Site selection to maximize ROI in an expansion cycle

The retail buildout cycle is accelerating again. Mixed-use flagships are onboarding premium tenants in established markets, convenience brands are planting flags along new highway corridors, and casual dining chains are announcing multi-format growth plans. Easton Town Center’s latest leases in Columbus, QuikTrip’s construction in Kentucky, and TGI Fridays’ new targets all point to the same reality: when square footage expands, location decisions carry higher stakes. The operators who validate demand with quantitative traffic analytics will protect margins and compress payback periods. Those who guess will not.

How C-Site turns traffic into ROI

Start with directional traffic that is exact to the address. C-Site reports Average Annual Daily Traffic at the precise road segment and by direction, based on year-round observations for the most recent twelve months ending one week before the order. In an internal Chick-fil-A case example, a candidate frontage on US‑158 showed ADT of 38,327 at the exact location, not a nearby counter or district average. That level of positional accuracy is the difference between an 18-month payback and a miss that looks plausible on paper.

Replace raw AADT with Total ADT for candidate comparison. Our site selection framework aggregates the flows from primary and secondary approaches that can physically and legally access the parcel, then applies turn-in feasibility and signalization effects. This produces a Total ADT that reflects the real universe of stoppers, not only the heaviest stream on the nearest mainline. In practice, two sites with similar corridor AADT can have materially different Total ADT once approach geometry and maneuverability are accounted for.

Quantify who is passing and who is likely to stop.

C-Site combines:
• Local versus in-transit share to distinguish neighborhood demand from pass-through trips
• In-transit demographics to align concept fit with the actual people in the flow
• Driver behavior indicators derived from speed distribution and network maneuverability to estimate stopping propensity

In one C-Site example, the fifteen-minute accessibility radius encompassed 40,310 people, and the speed profile indicated a favorable share of slowing vehicles near a signalized corner. Folding that into a concept’s verified catch rate yields a realistic visit forecast by daypart rather than a generic uplift assumption. This is essential for formats that succeed on two peaks per day such as lunch and dinner in casual dining, or morning and afternoon in convenience and fuel.

Model volatility before you sign.

External conditions can change traffic quickly, which is why C-Site impact analysis is embedded in site workups. In a published Ticon case study, a road closure drove a 51 percent reduction in Total ADT on the closed route and a 20 percent increase on the adjacent relief road. Without impact analysis, a retailer on the closed road would overestimate demand by half, while a retailer on the parallel route would undervalue an emergent opportunity. The same methods flag recurring surges around sporting events and festivals, enabling staffing and inventory plans that protect service levels and margin.

Treat competitor presence as a measurable variable, not a myth.

Our competitor presence analyses show that clustering can create customer hubs that lift visits for multiple operators when the trade area has unmet demand. C-Site quantifies this through before and after volume, day-of-week patterns, and directional inflow changes, so a retailer can decide when proximity is accretive and when it is cannibalizing. This matters at mixed-use destinations like Easton where complementary brands can compound dwell time, and along highway corridors where co-location can convert more pass-by traffic.

Tie format to micro-location.

The current news cycle highlights three distinct placement problems that require different traffic signatures:
• Mixed-use destinations with discretionary retail: prioritize Total ADT with high weekend and evening peaks, affluent in-transit demographics, and high pedestrian adjacency. Use C-Site to trace cross-traffic between anchors to select frontages that intercept the largest flows.
• Highway convenience and travel centers: prioritize directional ADT by approach, heavy pass-through shares, truck-friendly maneuverability, and deceleration profiles near signalized intersections. C-Site Scout helps small and medium operators quickly screen corners, competition density, and peak-hour patterns.
• Airports, hotels, and transport-adjacent dining: target stable weekday peaks plus secondary evening/weekend surges. Use in-transit demographics and stopping propensity to set format and hours, then validate that weekday lunch plus weekend leisure can support throughput targets.

From numbers to dollars: a practical playbook

• Screen candidates with exact-to-address directional ADT and compute Total ADT based on all accessible approaches.
• Profile the flow: local versus transit shares, in-transit demographics, and driver behavior indicators that reveal stop likelihood.
• Size the opportunity using your concept’s verified catch rate and average ticket to forecast visits and revenue by daypart and season.
• Run impact scenarios to capture roadworks, events, and seasonal shifts. Anchor the decision with quantified sensitivities, not averages from last year.
• Evaluate competitor effects with before and after analyses to identify true hubs versus saturated clusters.

Where C-Site adds immediate value

Retail site selection and investment appraisal: factual traffic, not proxies. Exact ADT and Total ADT, local versus transit mix, in-transit demographics, and stopping propensity shorten underwriting cycles and reduce error.

Operations and workforce planning: by-hour traffic distributions align labor with demand. C-Site’s intraday and weekday versus weekend profiles cut labor waste while protecting throughput.

Inventory and marketing optimization: seasonal and event-driven patterns inform procurement and campaign timing. Operators can amplify performance during predictable surges and avoid stockouts.

Evidence you can quote

• Exact-to-address ADT: US‑158 case with 38,327 vehicles per day at the location.
• Freshness window: twelve months of observations ending a week before report delivery.
• Impact analysis: 51 percent ADT decline on a closed route and 20 percent uplift on the adjacent road during a construction period.
• Accessibility and scale example: 40,310 people in a fifteen-minute radius, combined with speed-based stopping indicators to estimate visit potential.

Why this matters now

As premium tenants concentrate in mixed-use centers, convenience brands fill high-velocity corridors, and casual dining exercises with airports and hotel co-locations, the spread between good and poor sites widens. The winners will apply quantitative traffic analytics to match formats with micro-locations, anticipate volatility, and convert passing flow into reliable revenue. C-Site was built for this moment: precise traffic patterns, in-transit demographics, and stopping behavior indicators, integrated into a workflow that turns flows into forecasts and forecasts into ROI.

References

• Ticon, Impact Analysis case study and report, 2025
• Ticon, Competitor presence: a threat or a benefit, 2025
• Ticon, More than AADT: In-Transit Demographics & Retail Site Selection, 2025
• Ticon, C-Site Insight product materials and report organization
• Ticon, C-Site Scout methodology for small and medium operators