Traffic Counts, Daytime Population, and Retail Site Selection

For multifamily and industrial deals, the demographic and supply data from earlier lessons is the whole picture. For retail — strip centers, freestanding restaurants, gas stations, QSR pads, NNN single-tenant — there's an entirely separate layer of data that matters more than population: the specific physical location of the corner.

A retail tenant's profitability depends on how many people drive past the front door, how visible the sign is, how easy it is to access, and what's around it. Two retail buildings 500 feet apart can have completely different traffic patterns and therefore completely different rents and cap rates.

This lesson covers how site selectors actually evaluate retail locations, and how you should evaluate them when underwriting retail deals.

Traffic counts — the foundation

Traffic count = the number of vehicles that pass a given point on a road, per day.

It's the single most important data point for retail. Almost every chain restaurant, gas station, drug store, dollar store, and convenience store has a minimum traffic count threshold below which they won't even consider a site.

Where to find it

• State DOT websites — every state DOT publishes traffic counts on major roads, updated annually. Free.
• MapQuest, Google Maps, Apple Maps — sometimes show traffic data overlays, but unreliable for absolute numbers
• CoStar / Reis — overlay traffic counts on every listed property
• ESRI Business Analyst — traffic counts integrated into demographic reports
• Commercial broker market reports — often include local traffic data

What the numbers mean

| Traffic count (vehicles/day) | Type of location | What it supports | |---|---|---| | < 5,000 | Local / residential | Local convenience, neighborhood services | | 5,000-10,000 | Secondary | Small-format service retail, neighborhood centers | | 10,000-20,000 | Strong secondary | Most retail, value retail, smaller QSR | | 20,000-30,000 | Primary corridor | Major chain QSR, drug store, dollar store, oil change | | 30,000-50,000 | High traffic | Big-box anchors, regional retail centers | | 50,000+ | Very high | Mall outparcels, premium QSR, gas station / c-store |

These are rough thresholds. A tenant's specific minimum varies — Starbucks wants 25K+, Chick-fil-A wants 30K+, Dollar General will go down to 8K, McDonald's wants 30K+, RaceTrac wants 40K+.

If you're underwriting a freestanding NNN deal at a 6% cap rate, the cap rate is partly a function of the traffic count. A 20,000 ADT (Average Daily Traffic) location supports a 6% cap rate; a 5,000 ADT location at the same building and tenant supports maybe 7.5% cap. The difference is the salability of the site to a future tenant if the current one goes dark.

Visibility and access

Traffic count is necessary but not sufficient. A site with 30,000 ADT and bad visibility (set behind trees, around a curve, on the wrong side of a divided road) is worth less than a site with 20,000 ADT and perfect visibility.

The factors that matter:

1. Visibility

Can a driver see the building and the sign from at least 500 feet away? At 45 mph, that gives them ~7 seconds to react and turn into the parking lot. Less than 500 feet of sightline = miss-the-driveway problem = lost customers.

2. Sign placement and elevation

Is there a high pylon sign visible above competing signage? Can the sign be lit at night? Can the building face the road? Tenants pay more for sites where signage is visible from the highway and from competing approaches.

3. Curb cuts and access

• Right-in, right-out only? Or full access (left turns allowed)?
• Is there a median, or can drivers cross from the opposite direction?
• Is there a traffic signal at the entrance, making left turns easy?
• How many curb cuts are there? Two access points are dramatically better than one.

A signalized full-access corner can be worth 2x a mid-block right-in-right-out site at the same traffic count.

4. Parking ratio

• 4-5 spaces per 1,000 SF for shopping centers
• 8-10 per 1,000 SF for restaurants
• 12-15 for fast-casual / drive-thru
• Tenants will reject sites that don't meet their corporate minimums

5. Drive-thru viability

For QSR tenants, can the site accommodate a drive-thru with adequate stacking? Modern Chick-fil-A and Starbucks need 12-20 car stacking depth. A site that can't accommodate this is automatically excluded from the highest-value tenant pool.

6. Co-tenancy

What's around the site? A pad in front of a Walmart Supercenter is worth 2-3x a pad in a struggling strip center, even at the same traffic count. Strong co-tenants pull foot traffic; weak co-tenants depress it.

Daytime population

Daytime population = number of people physically present in a defined area during business hours (9am-5pm), not just the residential population.

This matters enormously for office-adjacent retail, lunch QSR, coffee, gas stations, dry cleaners, and any business whose customer is "people working nearby."

A residential neighborhood might have 50,000 people in a 3-mile radius but only 30,000 daytime population (because workers commute out to jobs elsewhere). A downtown core might have 20,000 residents in the same radius but 150,000 daytime population (because it's where everyone works).

For a coffee shop or breakfast QSR, the second site is dramatically better despite the lower residential count.

Where to find it

• ESRI Business Analyst — calculates daytime population at any radius
• Census On The Map — free Census tool showing where workers commute from/to
• CoStar reports include daytime population for retail listings

Rules of thumb

• Daytime > Residential = office or commercial-employment node (good for lunch retail)
• Daytime ≈ Residential = mixed-use or balanced (good for general retail)
• Daytime < Residential = bedroom community (good for dinner / weekend retail, weak for lunch/coffee)

Trade area capture

For larger retail (anchors, junior boxes, regional centers), the metric that matters is the trade area — the geographic area from which the store draws customers — and the capture rate — what % of households in that area shop there.

Defining the trade area

For most general retail, the trade area is a 3-5 mile radius around the site. For grocery, it's 1-3 miles. For a mall or regional power center, it's 5-15 miles. For destination retail (Cabela's, IKEA, Top Golf), it's 30+ miles.

Rule of thumb: drive time matters more than distance. A 5-mile drive with a freeway is worth more than a 3-mile drive on local roads with traffic lights. ESRI tools let you draw drive-time isochrones (e.g., "everyone within 10 minutes of this site").

Calculating capture

• Total households in trade area × average annual household spending in the relevant retail category × estimated capture rate (10-30% depending on competition) = annual sales potential
• Annual sales / SF needed = supportable size

This is exactly how site selectors model whether a store will hit its sales targets. You don't need to be precise — directional math is enough to know whether the site can support the rent the tenant is paying.

Demographic overlay for retail

Beyond the eight numbers from Lesson 3, retail-specific demographics matter:

| Metric | Why it matters for retail | |---|---| | Median household income | Determines spending capacity | | Average household size | Drives grocery, big-box demand | | Age 25-44 | Drives home improvement, family services | | Age 45-64 | Drives healthcare, optical, financial services | | Age 65+ | Drives medical, prescription, downsizing services | | % college educated | Drives premium QSR, premium grocery, fitness | | % homeowners | Drives home improvement, lawn/garden, hardware | | Households with kids | Drives kids' services, family restaurants, childcare |

A site with 80,000 ADT but median income $35K is a Dollar General / Family Dollar site. A site with 25,000 ADT but median income $120K is a Starbucks / Chipotle / Whole Foods site. Same retail category, completely different formats.

The retail underwriting checklist

When you're looking at a freestanding retail or strip center deal, work through this:

1. Traffic count at the front door — record the most recent ADT
2. Trend — is traffic growing, flat, or declining? (DOT publishes 5-year history)
3. Visibility — visit in person; verify sightlines
4. Access — full access vs. right-in/right-out; signal vs. no signal
5. Co-tenancy — what's around the site? Strong, weak, or mixed?
6. Parking ratio — meets the relevant tenant minimums?
7. Trade area demographics — population, income, age, density
8. Daytime vs. residential population — does the mix support the tenant type?
9. Competition — how many similar stores are in the trade area?
10. Existing tenant fit — does the site match the tenant's prototype requirements?

If any of these is materially off, adjust your underwriting (higher cap rate, lower rent assumptions, longer release time).

Visiting the site

Data is necessary; site visits are mandatory. Drive the site at multiple times:

• Weekday morning rush (7-9 am)
• Weekday lunch (11:30-1:30)
• Weekday evening rush (4:30-6:30)
• Weekend midday (Saturday 11-2)

You're checking traffic flow, queue lengths, ease of getting in and out of the parking lot, and how busy nearby tenants are. A strip center that's full at lunch but empty at 5 pm is supporting only daytime retail; one that's busy at 6 pm is supporting evening / family retail.

Photograph everything. Note what's vacant in nearby centers, what's under construction, and what new construction is happening on adjacent parcels. The future of the site is changing right in front of you — most underwriters miss it because they only look at the listing photos.

What to take away

• Traffic count is the foundation of retail underwriting — every tenant has a minimum threshold
• 20,000+ ADT supports most national chain retail; 30,000+ supports premium QSR and gas stations
• Visibility, access, and co-tenancy matter as much as raw traffic count
• Daytime population matters for office-adjacent retail; residential matters for evening/weekend retail
• Trade area + capture rate is the institutional retail underwriting math
• Always visit the site in person at multiple times — data alone misses too much

Next lesson: identifying the path of growth — the leading indicator that tells you which submarkets and corners are about to become valuable, often years before prices reflect it.