Most impactful relationship #1
Local condition7,962.1Population density
Operating exposureLocal business demand
14 of 14 concepts affected100% of concepts assessed
FASTSIGNSJAN-PRO InternationalCity Wide Facility SolutionsActionCOACH+10
Local operating-model alignment analysis
Best Franchise Opportunities We Assessed in Minneapolis, Minnesota
Compare 14 franchise concepts in Minneapolis and see how 7,962.1 residents per square mile population density shaped local-alignment scores.
What “best” means in this ranking“Best” means the strongest modeled local operating alignment among the franchise concepts assessed on this page. It does not estimate earnings or determine which franchise is best for a particular candidate.
Bottom line
City Wide Facility Solutions ranks first among the concepts assessed for Minneapolis, Minnesota
We compared 14 franchise concepts against Minneapolis's local operating conditions. Minneapolis' 7,962.1 residents per square mile population density created one of the strongest positive local signals for concepts exposed to local business demand. [1] Minneapolis' 47.7% owner-occupied housing share created one of the more important local constraints for concepts exposed to low homeownership concentration. [1] [2]
City Wide Facility Solutions scored 72.15. It leads FASTSIGNS by 0.16 points. The documented population density in Minneapolis is 7,962.1 residents per square mile. For City Wide Facility Solutions, this was the largest positive contribution, adding 1.11 points through local business demand. [1] Across the Minneapolis-St. Paul-Bloomington, MN-WI Metropolitan Statistical Area, the mean wage for building and grounds occupations was $21.68/hour in May 2025. For City Wide Facility Solutions, this was the largest negative contribution, reducing the score by 0.10 points through high local occupational wage cost environment. [6] The largest direct difference versus FASTSIGNS came from Minneapolis' 57.0% share of housing in buildings with two or more units, which contributed +0.88 points to City Wide Facility Solutions versus +0.46 points to FASTSIGNS. [3]
Evidence chain
- Local condition: The documented population density in Minneapolis is 7,962.1 residents per square mile. [1]
- Why it matters to this model: City Wide Facility Solutions's operating model depends on recurring commercial accounts, giving it direct exposure to local business demand.
- Modeled consequence: The model assigned +1.11 points through local business demand.
What this means: this is a deterministic comparison of documented local conditions against resolved operating-model exposures. It is not an earnings forecast, investment recommendation, or franchise-quality rating.
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.
Rankings use full-precision scores.Displayed scoring values use two decimal places. Identical displayed scores can therefore have different ranks, and close results should be treated as effectively similar.
| Rank | Franchise | Alignment and tier | Largest advantage | Largest constraint | Evidence confidence |
|---|---|---|---|---|---|
| 1 | City Wide Facility SolutionsIntegrated Facility Management | 72.15Tier 2 · Favorable modeled alignment | +1.11 pts7,962.1 residents per square mile population density | -0.10 pts$21.68/hour mean wage for building and grounds occupations | Moderate evidence confidence |
| 2 | FASTSIGNSSigns & GraphicsInvestment: $231,226–$386,285 Item 7 source | 71.99Tier 3 · Mixed modeled alignment | +1.35 pts7,962.1 residents per square mile population density | -0.18 pts$21.68/hour mean wage for building and grounds occupations | Moderate evidence confidence |
| 3 | JAN-PRO InternationalFranchise Consulting TrainingInvestment: $130,000–$421,500 Item 7 source | 71.71Tier 3 · Mixed modeled alignment | +1.23 pts7,962.1 residents per square mile population density | -0.23 pts7,962.1 residents per square mile population density | Moderate evidence confidence |
| 4 | ActionCOACHBusiness CoachingInvestment: $71,668–$303,513 Item 7 source | 71.10Tier 3 · Mixed modeled alignment | +1.06 pts7,962.1 residents per square mile population density | -0.21 pts7,962.1 residents per square mile population density | Moderate evidence confidence |
| 5 | Rainbow International RestorationProperty RestorationInvestment: $185,336–$351,900 Item 7 source | 70.66Tier 3 · Mixed modeled alignment | +0.52 pts57.0% of housing in buildings with two or more units | -0.36 ptsSnow Emergencies trigger three days of special street-parking rules… | Moderate evidence confidence |
| 6 | PuroCleanProperty RestorationInvestment: $54,575–$262,145 Item 7 source | 70.59Tier 3 · Mixed modeled alignment | +0.68 pts57.0% of housing in buildings with two or more units | -0.36 ptsSnow Emergencies trigger three days of special street-parking rules… | High evidence confidence |
| 7 | Pillar To Post Home InspectorsHome InspectionInvestment: $102,690–$134,290 Item 7 source | 69.60Tier 3 · Mixed modeled alignment | +0.65 pts21.5% recent-mover share | -0.73 pts47.7% owner-occupied housing share | Moderate evidence confidence |
| 8 | Tiger AdjustersPublic Adjusting & Claims AdvocacyInvestment: $43,050–$159,500 Item 7 source | 69.53Tier 3 · Mixed modeled alignment | +0.23 pts7,962.1 residents per square mile population density | -0.65 pts47.7% owner-occupied housing share | Moderate evidence confidence |
| 9 | Workout AnytimeFull-Service FitnessInvestment: $1,060,850–$1,840,550 Item 7 source | 69.20Tier 3 · Mixed modeled alignment | +0.13 pts7,962.1 residents per square mile population density | -0.33 ptsSnow Emergencies trigger three days of special street-parking rules… | Moderate evidence confidence |
| 10 | ZOOM DRAINPlumbing & Drain ServicesInvestment: $266,250–$570,500 Item 7 source | 68.81Tier 3 · Mixed modeled alignment | +0.40 pts7,962.1 residents per square mile population density | -0.75 pts39.8% detached single-family housing share | Moderate evidence confidence |
Cross-concept impact analysis
The local conditions that moved scores most
A city condition changes a franchise score only when it intersects with a relevant operating-model exposure. The center shows average effect when applied; the surrounding ring shows how broadly that relationship reached across the concepts assessed.
Most impactful relationship #2
Local condition47.7%Owner-occupied housing share
Operating exposureLow homeownership concentration
9 of 14 concepts affected64% of concepts assessed
Mister Sparky ElectricPillar To Post Home InspectorsTiger AdjustersHomeSmiles+5
Most impactful relationship #3
Local condition57.0%Housing in buildings with two or more units
Operating exposureMultifamily housing concentration
11 of 14 concepts affected79% of concepts assessed
City Wide Facility SolutionsPuroCleanJAN-PRO InternationalRainbow International Restoration+7
Most impactful relationship #4
Local conditionSnow Emergencies trigger three days of sp…
Operating exposureWinter parking and access pressure
11 of 14 concepts affected79% of concepts assessed
ZOOM DRAINMr. RooterHomeSmilesPuroClean+7
Most impactful relationship #5
Local condition39.8%Detached single-family housing share
Operating exposureLow detached single-family housing share
5 of 14 concepts affected36% of concepts assessed
HomeSmilesAire ServZOOM DRAINMr. Rooter+1
Details for 7,962.1 residents per square mile population density Ă— Local business demand
Relationship #17,962.1 residents per square mile population density Local business demand
Minneapolis evidence7,962.1 residents per square mile [1]39.8% detached single-family housing share
Model exposureLocal business demand
Most relevant modeled attributes: recurring commercial demand, local business density dependence, and sales intensive.
Average effect+0.55 ptsTotal absolute modeled influence7.767 ptsLargest single effect+1.35 ptsEvidence confidenceModerate
Effect across concepts
FASTSIGNSSigns & Graphics+1.35 pts
JAN-PRO InternationalFranchise Consulting Training+1.23 pts
City Wide Facility SolutionsIntegrated Facility Management+1.11 pts
ActionCOACHBusiness Coaching+1.06 pts
HomeSmilesRecurring Property Maintenance+0.54 pts
PuroCleanProperty Restoration+0.51 pts
Mr. RooterPlumbing & Drain Services+0.41 pts
ZOOM DRAINPlumbing & Drain Services+0.40 pts
Rainbow International RestorationProperty Restoration+0.29 pts
Aire ServHVAC+0.29 pts
Tiger AdjustersPublic Adjusting & Claims Advocacy+0.22 pts
Pillar To Post Home InspectorsHome Inspection+0.16 pts
Workout AnytimeFull-Service Fitness+0.12 pts
Mister Sparky ElectricElectrical Services+0.07 pts
Selected by total absolute modeled influence across affected concepts.Open evidence chain
Details for 47.7% owner-occupied housing share Ă— Low homeownership concentration
Relationship #247.7% owner-occupied housing share Low homeownership concentration
Minneapolis evidence47.7% [1] [2]39.8% detached single-family housing share
- United States owner-occupied housing share
- 65.2%
- Difference
- -17.5 percentage points
Model exposureLow homeownership concentration
Most relevant modeled attributes: homeownership dependency.
Average effect-0.47 ptsTotal absolute modeled influence4.235 ptsLargest single effect-0.89 ptsEvidence confidenceHigh
Effect across concepts
Mister Sparky ElectricElectrical Services-0.89 pts
Pillar To Post Home InspectorsHome Inspection-0.73 pts
Tiger AdjustersPublic Adjusting & Claims Advocacy-0.65 pts
HomeSmilesRecurring Property Maintenance-0.40 pts
Aire ServHVAC-0.36 pts
ZOOM DRAINPlumbing & Drain Services-0.36 pts
Mr. RooterPlumbing & Drain Services-0.36 pts
PuroCleanProperty Restoration-0.24 pts
Rainbow International RestorationProperty Restoration-0.24 pts
Selected by total absolute modeled influence across affected concepts.Open evidence chain
Details for 57.0% of housing in buildings with two or more units Ă— Multifamily housing concentration
Relationship #357.0% of housing in buildings with two or more units Multifamily housing concentration
Minneapolis evidence57.0% [3]39.8% detached single-family housing share
Model exposureMultifamily housing concentration
Most relevant modeled attributes: property manager sales, multi family housing dependency, and recurring commercial demand.
Average effect+0.38 ptsTotal absolute modeled influence4.160 ptsLargest single effect+0.88 ptsEvidence confidenceHigh
Effect across concepts
City Wide Facility SolutionsIntegrated Facility Management+0.88 pts
PuroCleanProperty Restoration+0.68 pts
JAN-PRO InternationalFranchise Consulting Training+0.60 pts
Rainbow International RestorationProperty Restoration+0.52 pts
FASTSIGNSSigns & Graphics+0.46 pts
Tiger AdjustersPublic Adjusting & Claims Advocacy+0.22 pts
ActionCOACHBusiness Coaching+0.20 pts
HomeSmilesRecurring Property Maintenance+0.18 pts
ZOOM DRAINPlumbing & Drain Services+0.17 pts
Aire ServHVAC+0.13 pts
Mr. RooterPlumbing & Drain Services+0.12 pts
Selected by total absolute modeled influence across affected concepts.Open evidence chain
Details for Snow Emergencies trigger three days of special street-parking rules to enable plowing and… × Winter parking and access pressure
Relationship #4Snow Emergencies trigger three days of special street-parking rules to enable plowing and… Winter parking and access pressure
Minneapolis evidenceMinneapolis' winter parking and access pressure
Model exposureWinter parking and access pressure
Most relevant modeled attributes: service vehicle required, high daily stop count, and customer parking dependency.
Average effect-0.35 ptsTotal absolute modeled influence3.814 ptsLargest single effect-0.53 ptsEvidence confidenceHigh
Effect across concepts
ZOOM DRAINPlumbing & Drain Services-0.53 pts
Mr. RooterPlumbing & Drain Services-0.53 pts
HomeSmilesRecurring Property Maintenance-0.44 pts
PuroCleanProperty Restoration-0.36 pts
Rainbow International RestorationProperty Restoration-0.36 pts
Aire ServHVAC-0.34 pts
Mister Sparky ElectricElectrical Services-0.33 pts
Pillar To Post Home InspectorsHome Inspection-0.33 pts
Workout AnytimeFull-Service Fitness-0.33 pts
Tiger AdjustersPublic Adjusting & Claims Advocacy-0.16 pts
FASTSIGNSSigns & Graphics-0.12 pts
Selected by total absolute modeled influence across affected concepts.Open evidence chain
Details for 39.8% detached single-family housing share Ă— Low detached single-family housing share
Relationship #539.8% detached single-family housing share Low detached single-family housing share
Minneapolis evidence39.8% [3] [4]39.8% detached single-family housing share
- United States detached single-family housing share
- 61.1%
- Difference
- -21.3 percentage points
Model exposureLow detached single-family housing share
Most relevant modeled attributes: single family detached dependency.
Average effect-0.76 ptsTotal absolute modeled influence3.795 ptsLargest single effect-1.24 ptsEvidence confidenceHigh
Effect across concepts
HomeSmilesRecurring Property Maintenance-1.24 pts
Aire ServHVAC-0.75 pts
ZOOM DRAINPlumbing & Drain Services-0.75 pts
Mr. RooterPlumbing & Drain Services-0.75 pts
Mister Sparky ElectricElectrical Services-0.31 pts
Selected by total absolute modeled influence across affected concepts.Open evidence chain
Modeled evidence traces
Why the same Minneapolis conditions affect franchise models differently
Each trace follows one documented local condition through resolved operating-model exposure, exact score contribution, and the resulting modeled difference. Open either image for the full-size analytical view.
Why the ranking came out this way
Why the top concepts are nearly tied
The comparison, score path, and counterfactual below all use the same contribution ledger as the published ranking.
Head-to-head
City Wide Facility Solutions vs. FASTSIGNS
The modeled gap is small enough that the two concepts should be treated as a leading cluster rather than a decisive first and second place.
| Modeled relationship | City Wide Facility Solutions | FASTSIGNS | Difference |
|---|---|---|---|
| 57.0% of housing in buildings with two or more units [3] | +0.88 pts | +0.46 pts | +0.42 pts |
| Mining, logging, and construction employment was up 7.1% year over year in July 2026. metro construction employment growth [7] | 0.00 pts | +0.28 pts | -0.28 pts |
| 7,962.1 residents per square mile population density [1] | +1.11 pts | +1.35 pts | -0.23 pts |
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions [12] | 0.00 pts | -0.12 pts | +0.12 pts |
| $21.68/hour mean wage for building and grounds occupations [6] | -0.10 pts | -0.18 pts | +0.08 pts |
Minneapolis' 57.0% share of housing in buildings with two or more units created the largest modeled gap in this head-to-head: +0.88 points for City Wide Facility Solutions versus +0.46 points for FASTSIGNS. [3]
How to interpret the leading cluster
City Wide Facility Solutions, FASTSIGNS, and JAN-PRO International gained more than the rest of the field from 7,962.1 residents per square mile population density and 57.0% of housing in buildings with two or more units through target-market demand. They were also less exposed than the rest of the field to $21.68/hour mean wage for building and grounds occupations through labor and staffing friction. The same city condition can help one operating model while constraining another, so this ranking describes local operating alignment rather than universal franchise quality. [1] [3] [6]
Contribution path
Contribution path for City Wide Facility Solutions
Baseline70.00Final72.15Net change+2.15 pts
Scored local driverRelationship effectScore after driver
57.0% of housing in buildings with two or more units [3]Multifamily housing concentration
+0.88 pts
72.00
36,071,627 passengers annual MSP airport passengers [14]Airport and aviation activity concentration
+0.16 pts
72.16
$21.68/hour mean wage for building and grounds occupations [6]High local occupational wage cost environment
-0.10 pts
72.06
View the full score ledger for City Wide Facility Solutions
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +2.25 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.10 |
| Transportation, routing, and parking | Not applicable to this operating model |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 72.154 |
| Published local-market alignment | 72.15 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Research workbench
How the Minneapolis evidence was structured
City-specific methodology views that change only when the selected city evidence or analytical workflow materially changes.
14Concepts evaluated
32Local sources used
30Primary local sources
36Local metrics
Evaluation set
Why these concepts were evaluated
This is not a ranking of every franchise that may be offered in the city.
14Concepts assessed
Concepts were included when the available operating-model evidence supported a deterministic local-sensitivity profile. Brand participation in our referral network does not affect the score.
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
70.62 average across 2 concepts
0.48 points average among 14 affected concepts
0.35 points average reduction among 11 affected concepts
Tested rank range spans 7 positions
Conditions that changed the analysis
What mattered most in Minneapolis, Minnesota
Dense customer and business demand
This relationship affected 14 concepts and added 0.56 points on average among those exposed. Local evidence: 7,962.1 residents per square mile population density. [1]
Low homeownership concentration
This relationship affected 9 concepts and reduced 0.47 points on average among those exposed. Local evidence: 47.7% owner-occupied housing share. [1] [2]
Evidence behind the city mechanisms
Dense customer and business demand1 local fact · 1 modeled effect · 1 source
Local business demandTarget-market demand
- 7,962.1 residents per square mile population density [1]
Low homeownership concentration1 local fact · 1 modeled effect · 2 sources
Low detached single-family housing share1 local fact · 1 modeled effect · 2 sources
Multifamily housing concentration1 local fact · 1 modeled effect · 1 source
Multifamily housing concentrationTarget-market demand
- 57.0% of housing in buildings with two or more units [3]
Winter parking and access friction1 modeled effect
Winter parking and access pressureTransportation, routing, and parking
Compare all assessed concepts
Local impact by franchise concept
14 concepts shown. Expand a concept to see every material score-changing relationship, with factor net shown only as secondary context; the full audit ledger stays collapsed.
#1Tier 2 · Favorable modeled alignment72.15
City Wide Facility Solutions
Advantage +1.11 pts 7,962.1 residents per square mile population densityConstraint -0.10 pts $21.68/hour mean wage for building and grounds occupations
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+2.25 pts
Constraints-0.10 pts
Net local movement+2.154 pts
Final score72.15
5 material local relationships changed this score: 4 advantages and 1 constraint.
Largest individual score driver7,962.1 residents per square mile population density+1.11 pts
Factor
Target-market demand
Factor subtotal+2.25 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population densityLargest driverRelationship test: Rank stays #1 without this driver. | +1.11 pts | ModerateEvidence |
| 57.0% of housing in buildings with two or more units | +0.88 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.16 pts | HighEvidence |
| 52.3% renter-occupied housing share | +0.10 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.10 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.10 pts | HighEvidence |
Overall local score movement+2.154 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +2.25 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.10 |
| Transportation, routing, and parking | Not applicable to this operating model |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 72.154 |
| Published local-market alignment | 72.15 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.25 pts
- Tested rank range
- #1–#2
#2Tier 3 · Mixed modeled alignment71.99
FASTSIGNS
Initial investment: $231,226–$386,285 · Item 7 evidence below
Advantage +1.35 pts 7,962.1 residents per square mile population densityConstraint -0.18 pts $21.68/hour mean wage for building and grounds occupations
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+2.29 pts
Constraints-0.30 pts
Net local movement+1.991 pts
Final score71.99
6 material local relationships changed this score: 4 advantages and 2 constraints. 1 additional scored relationship fell below the public row threshold and reconcile to +0.048 pts.
Largest individual score driver7,962.1 residents per square mile population density+1.35 pts
Factor
Target-market demand
Factor subtotal+2.29 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population densityLargest driverRelationship test: Rank stays #2 without this driver. | +1.35 pts | ModerateEvidence |
| 57.0% of housing in buildings with two or more units | +0.46 pts | HighEvidence |
| Mining, logging, and construction employment was up 7.1% year over year in July 2026. metro construction employment growth | +0.28 pts | ModerateEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.15 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.18 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.18 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.12 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.12 pts | HighEvidence |
Overall local score movement+1.991 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Item 19 — Financial Performance Representation
2 images
Additional brand source material assessed
3 sourcesFull calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +2.29 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.18 |
| Transportation, routing, and parking | -0.12 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 71.991 |
| Published local-market alignment | 71.99 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.29 pts
- Tested rank range
- #1–#3
#3Tier 3 · Mixed modeled alignment71.71
JAN-PRO International
Initial investment: $130,000–$421,500 · Item 7 evidence below
Advantage +1.23 pts 7,962.1 residents per square mile population densityConstraint -0.23 pts 7,962.1 residents per square mile population density
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+2.01 pts
Constraints-0.30 pts
Net local movement+1.706 pts
Final score71.71
6 material local relationships changed this score: 4 advantages and 2 constraints.
Largest individual score driver7,962.1 residents per square mile population density+1.23 pts
Factor
Target-market demand
Factor subtotal+2.01 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population densityLargest driverRelationship test: Rank stays #3 without this driver. | +1.23 pts | ModerateEvidence |
| 57.0% of housing in buildings with two or more units | +0.60 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.12 pts | HighEvidence |
| 52.3% renter-occupied housing share | +0.06 pts | HighEvidence |
Factor
Sales and customer acquisition
Factor subtotal-0.23 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population density | -0.23 pts | ModerateEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.07 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.07 pts | HighEvidence |
Overall local score movement+1.706 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
1 image
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +2.01 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.07 |
| Transportation, routing, and parking | Not applicable to this operating model |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | -0.23 |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 71.706 |
| Published local-market alignment | 71.71 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +2.01 pts
- Tested rank range
- #3–#4
#4Tier 3 · Mixed modeled alignment71.10
ActionCOACH
Initial investment: $71,668–$303,513 · Item 7 evidence below
Advantage +1.06 pts 7,962.1 residents per square mile population densityConstraint -0.21 pts 7,962.1 residents per square mile population density
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+1.30 pts
Constraints-0.21 pts
Net local movement+1.097 pts
Final score71.10
3 material local relationships changed this score: 2 advantages and 1 constraint. 1 additional scored relationship fell below the public row threshold and reconcile to +0.045 pts.
Largest individual score driver7,962.1 residents per square mile population density+1.06 pts
Factor
Target-market demand
Factor subtotal+1.30 pts
Factor
Sales and customer acquisition
Factor subtotal-0.21 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population density | -0.21 pts | ModerateEvidence |
Overall local score movement+1.097 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +1.30 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | Not applicable to this operating model |
| Transportation, routing, and parking | Not applicable to this operating model |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | -0.21 |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 71.097 |
| Published local-market alignment | 71.10 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.30 pts
- Tested rank range
- #2–#4
#5Tier 3 · Mixed modeled alignment70.66
Rainbow International Restoration
Initial investment: $185,336–$351,900 · Item 7 evidence below
Advantage +0.52 pts 57.0% of housing in buildings with two or more unitsConstraint -0.36 pts Snow Emergencies trigger three days of special street-parking rules…
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+1.57 pts
Constraints-0.91 pts
Net local movement+0.656 pts
Final score70.66
8 material local relationships changed this score: 5 advantages and 3 constraints. 2 additional scored relationships fell below the public row threshold and reconcile to +0.011 pts.
Largest individual score driver57.0% of housing in buildings with two or more units+0.52 pts
Factor
Target-market demand
Factor subtotal+1.15 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 57.0% of housing in buildings with two or more unitsLargest driverRelationship test: Rank stays #5 without this driver. | +0.52 pts | HighEvidence |
| 6.3% uninsured under-65 share | +0.44 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.29 pts | ModerateEvidence |
| 47.7% owner-occupied housing share | -0.24 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.11 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.36 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.36 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.30 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.27 pts | HighEvidence |
Factor
Property replacement-cycle demand
Factor subtotal+0.17 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.17 pts | ModerateEvidence |
Overall local score movement+0.656 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate advantageMapped flood or coastal flood exposureProperty replacement-cycle demand
Applicability depends on the selected floodplain
Potential candidate constraintNicollet Avenue bridge construction closureTransportation, routing, and parking
Applicability depends on the selected corridor
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +1.15 |
| Property replacement-cycle demand | +0.17 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.30 |
| Transportation, routing, and parking | -0.36 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 70.656 |
| Published local-market alignment | 70.66 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand +1.15 pts
- Tested rank range
- #5–#6
#6Tier 3 · Mixed modeled alignment70.59
PuroClean
Initial investment: $54,575–$262,145 · Item 7 evidence below
Advantage +0.68 pts 57.0% of housing in buildings with two or more unitsConstraint -0.36 pts Snow Emergencies trigger three days of special street-parking rules…
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+1.52 pts
Constraints-0.93 pts
Net local movement+0.591 pts
Final score70.59
8 material local relationships changed this score: 4 advantages and 4 constraints. 1 additional scored relationship fell below the public row threshold and reconcile to +0.043 pts.
Largest individual score driver57.0% of housing in buildings with two or more units+0.68 pts
Factor
Target-market demand
Factor subtotal+1.11 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 57.0% of housing in buildings with two or more unitsLargest driverRelationship test: Rank stays #6 without this driver. | +0.68 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.51 pts | ModerateEvidence |
| 47.7% owner-occupied housing share | -0.24 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.12 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.36 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.36 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.32 pts
Factor
Property replacement-cycle demand
Factor subtotal+0.17 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.17 pts | ModerateEvidence |
Overall local score movement+0.591 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate advantageMapped flood or coastal flood exposureProperty replacement-cycle demand
Applicability depends on the selected floodplain
Potential candidate constraintCity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintUniversity procurement vendor-onboarding frictionReferral ecosystem
Applicability depends on the selected procurement jurisdiction
Potential candidate constraintCommercial-vehicle storage restrictionsRegulatory and operating friction
Applicability depends on the selected neighborhood
Potential candidate constraintNicollet Avenue bridge construction closureTransportation, routing, and parking
Applicability depends on the selected corridor
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +1.11 |
| Property replacement-cycle demand | +0.17 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.32 |
| Transportation, routing, and parking | -0.36 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 70.591 |
| Published local-market alignment | 70.59 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- High evidence confidence
- Largest absolute effect
- Target-market demand +1.11 pts
- Tested rank range
- #6–#7
#7Tier 3 · Mixed modeled alignment69.60
Pillar To Post Home Inspectors
Initial investment: $102,690–$134,290 · Item 7 evidence below
Advantage +0.65 pts 21.5% recent-mover shareConstraint -0.73 pts 47.7% owner-occupied housing share
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.96 pts
Constraints-1.36 pts
Net local movement-0.398 pts
Final score69.60
6 material local relationships changed this score: 3 advantages and 3 constraints. 2 additional scored relationships fell below the public row threshold and reconcile to +0.029 pts.
Largest individual score driver47.7% owner-occupied housing share-0.73 pts
Factor
Target-market demand
Factor subtotal+0.14 pts
Factor
Transportation, routing, and parking
Factor subtotal-0.33 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.33 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.31 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.29 pts | HighEvidence |
Factor
Property replacement-cycle demand
Factor subtotal+0.10 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.10 pts | ModerateEvidence |
Overall local score movement-0.398 ptsThis is the accounting total after all factor subtotals and model controls.
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 19 — Financial Performance Representation
1 image
Additional brand source material assessed
2 sourcesFull calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +0.14 |
| Property replacement-cycle demand | +0.10 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.31 |
| Transportation, routing, and parking | -0.33 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 69.602 |
| Published local-market alignment | 69.60 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Transportation, routing, and parking -0.33 pts
- Tested rank range
- #7–#9
#8Tier 3 · Mixed modeled alignment69.53
Tiger Adjusters
Initial investment: $43,050–$159,500 · Item 7 evidence below
Advantage +0.23 pts 7,962.1 residents per square mile population densityConstraint -0.65 pts 47.7% owner-occupied housing share
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.48 pts
Constraints-0.96 pts
Net local movement-0.473 pts
Final score69.53
5 material local relationships changed this score: 2 advantages and 3 constraints. 1 additional scored relationship fell below the public row threshold and reconcile to +0.036 pts.
Largest individual score driver47.7% owner-occupied housing share-0.65 pts
Factor
Target-market demand
Factor subtotal-0.16 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 47.7% owner-occupied housing shareLargest driverRelationship test: Rank #8 to #7 without this driver. | -0.65 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.22 pts | ModerateEvidence |
| 57.0% of housing in buildings with two or more units | +0.22 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.16 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.16 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.15 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.15 pts | HighEvidence |
Overall local score movement-0.473 ptsThis is the accounting total after all factor subtotals and model controls.
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 19 — Financial Performance Representation
1 image
Additional brand source material assessed
1 sourceFull calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -0.16 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.15 |
| Transportation, routing, and parking | -0.16 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 69.527 |
| Published local-market alignment | 69.53 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Transportation, routing, and parking -0.16 pts
- Tested rank range
- #5–#9
#9Tier 3 · Mixed modeled alignment69.20
Workout Anytime
Initial investment: $1,060,850–$1,840,550 · Item 7 evidence below
Advantage +0.13 pts 7,962.1 residents per square mile population densityConstraint -0.33 pts Snow Emergencies trigger three days of special street-parking rules…
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.12 pts
Constraints-0.92 pts
Net local movement-0.797 pts
Final score69.20
5 material local relationships changed this score: 1 advantage and 4 constraints.
Largest individual score driverSnow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions-0.33 pts
Factor
Regulatory and operating friction
Factor subtotal-0.52 pts
Factor
Transportation, routing, and parking
Factor subtotal-0.33 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictionsLargest driverRelationship test: Rank stays #9 without this driver. | -0.33 pts | HighEvidence |
Factor
Target-market demand
Factor subtotal+0.12 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 7,962.1 residents per square mile population density | +0.12 pts | ModerateEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.08 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.08 pts | HighEvidence |
Overall local score movement-0.797 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintMapped flood or coastal flood exposureProperty replacement-cycle demand
Applicability depends on the selected floodplain
Potential candidate constraintSt. Anthony Falls historic-design reviewRegulatory and operating friction
Applicability depends on the selected historic district
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | +0.12 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.08 |
| Transportation, routing, and parking | -0.33 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | -0.52 |
| Full-precision calculated score | 69.203 |
| Published local-market alignment | 69.20 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Regulatory and operating friction -0.52 pts
- Tested rank range
- #7–#14
#10Tier 3 · Mixed modeled alignment68.81
ZOOM DRAIN
Initial investment: $266,250–$570,500 · Item 7 evidence below
Advantage +0.40 pts 7,962.1 residents per square mile population densityConstraint -0.75 pts 39.8% detached single-family housing share
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.90 pts
Constraints-2.09 pts
Net local movement-1.189 pts
Final score68.81
8 material local relationships changed this score: 3 advantages and 5 constraints. 3 additional scored relationships fell below the public row threshold and reconcile to +0.104 pts.
Largest individual score driver39.8% detached single-family housing share-0.75 pts
Factor
Target-market demand
Factor subtotal-0.43 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 39.8% detached single-family housing shareLargest driverRelationship test: Rank #10 to #9 without this driver. | -0.75 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.40 pts | ModerateEvidence |
| 47.7% owner-occupied housing share | -0.36 pts | HighEvidence |
| 57.0% of housing in buildings with two or more units | +0.17 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.53 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.53 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.45 pts
Factor
Property replacement-cycle demand
Factor subtotal+0.22 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.22 pts | ModerateEvidence |
Overall local score movement-1.189 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintNicollet Avenue bridge construction closureTransportation, routing, and parking
Applicability depends on the selected corridor
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -0.43 |
| Property replacement-cycle demand | +0.22 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.45 |
| Transportation, routing, and parking | -0.53 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 68.811 |
| Published local-market alignment | 68.81 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Transportation, routing, and parking -0.53 pts
- Tested rank range
- #10–#11
#11Tier 3 · Mixed modeled alignment68.78
Mr. Rooter
Initial investment: $152,900–$298,675 · Item 7 evidence below
Advantage +0.41 pts 7,962.1 residents per square mile population densityConstraint -0.75 pts 39.8% detached single-family housing share
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.87 pts
Constraints-2.10 pts
Net local movement-1.221 pts
Final score68.78
9 material local relationships changed this score: 4 advantages and 5 constraints. 2 additional scored relationships fell below the public row threshold and reconcile to +0.041 pts.
Largest individual score driver39.8% detached single-family housing share-0.75 pts
Factor
Target-market demand
Factor subtotal-0.46 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 39.8% detached single-family housing shareLargest driverRelationship test: Rank stays #11 without this driver. | -0.75 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.41 pts | ModerateEvidence |
| 47.7% owner-occupied housing share | -0.36 pts | HighEvidence |
| 57.0% of housing in buildings with two or more units | +0.12 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.08 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.53 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.53 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.46 pts
Factor
Property replacement-cycle demand
Factor subtotal+0.22 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.22 pts | ModerateEvidence |
Overall local score movement-1.221 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCommercial-vehicle storage restrictionsRegulatory and operating friction
Applicability depends on the selected neighborhood
Potential candidate constraintNicollet Avenue bridge construction closureTransportation, routing, and parking
Applicability depends on the selected corridor
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -0.46 |
| Property replacement-cycle demand | +0.22 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.46 |
| Transportation, routing, and parking | -0.53 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 68.779 |
| Published local-market alignment | 68.78 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Transportation, routing, and parking -0.53 pts
- Tested rank range
- #11–#12
#12Tier 3 · Mixed modeled alignment68.73
Aire Serv
Initial investment: $113,308–$271,708 · Item 7 evidence below
Advantage +0.29 pts 7,962.1 residents per square mile population densityConstraint -0.75 pts 39.8% detached single-family housing share
Rank sensitivity: Moderately sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.66 pts
Constraints-1.93 pts
Net local movement-1.268 pts
Final score68.73
8 material local relationships changed this score: 3 advantages and 5 constraints. 2 additional scored relationships fell below the public row threshold and reconcile to +0.043 pts.
Largest individual score driver39.8% detached single-family housing share-0.75 pts
Factor
Target-market demand
Factor subtotal-0.66 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 39.8% detached single-family housing shareLargest driverRelationship test: Rank stays #12 without this driver. | -0.75 pts | HighEvidence |
| 47.7% owner-occupied housing share | -0.36 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.29 pts | ModerateEvidence |
| 57.0% of housing in buildings with two or more units | +0.13 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.47 pts
Factor
Transportation, routing, and parking
Factor subtotal-0.34 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.34 pts | HighEvidence |
Factor
Property replacement-cycle demand
Factor subtotal+0.20 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.20 pts | ModerateEvidence |
Overall local score movement-1.268 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintCommercial-vehicle storage restrictionsRegulatory and operating friction
Applicability depends on the selected neighborhood
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
1 image
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Item 19 — Financial Performance Representation
1 image
Additional brand source material assessed
1 sourceFull calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -0.66 |
| Property replacement-cycle demand | +0.20 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.47 |
| Transportation, routing, and parking | -0.34 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 68.732 |
| Published local-market alignment | 68.73 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand -0.66 pts
- Tested rank range
- #10–#12
#13Tier 3 · Mixed modeled alignment68.33
Mister Sparky Electric
Advantage +0.19 pts 1951 median year structure builtConstraint -0.89 pts 47.7% owner-occupied housing share
Rank sensitivity: Highly sensitive
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.26 pts
Constraints-1.94 pts
Net local movement-1.675 pts
Final score68.33
7 material local relationships changed this score: 2 advantages and 5 constraints. 1 additional scored relationship fell below the public row threshold and reconcile to +0.006 pts.
Largest individual score driver47.7% owner-occupied housing share-0.89 pts
Factor
Target-market demand
Factor subtotal-1.13 pts
Factor
Labor and staffing friction
Factor subtotal-0.41 pts
Factor
Transportation, routing, and parking
Factor subtotal-0.33 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.33 pts | HighEvidence |
Factor
Property replacement-cycle demand
Factor subtotal+0.19 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 1951 median year structure built | +0.19 pts | ModerateEvidence |
Overall local score movement-1.675 ptsThis is the accounting total after all factor subtotals and model controls.
Potential candidate-specific adjustmentsThese relationships depend on territory, site, customer mix, project, or another candidate-specific selection. They stay outside the baseline city score until that selection is known; the model should then be rerun to produce the candidate-adjusted score.
Potential candidate constraintNicollet Avenue bridge construction closureTransportation, routing, and parking
Applicability depends on the selected corridor
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -1.13 |
| Property replacement-cycle demand | +0.19 |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.41 |
| Transportation, routing, and parking | -0.33 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | Not applicable to this operating model |
| Full-precision calculated score | 68.325 |
| Published local-market alignment | 68.33 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand -1.13 pts
- Tested rank range
- #8–#14
#14Tier 3 · Mixed modeled alignment68.30
HomeSmiles
Initial investment: $148,110–$201,800 · Item 7 evidence below
Advantage +0.54 pts 7,962.1 residents per square mile population densityConstraint -1.24 pts 39.8% detached single-family housing share
Rank sensitivity: Stable
Why it ranks here
Score-changing local relationships are grouped by factor. Each factor subtotal shows the net contribution after model controls.
Baseline70.00
Advantages+0.84 pts
Constraints-2.54 pts
Net local movement-1.701 pts
Final score68.30
8 material local relationships changed this score: 3 advantages and 5 constraints. 1 additional scored relationship fell below the public row threshold and reconcile to +0.042 pts.
Largest individual score driver39.8% detached single-family housing share-1.24 pts
Factor
Target-market demand
Factor subtotal-0.80 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| 39.8% detached single-family housing shareLargest driverRelationship test: Rank #14 to #10 without this driver. | -1.24 pts | HighEvidence |
| 7,962.1 residents per square mile population density | +0.54 pts | ModerateEvidence |
| 47.7% owner-occupied housing share | -0.40 pts | HighEvidence |
| 57.0% of housing in buildings with two or more units | +0.18 pts | HighEvidence |
| 36,071,627 passengers annual MSP airport passengers | +0.08 pts | HighEvidence |
Factor
Transportation, routing, and parking
Factor subtotal-0.44 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| Snow Emergencies trigger three days of special street-parking rules to enable plowing and emergency access. snow-emergency parking restrictions | -0.44 pts | HighEvidence |
Factor
Labor and staffing friction
Factor subtotal-0.32 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $21.68/hour mean wage for building and grounds occupations | -0.32 pts | HighEvidence |
Factor
Regulatory and operating friction
Factor subtotal-0.14 pts
| Scored local driver | Effect | Evidence |
|---|---|---|
| $16.37/hour minneapolis statutory minimum wage | -0.14 pts | HighEvidence |
Overall local score movement-1.701 ptsThis is the accounting total after all factor subtotals and model controls.
Relationship effects are shown individually. Factor net values are secondary subtotals. Any scored relationship below the public materiality threshold is reconciled in the accounting residual.
Franchise evidence
Source material assessed
Item 3 — Litigation
1 image
Item 6 — Other Fees
1 image
Item 7 — Estimated Initial Investment
2 images
Item 12 — Territory
1 image
Item 20 — Outlets and Franchise Information
1 image
Full calculation and evidence confidence
Audit layer
Full factor ledger
Full score ledger
Every factor is classified. Factor values here are net totals; the score-changing relationship table above preserves material positive and negative drivers even when they offset inside the same factor.
| Neutral model baseline | 70.00 |
|---|---|
| Target-market demand | -0.80 |
| Property replacement-cycle demand | Not applicable to this operating model |
| Competitive environment | Not included in the score |
| Labor and staffing friction | -0.32 |
| Transportation, routing, and parking | -0.44 |
| Real estate and site feasibility | Not included in the score |
| Sales and customer acquisition | Not included in the score |
| Referral ecosystem | Potential candidate-specific adjustment |
| Territory quality | Not included in the score |
| Regulatory and operating friction | -0.14 |
| Full-precision calculated score | 68.299 |
| Published local-market alignment | 68.30 |
Factor calculations use full precision. Contributions and published scores are displayed to two decimal places; ranking order uses the full-precision score.
Evidence confidence
- City Modifier Evidence
- Strong
- Factor Research Coverage
- Limited
- Franchise-profile completeness
- Strong
- Source-evidence confidence
- Strong
- Geographic applicability
- Strong
- Overall evidence confidence
- Moderate evidence confidence
- Largest absolute effect
- Target-market demand -0.80 pts
- Tested rank range
- #13–#14
No franchise concepts match the selected filters.
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.
Observed model effectMixed or model dependent
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 14 of 14 concepts. When we neutralized the factor and recalculated the table, 13 concepts changed position. Workout Anytime moved from #9 to #14, the largest movement among concepts directly affected by this factor.
Concepts adjusted14 of 14
Average among affected+0.48 pts
Average across all concepts+0.48 pts
Concepts changing rank13
What we observed
- Population Density7,962.1 residents per square mile
- Owner Occupied Housing Share47.7%
- Renter Occupied Housing Share52.3%
Concepts helped most
FASTSIGNSSigns & Graphics
+2.29 pts
City Wide Facility SolutionsIntegrated Facility Management
+2.25 pts
JAN-PRO InternationalFranchise Consulting Training
+2.01 pts
ActionCOACHBusiness Coaching
+1.30 pts
Rainbow International RestorationProperty Restoration
+1.15 pts
Concepts challenged most
Mister Sparky ElectricElectrical Services
-1.13 pts
HomeSmilesRecurring Property Maintenance
-0.80 pts
Aire ServHVAC
-0.66 pts
Mr. RooterPlumbing & Drain Services
-0.46 pts
ZOOM DRAINPlumbing & Drain Services
-0.43 pts
Observed model effectResearched; no material local effect
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, 4 concepts changed position. Pillar To Post Home Inspectors moved from #7 to #8, the largest movement among concepts directly affected by this factor.
Concepts adjusted7 of 14
Average among affected+0.18 pts
Average across all concepts+0.09 pts
Concepts changing rank4
What we observed
- Median Year Structure Built1951
Concepts helped most
ZOOM DRAINPlumbing & Drain Services
+0.22 pts
Mr. RooterPlumbing & Drain Services
+0.22 pts
Aire ServHVAC
+0.20 pts
Mister Sparky ElectricElectrical Services
+0.19 pts
PuroCleanProperty Restoration
+0.17 pts
Observed model effectMixed or model dependent
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 13 of 14 concepts. The adjustments changed absolute scores without changing the order.
Concepts adjusted13 of 14
Average among affected-0.28 pts
Average across all concepts-0.26 pts
Concepts changing rank0
What we observed
- Food Preparation And Serving Mean Hourly Wage$17.41/hour
- Mean Hourly Wage For Building And Grounds Occupations$21.68/hour
- Construction And Extraction Mean Hourly Wage$37.82/hour
Concepts challenged most
Aire ServHVAC
-0.47 pts
Mr. RooterPlumbing & Drain Services
-0.46 pts
ZOOM DRAINPlumbing & Drain Services
-0.45 pts
Mister Sparky ElectricElectrical Services
-0.41 pts
PuroCleanProperty Restoration
-0.32 pts
Observed model effectMixed or model dependent
Transportation, routing, and parking
We recalculated route-dependent models after accounting for travel corridors, parking, and the number of productive stops they require.
Why concepts react differently
We applied a measurable adjustment to 11 of 14 concepts. When we neutralized the factor and recalculated the table, 2 concepts changed position. HomeSmiles moved from #14 to #13, the largest movement among concepts directly affected by this factor.
Concepts adjusted11 of 14
Average among affected-0.35 pts
Average across all concepts-0.27 pts
Concepts changing rank2
Concepts challenged most
ZOOM DRAINPlumbing & Drain Services
-0.53 pts
Mr. RooterPlumbing & Drain Services
-0.53 pts
HomeSmilesRecurring Property Maintenance
-0.44 pts
PuroCleanProperty Restoration
-0.36 pts
Rainbow International RestorationProperty Restoration
-0.36 pts
Observed model effectEvidence incomplete
Sales and customer acquisition
We weighed the size of the prospect pool against local digital competition and the length of the relevant sales cycle.
Why concepts react differently
We applied a measurable adjustment to 2 of 14 concepts. The adjustments changed absolute scores without changing the order.
Concepts adjusted2 of 14
Average among affected-0.22 pts
Average across all concepts-0.03 pts
Concepts changing rank0
Concepts challenged most
JAN-PRO InternationalFranchise Consulting Training
-0.23 pts
ActionCOACHBusiness Coaching
-0.21 pts
Observed model effectMixed or model dependent
Regulatory and operating friction
We separated regulations that create operating burdens from those that may create demand for qualified compliance and retrofit services.
Why concepts react differently
We applied a measurable adjustment to 2 of 14 concepts. When we neutralized the factor and recalculated the table, 5 concepts changed position. Workout Anytime moved from #9 to #7, the largest movement among concepts directly affected by this factor.
Concepts adjusted2 of 14
Average among affected-0.33 pts
Average across all concepts-0.05 pts
Concepts changing rank5
What we observed
- Minneapolis Statutory Minimum Wage$16.37/hour
Concepts challenged most
Workout AnytimeFull-Service Fitness
-0.52 pts
HomeSmilesRecurring Property Maintenance
-0.14 pts
Measured but not differentiating in this concept set
- Competitive environmentNo material score adjustment
- Real estate and site feasibilityNo material score adjustment
- Referral ecosystemNo material score adjustment
- Territory qualityNo 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.
#1 City Wide Facility SolutionsStable · tested #1–#2
#2 FASTSIGNSModerately sensitive · tested #1–#3
#3 JAN-PRO InternationalStable · tested #3–#4
#4 ActionCOACHModerately sensitive · tested #2–#4
#5 Rainbow International RestorationStable · tested #5–#6
#6 PuroCleanStable · tested #6–#7
#7 Pillar To Post Home InspectorsModerately sensitive · tested #7–#9
#8 Tiger AdjustersHighly sensitive · tested #5–#9
#9 Workout AnytimeHighly sensitive · tested #7–#14
#10 ZOOM DRAINStable · tested #10–#11
#11 Mr. RooterStable · tested #11–#12
#12 Aire ServModerately sensitive · tested #10–#12
#13 Mister Sparky ElectricHighly sensitive · tested #8–#14
#14 HomeSmilesStable · tested #13–#14
Neutralizing a factor removes it from every concept. A concept can move down even when its own score improves because competitors may benefit more.
Net factor impact
Net factor totals across the highest-ranked concepts
This graph plots net factor totals for the top 14 concepts. A near-zero net can contain meaningful positive and negative scored relationships that offset each other; those underlying drivers remain visible in each franchise's expanded score explanation.
Primary source records by factorTarget-market demand: [7] [6] [3] [4] [1] [2] [5] [12] [14] [24] [23] [15]Property replacement-cycle demand: [12]Labor and staffing friction: [7] [6] [1] [2] [9] [8]Transportation, routing, and parking: [32]Referral ecosystem: [27] [28] [29]Regulatory and operating friction: [9] [17] [18] [8] [26] [30] [25] [31]
View the chart data as a table
| Concept | Target-market demand | Property replacement-cycle demand | Labor and staffing friction | Transportation, routing, and parking | Sales and customer acquisition | Regulatory and operating friction |
|---|---|---|---|---|---|---|
| #1 City Wide Facility Solutions | +2.30 pts | — | -0.10 pts | — | — | — |
| #2 FASTSIGNS | +2.30 pts | — | -0.20 pts | -0.10 pts | — | — |
| #3 JAN-PRO International | +2.00 pts | — | -0.10 pts | — | -0.20 pts | — |
| #4 ActionCOACH | +1.30 pts | — | — | — | -0.20 pts | — |
| #5 Rainbow International Restoration | +1.20 pts | +0.20 pts | -0.30 pts | -0.40 pts | — | — |
| #6 PuroClean | +1.10 pts | +0.20 pts | -0.30 pts | -0.40 pts | — | — |
| #7 Pillar To Post Home Inspectors | +0.10 pts | +0.10 pts | -0.30 pts | -0.30 pts | — | — |
| #8 Tiger Adjusters | -0.20 pts | — | -0.10 pts | -0.20 pts | — | — |
| #9 Workout Anytime | +0.10 pts | — | -0.10 pts | -0.30 pts | — | -0.50 pts |
| #10 ZOOM DRAIN | -0.40 pts | +0.20 pts | -0.50 pts | -0.50 pts | — | — |
| #11 Mr. Rooter | -0.50 pts | +0.20 pts | -0.50 pts | -0.50 pts | — | — |
| #12 Aire Serv | -0.70 pts | +0.20 pts | -0.50 pts | -0.30 pts | — | — |
| #13 Mister Sparky Electric | -1.10 pts | +0.20 pts | -0.40 pts | -0.30 pts | — | — |
| #14 HomeSmiles | -0.80 pts | — | -0.30 pts | -0.40 pts | — | -0.10 pts |
Interpretation
How to interpret the leading cluster
City Wide Facility Solutions, FASTSIGNS, and JAN-PRO International gained more than the rest of the field from 7,962.1 residents per square mile population density and 57.0% of housing in buildings with two or more units through target-market demand. They were also less exposed than the rest of the field to $21.68/hour mean wage for building and grounds occupations through labor and staffing friction. The same city condition can help one operating model while constraining another, so this ranking describes local operating alignment rather than universal franchise quality.
Local evidence assessed for modeling
Category comparisons
Best franchise categories we assessed in Minneapolis, Minnesota
Category summaries are shown only when at least two concepts qualified. Two-concept comparisons are explicitly labeled as limited.
Limited two-concept comparison
70.62Limited comparison: Property Restoration franchise opportunities assessed in Minneapolis, Minnesota
2 Property Restoration concepts qualified for comparison, with scores ranging from 70.59 to 70.66. Rainbow International Restoration ranked highest at 70.66. Target-market demand added 1.13 points on average among the affected concepts. Transportation, routing, and parking reduced the exposed concepts by 0.36 points on average.
Interpret cautiously: A 0.07-point spread is too small to support a strong brand-level conclusion from city alignment alone.
- Concepts compared
- 2
- Score range
- 70.59–70.66
- Category average
- 70.62
Rainbow International Restoration70.66
PuroClean70.59
Limited two-concept comparison
68.80Limited comparison: Plumbing & Drain Services franchise opportunities assessed in Minneapolis, Minnesota
2 Plumbing & Drain Services concepts qualified for comparison, with scores ranging from 68.78 to 68.81. ZOOM DRAIN ranked highest at 68.81. Property replacement-cycle demand added 0.22 points on average among the affected concepts. Transportation, routing, and parking reduced the exposed concepts by 0.53 points on average.
Interpret cautiously: A 0.03-point spread is too small to support a strong brand-level conclusion from city alignment alone.
- Concepts compared
- 2
- Score range
- 68.78–68.81
- Category average
- 68.80
ZOOM DRAIN68.81
Mr. Rooter68.78
Metric registry
The 36 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 |
|---|---|---|---|---|---|
| Population estimate | 430,324 | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Population change since 2020 | 0.1% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Population density | 7,962.1 residents per square mile | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Used in scoring | [1] |
| Household count | 192,734 households | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Household growth since 2020 | 5.0% | 2020 Census to 2024 estimate | Minneapolis, Minnesota | Context only | [5] |
| Housing-unit count | 216,155 housing units | 2024 ACS 1-year estimates | Minneapolis, Minnesota | Context only | [3] |
| Owner-occupied housing share | 47.7% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Used in scoring | [1] [2] |
| Renter-occupied housing share | 52.3% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Used in scoring | [1] [2] |
| Detached single-family housing share | 39.8% | 2024 ACS 1-year estimates | Minneapolis, Minnesota | Used in scoring | [3] [4] |
| Housing in buildings with two or more units | 57.0% | 2024 ACS 1-year estimates | Minneapolis, Minnesota | Used in scoring | [3] |
| Median owner-occupied home value | $362,200 | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Median household income | $80,846 | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Poverty rate | 16.0% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Recent-mover share | 21.5% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Used in scoring | [1] [2] |
| Age-65-and-older share | 11.4% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Under-18 population share | 18.8% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Uninsured under-65 share | 6.3% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Used in scoring | [1] [2] |
| Under-65 disability share | 9.8% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Broadband subscription share | 90.8% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Retail sales per capita | $19,047 per capita | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Mean commute time | 22.0 minutes | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Labor-force participation | 72.8% | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] [2] |
| Food preparation and serving mean hourly wage | $17.41/hour | May 2025 | Minneapolis-St | Used in scoring | [6] |
| Mean hourly wage for building and grounds occupations | $21.68/hour | May 2025 | Minneapolis-St | Used in scoring | [6] |
| Construction and extraction mean hourly wage | $37.82/hour | May 2025 | Minneapolis-St | Used in scoring | [6] |
| Installation, maintenance and repair mean hourly wage | $33.63/hour | May 2025 | Minneapolis-St | Used in scoring | [6] |
| Office and administrative support mean hourly wage | $27.00/hour | May 2025 | Minneapolis-St | Used in scoring | [6] |
| Metro unemployment rate | 4.4% | February-July 2026 | Minneapolis-St | Context only | [7] |
| Workers usually working from home | 26.2% | 2020-2024 ACS 5-year estimates | Minneapolis, Minnesota | Supports modeled relationship | [23] [24] |
| Median year structure built | 1951 | 2020-2024 ACS 5-year estimates | Minneapolis, Minnesota | Used in scoring | [23] |
| Accommodation and food-services sales | $2.142 billion | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Health care and social-assistance receipts | $10.260 billion | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Transportation and warehousing receipts | $2.255 billion | 2020-2024 ACS / 2025 population estimate | Minneapolis, Minnesota | Context only | [1] |
| Annual MSP airport passengers | 36,071,627 passengers | 2025 | Minneapolis-St | Used in scoring | [14] |
| University of Minnesota Twin Cities undergraduate enrollment | 32,632 undergraduates | Fall 2025 | University of Minnesota Twin Cities campus | Context only | [15] |
| Minneapolis statutory minimum wage | $16.37/hour | 2026 and scheduled 2027 rates | Minneapolis, Minnesota | Used in scoring | [8] [9] |
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.
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 broadly applicable effects
Apply fully supported relationships at full weight and otherwise scoreable research- or taxonomy-gated relationships at a reduced provisional weight.
Preserve candidate-dependent effects
Keep territory-, site-, customer-, project-, or configuration-dependent relationships outside the baseline score until the relevant candidate selections are known.
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 70.00 reference point, so differences come only from modeled local interactions. In Minneapolis, City Wide Facility Solutions reached 72.154. Target-market demand combined several local relationships for a net +2.25 points. [1] [3] Labor and staffing friction totaled -0.10 points, led by $21.68/hour mean wage for building and grounds occupations at -0.10 points. [6]
The current model caps total local movement at ±18.00 points. The score is not a percentage, probability, or estimate of investment quality.
Score calibration
How relationship effects become score adjustments
Each score-changing relationship starts with its model-defined maximum effect. The documented city-condition strength and the franchise's weighted operating exposure scale that maximum. Evidence confidence, provenance, geographic applicability, and the profile-confidence multiplier then modify the pre-cap effect. Fully supported relationships use full weight; broadly applicable relationships held back only by research or taxonomy-review gates use an additional 0.80 eligibility multiplier. Candidate-dependent site, territory, customer, project, or operating selections remain outside the baseline score until resolved. Correlation and score caps can reduce the resulting magnitude before the final contribution is added to the common baseline.
Local condition7,962.1 residents per square mile [1]7,962.1 residents per square mile population densityStrength 0.550 / 1.000
Operating exposureLocal business demandCity Wide Facility Solutions weighted operating exposureExposure 0.767 / 1.000
Model calibration+4.50 pts ceilingEvidence/applicability ×0.733 · pre-cap +1.11 ptsRelationship-specific maximum
Score effect+1.11 ptsNo post-calibration control reduced this relationshipOpen evidence chain
Worked-example calibration inputsActual model values, not generic point bands
City-condition strength0.550 / 1.000
Operating exposure0.767 / 1.000
Evidence & applicabilityĂ—0.733
Relationship ceiling4.500 pts
The model does not use one universal Minor/Moderate/Strong point table. Relationship-specific max_effect values are the actual point ceilings, so publishing generic point bands would misstate the scoring system.
Score tiers
Tier 1 · Strongest modeled alignment80.00–100.00
Tier 2 · Favorable modeled alignment72.00–<80.00
Tier 3 · Mixed modeled alignment64.00–<72.00
Tier 4 · Higher-friction modeled alignment0.00–<64.00
How factor rows are classified
Positive local adjustmentNegative local adjustmentMeasured; no meaningful local adjustmentEffect below the publication thresholdNot applicable to this operating modelPotential candidate-specific adjustmentNot included in the score
What “best” means here
“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.
- 1QuickFacts: Minneapolis city, Minnesota
Used for: Population estimate, Population change since 2020, Population density, Household count, and Owner-occupied housing share
- 2QuickFacts: United States
Used for: Owner-occupied housing share, Renter-occupied housing share, Median owner-occupied home value, Median household income, and Recent-mover share
- 3DP04: Selected Housing Characteristics — Minneapolis city, Minnesota
Used for: Housing-unit count, Detached single-family housing share, and Housing in buildings with two or more units
- 4DP04: Selected Housing Characteristics — United States
Used for: Detached single-family housing share
- 52024 Final Population and Household Estimates
Used for: Household growth since 2020
- 6Occupational Employment and Wages in Minneapolis-St. Paul-Bloomington — May 2025
Used for: Food preparation and serving mean hourly wage, Mean hourly wage for building and grounds occupations, Construction and extraction mean hourly wage, Installation, maintenance and repair mean hourly wage, and Office and administrative support mean hourly wage
- 7Minneapolis-St. Paul-Bloomington, MN-WI Economy at a Glance
Used for: Metro unemployment rate
- 8Minneapolis Minimum Wage
Used for: Minneapolis statutory minimum wage
- 9Minimum-wage rate adjusted for inflation as of Jan. 1, 2026
Used for: Minneapolis statutory minimum wage
- 10
- 11
- 12
- 13
- 14MSP Airport tops 36 million passengers in 2025
Used for: Annual MSP airport passengers
- 15Twin Cities Undergraduate Enrollment 2025
Used for: University of Minnesota Twin Cities undergraduate enrollment
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23Minneapolis, MN Facts, Statistics and Data
Used for: Workers usually working from home and Median year structure built
- 24Minneapolis metro area Facts, Statistics and Data
Used for: Workers usually working from home
- 25
- 26
- 27
- 28
- 29
- 30
- 31
- 32
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.
Disclaimer and broker disclosure: This analysis is informational and does not constitute financial, legal, accounting, or investment advice. Market-alignment scores do not predict financial performance or business success. Offers are made only through the delivery of a Franchise Disclosure Document. We may receive referral compensation from participating franchisors; compensation is not an input to the scoring model.