | turnover change: 70; average park duration change: -60; maximum share using grace period: 85percent | Current operating rules accessed August 2026; pilot results January 2022 through December 2024 | Pittsburgh Smart Loading Zone pilot locations | Conditional relationship | [9] |
| Exterior work on a property in a city-designated historic district requires historic review and a Certificate of Appropriateness | yesboolean | Current process accessed August 2026 | City-designated historic properties and districts in Pittsburgh | Conditional relationship | [10] [3] |
| Property and project conditions that can trigger a geotechnical report | landslide prone overlay: new construction, multi story addition; undermined area overlay: new construction or enlargement subject to project type and overburden rules; steep slope: cut or fill slope over 25 percent unless certifiedrule attributes | Current zoning guidance accessed August 2026 | Applicable Pittsburgh parcels and projects | Conditional relationship | [11] [12] [13] [3] |
| Nonresidential monthly stormwater rate per equivalent residential unit | 11.5usd per eru per month | Rates effective March 8, 2026 | Pittsburgh Water customers | Context only | [14] |
| Illustrative monthly Pittsburgh Water bill for a commercial customer using 13,000 gallons with a 1-inch meter and eight ERUs | prior rate bill: 425.81; rate 2026 bill: 491.83; change percent: 15.5usd per month and percent | Illustrative class bills for 2026 rates effective March 8, 2026 | Typical Pittsburgh Water commercial customer defined by the utility | Context only | [15] |
| Pittsburgh office market directional measures in Q2 2026 | quarterly net absorption sqft: 297,000; vacancy change qoq bps: 0; vacancy change yoy bps: 20; asking rent change qoq percent: 1.5; asking rent change yoy percent: 1.3; construction pipeline sqft: 0market metrics | Second quarter 2026 | Pittsburgh office market | Conditional relationship | [19] |
| Pittsburgh industrial market measures in Q2 2026 | vacancy percent: 5.4; availability percent: 6.2; average asking rent usd per sqft: 7.73; quarterly net absorption sqft: -68,000; construction pipeline sqft: 959,000market metrics | Second quarter 2026 | Pittsburgh industrial market | Conditional relationship | [20] |
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 that apply without an unresolved site, territory, customer, or project gate.
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 72.65 after target-market demand +1.9 pts and referral ecosystem +0.8 pts. The current model caps total local movement at ±18.0 points. The score is not a percentage, probability, or estimate of investment quality.
Precision and materiality
Calculations use full-precision values. Published scores and factor contributions display one decimal place, while ranks use full precision. Effects smaller than 0.1 points are identified as below the publication threshold rather than presented as a meaningful zero.
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. Before this template is activated, the report is reviewed for source scope, classification, arithmetic, unsupported claims, duplication, and readability.
Model history
- Model 0.9.0-calibration · August 19, 2026Added compiler-derived decision intelligence and observation usage mapping., Changed factor sensitivity and channel counterfactuals to full model reruns., Added data-dependent city content signals while preserving legacy public report fields., and Added model-owned semantic compatibility gates and backward-compatible channel-level evidence attribution.
Corrections policy
Corrected source, geography, or operating-profile evidence triggers a full compiler rerun so every dependent score and visual is recalculated.
Source registry
Evidence represented in this report
Each source identifies its period, scope, and the local metrics it supports. Internal or supplied research is not presented as independently accessible evidence.
- 1United States Structural Inefficiency and CRE Arbitrage AuditInternal or supplied research; not publicly accessible.
Used for: Housing units constructed in 1939 or earlier and Share of charted housing units constructed before 1980
- 2Jurisdictional Friction and Structural Capital Constraints: A Forensic Audit of Municipal Operating EnvironmentsInternal or supplied research; not publicly accessible.
Used for: Mean hourly wages for selected occupational groups
- 3Franchise city and neighborhood operating-condition recordsInternal or supplied research; not publicly accessible.
Used for: Current Smart Loading Zone operating rules, Exterior work on a property in a city-designated historic district requires historic review and a Certificate of Appropriateness, and Property and project conditions that can trigger a geotechnical report
- 4QuickFacts: Pittsburgh city, Pennsylvania
Used for: Resident population estimate on July 1, 2025, Population change from the April 2020 estimate base to July 2025, Estimated households in the 2020-2024 period, Owner-occupied housing unit rate, and Persons in poverty
- 5Pittsburgh city, Pennsylvania - Census Bureau Profile
Used for: Total housing units in the 2024 ACS 1-year estimate
- 6QuickFacts: Allegheny County, Pennsylvania
Used for: Employer establishments in the primary county containing Pittsburgh and Employment in employer establishments in the primary county containing Pittsburgh
- 7Pittsburgh Housing Needs Assessment
Used for: Housing units constructed in 1939 or earlier, Share of charted housing units constructed in 1939 or earlier, Share of charted housing units constructed before 1980, and Multifamily rental share of new construction over the decade described by the 2022 assessment
- 8Occupational Employment and Wages in Pittsburgh — May 2025
Used for: Mean hourly wages for selected occupational groups and Pittsburgh-area wage differences from national means for selected occupational groups
- 9Smart Loading Zones
Used for: Current Smart Loading Zone operating rules and Reported Smart Loading Zone pilot outcomes from January 2022 through December 2024
- 10Apply for Historic Review
Used for: Exterior work on a property in a city-designated historic district requires historic review and a Certificate of Appropriateness
- 11Geotechnical Reports
Used for: Property and project conditions that can trigger a geotechnical report
- 12Environmental Review
Used for: Property and project conditions that can trigger a geotechnical report
- 13Planning Application and Process
Used for: Property and project conditions that can trigger a geotechnical report
- 14Rates
Used for: Nonresidential monthly stormwater rate per equivalent residential unit
- 15Our Water Future
Used for: Illustrative monthly Pittsburgh Water bill for a commercial customer using 13,000 gallons with a 1-inch meter and eight ERUs
- 16Institutional Research and Analytics: By the Numbers
Used for: University of Pittsburgh Pittsburgh-campus headcount enrollment in Fall 2025 and University of Pittsburgh Pittsburgh-campus employees in Fall 2025
- 17Our Data
Used for: Carnegie Mellon University reported students, faculty, and staff in Fall 2025
- 18By the Numbers: UPMC Facts and Figures
Used for: UPMC reported system employment and facilities
- 19Pittsburgh Office Figures Q2 2026
Used for: Pittsburgh office market directional measures in Q2 2026
- 20Pittsburgh Industrial Figures Q2 2026
Used for: Pittsburgh industrial market measures in Q2 2026
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.















































































