How to Create Your Personalized Scoring Profile on PlaceToBe AI

One of the most persistent misconceptions in commercial real estate analysis is that a good location is universally good. In reality, a site that generates exceptional returns for a fast-food franchise would be mediocre for a luxury gym, and a location that an independent bookstore would thrive in might be completely wrong for a convenience store. Location quality is inherently relative — relative to the business model, the target customer profile, the operational format, and the investment thesis.

This is why generic, one-size-fits-all location scores are fundamentally limited. A composite score of 75 out of 100 tells you very little if you don't know how that score was constructed and whether the underlying dimensions match what actually drives performance for your specific business.

PlaceToBe AI's personalized scoring profiles address this problem directly. By allowing users to configure how each scoring dimension is weighted, the platform produces rankings calibrated to your business model — not to an abstract notion of "commercial potential."

Why Generic Scoring Doesn't Work

Consider two businesses evaluating the same Paris street:

A bakery succeeds on morning foot traffic from commuters and residents. It needs a location with strong 7–10am weekday pedestrian flows, proximity to residential buildings, and easy access on foot. Transport connectivity matters, but it's the walking-accessible residential catchment that drives daily revenue. Competitive density is a concern mainly for direct bakery competitors, not general commercial activity.

A corporate fitness studio needs proximity to dense office employment, accessible transport for the post-work peak (18:00–20:00), a demographic profile skewed toward professionals aged 25–45, and sufficient floor area on an accessible street. Residential proximity matters less; office concentration matters more. Weekend footfall is largely irrelevant; weekday evening traffic is critical.

Put both of these businesses through a generic location scoring model and they may receive identical scores for a site that is excellent for one and unsuitable for the other. A generic model optimizes for average commercial viability — which is useful for a broad comparison but dangerous for a specific investment decision.

PlaceToBe AI's scoring profiles solve this by allowing each user to define what matters most for their specific use case, and letting the platform rank locations accordingly.

What a Scoring Profile Does

A scoring profile is a set of dimension weights that tell PlaceToBe AI's engine how to prioritize the four core scoring dimensions when calculating a composite score:

• Transport and Accessibility: How well-connected is this location by metro, bus, RER, cycling infrastructure, and pedestrian access?
• Footfall Analysis: What is the pedestrian traffic intensity, and how does it vary by time of day and day of week?
• Neighborhood Analysis: What is the demographic profile, income level, commercial density, and competitive ecosystem of the surrounding area?
• Security Indicators: What do incident data, commercial activity patterns, and infrastructure quality indicate about safety and comfort?

Without a profile, these four dimensions are weighted equally (25% each), producing a general commercial quality score. With a profile, you shift those weights to reflect your business priorities.

A bakery operator might configure: Footfall 40%, Neighborhood Analysis 30%, Transport 20%, Security 10%.

A logistics investor might configure: Transport 50%, Neighborhood Analysis 30%, Security 15%, Footfall 5%.

Same underlying data. Completely different rankings. Both entirely valid — and both more useful than a generic average.

Step-by-Step: Creating Your Profile on PlaceToBe AI

Step 1: Access the Profile Wizard

From the PlaceToBe AI dashboard, navigate to My Profiles in the top navigation bar, then click Create New Profile. The wizard guides you through the configuration process in four simple steps, with explanatory text for each dimension.

You can create multiple profiles — one for each business concept, investment format, or client mandate you manage. Profiles are saved to your account and can be applied at any time when exploring locations.

Step 2: Name Your Profile

Give your profile a descriptive name that reflects the use case — for example, "QSR Franchise — High Footfall" or "Logistics Acquisition — Transport Priority" or "Residential Investor — Security Focus." This naming convention becomes valuable when you're managing multiple profiles for different mandates.

Step 3: Set Your Dimension Weights

The weight configuration interface presents four sliders, one per dimension. Weights must sum to 100%. As you adjust each slider, the interface shows you a preview of how a sample set of locations would re-rank under your configuration — giving immediate intuition for the effect of your choices.

Guidance for each dimension:

Transport and Accessibility: Weight this heavily (35–50%) if your business model depends on customers or employees arriving by public transport, or if you are evaluating logistics and industrial assets where freight connectivity is critical. Also weight this heavily if you are evaluating assets in Grand Paris Express station catchment areas, where transport trajectory is a primary value driver.

Footfall Analysis: Weight this heavily (35–50%) if your format is impulse-purchase or convenience-oriented — food service, pharmacy, convenience retail, specialty snacking, etc. For formats that rely on destination visits rather than passing traffic (gym, specialist clinic, professional services), reduce this weight significantly.

Neighborhood Analysis: Weight this heavily (30–40%) if the demographic composition of the catchment area is a primary driver of customer qualification — luxury retail, specialist medical, financial services, premium food concepts. This dimension is also critical for residential investors evaluating the long-term social trajectory of an investment neighborhood.

Security Indicators: This dimension rarely warrants the highest weight, but it should never be set to zero. For family-oriented franchise formats, evening retail concepts, or any location targeting female-majority customer profiles, weight this dimension at 15–25% to surface locations where comfort and safety indicators are above average.

Step 4: Save and Apply

Once your weights are configured, click Save Profile. The profile is now available as a filter option in PlaceToBe AI's Explore view. When active, all locations on the map and in list view are scored and ranked using your profile weights rather than the default equal-weight model.

You can switch between profiles at any time, making it easy to compare how the same set of candidate locations ranks across different business models — a useful capability when evaluating multi-format franchise networks or mixed-portfolio acquisitions.

Example Profiles in Practice

Profile 1: Franchise Expansion Manager — QSR Format

Use case: Network development manager for a quick-service restaurant brand targeting 20 new French openings in 2026.

Priority logic: QSR revenue is almost entirely footfall-driven. A busy, accessible location with 25,000+ daily passers-by will outperform a demographically perfect location with 8,000 daily passers-by almost every time. Transport access drives lunchtime worker traffic. Demographics matter for pricing power and average transaction value, but secondary to raw volume.

Suggested weights:

• Footfall Analysis: 45%
• Transport and Accessibility: 30%
• Neighborhood Analysis: 15%
• Security Indicators: 10%

Impact on rankings: This profile surface locations in dense pedestrian corridors — central Paris arrondissements, major transit hubs, high-street retail zones — even when their neighborhood demographic scores are moderate. It downranks quiet residential neighborhoods that score well on demographics and security but lack the daily foot traffic to sustain QSR volumes.

Profile 2: Commercial Real Estate Investor — Retail Asset Acquisition

Use case: Fund manager acquiring a portfolio of French retail assets targeting 5–7% net yield over a 5-year hold.

Priority logic: Retail asset performance depends on tenant stability, which is driven by location quality across multiple dimensions. Transport access determines tenant catchment; demographics determine spending quality; security affects tenant retention and lease renewal rates. Footfall is important but already partially reflected in current rent levels.

Suggested weights:

• Neighborhood Analysis: 35%
• Transport and Accessibility: 30%
• Footfall Analysis: 25%
• Security Indicators: 10%

Impact on rankings: This profile prioritizes locations with strong, stable demographic profiles and excellent transport connectivity — assets that will remain attractive to tenants across market cycles. It downweights pure footfall scores that may reflect temporary patterns (tourist seasons, construction detours) rather than structural demand.

Profile 3: Residential Investor

Use case: Individual investor acquiring a buy-to-let apartment in Paris or a French secondary city.

Priority logic: Long-term tenant quality and retention, rental yield stability, and capital value appreciation are the primary objectives. Neighborhood quality and trajectory matter most; security affects tenant comfort and willingness to sign long leases; transport drives both rental demand and asset liquidity.

Suggested weights:

• Neighborhood Analysis: 40%
• Security Indicators: 30%
• Transport and Accessibility: 25%
• Footfall Analysis: 5%

Impact on rankings: This profile prioritizes stable, well-served residential neighborhoods over high-footfall commercial zones. It will surface locations in established arrondissements with strong community infrastructure, good schools, and low incident rates — characteristics that drive tenant retention and premium rents.

How Your Profile Affects Rankings in Explore

When you apply a profile in PlaceToBe AI's Explore view, two things change:

The composite score displayed for each location is recalculated using your dimension weights. A location that scores 68 under the default equal-weight model may score 81 under your footfall-heavy franchise profile, if its footfall dimension score is 90 and its other dimensions are average.

The ranking order of locations changes accordingly. The map heat-map highlighting and the list view ranking both reflect your profile, so you are always seeing locations ranked by what matters to your business model, not by a generic metric.

Over time, you can refine your profile based on feedback from the field. If you notice that locations you've opened consistently outperform their scored predictions on one dimension, that may indicate an opportunity to increase that dimension's weight in your model.

Tips for Refining Your Profile Over Time

Start with a baseline, then adjust: Begin with a profile that reflects your intuitive priorities, then review how the rankings align with your existing knowledge of high-performing locations. If your best-performing sites consistently score high on transport but only moderately on footfall, consider shifting weight toward transport.

Create separate profiles for different formats: A franchise network that operates both a standard format and a premium format should maintain separate profiles for each. The premium format's customer is less price-sensitive and more destination-driven, which typically means higher demographic and security weights.

Re-evaluate annually: Market dynamics change. The demographic profile of an arrondissement can shift meaningfully over two to three years; transport improvements alter the accessibility landscape; competitive dynamics evolve. Reviewing your profile weights annually against current performance data keeps your model calibrated.

Use profile comparison to test assumptions: Run your candidate locations through two or three different profiles and look for locations that rank highly across all of them. These are the sites with broad commercial resilience — strong fundamentals across multiple dimensions — that tend to outperform across market cycles.

Create Your Profile on PlaceToBe AI

Personalized scoring profiles are available to all PlaceToBe AI users. The configuration takes less than five minutes, and the impact on the quality of your location analysis is immediate.

Stop evaluating locations against someone else's definition of quality. Configure your profile and let the data work for your specific investment thesis.

Create your personalized scoring profile on PlaceToBe AI at placetobe.ai