From Traffic Counts to Bankable Sales Projections: Why Retail Feasibility Needs More Than a Good Anchor

Recent retail real estate headlines show two sides of the same investment question. Newport Pavilion, a 332,309-square-foot power center in Kentucky anchored by Kroger and Target, and Hammock Landing, a 750,000-square-foot super-regional power center on Florida’s Space Coast sold for $78.5 million, both point to continuing investor interest in large retail nodes with strong anchor tenants. At the same time, the NATSO Foundation’s 2026 professional driver toolkit reminds operators that traffic alone does not guarantee sales. Drivers and shoppers choose locations based on the total experience: access, convenience, safety, parking, cleanliness, tenant mix, and ease of stopping.

For lenders, investors, developers, and operators, that is the central issue behind a bankable feasibility study. A location can look compelling on paper because it has a grocery anchor, a national tenant lineup, or a busy road frontage. Yet underwriting requires a more rigorous question: how much of that movement can realistically become customer visits, category sales, and repeat demand over the next five years?

That is where C-Site Insight turns traffic analytics into commercial evidence.

Bankable feasibility begins with the right definition of demand

Traditional feasibility studies often start with radius rings, drive-time polygons, and demographic summaries. These are useful, but they can miss the most important part of retail demand: who is actually passing the site, when they pass, from which direction, and whether their driving behavior suggests a realistic willingness to stop.

Ticon’s 2025 research paper, "Reevaluating Trade Area Analysis with Accurate Traffic and Highly Granular Demographics Data," argues that a more precise trade area assessment should combine three elements: the Immediate Trade Area of 1 to 2 miles, the Extended Trade Area of 5 to 20 miles, and Passing Traffic, which captures the factual flow of travelers at the site. This distinction matters because the first two describe location potential, while passing traffic reflects real exposure to potential customers.

For a grocery-anchored center, for example, a Kroger tenancy may signal strong baseline demand. Ticon’s retail chain research cites Kroger site criteria that include a minimum of 20,000 people in the trade area and median income of at least $40,000. Those thresholds are important, but they are only the starting point. A feasibility study must still determine whether the site’s traffic patterns support cross-shopping, whether local customers dominate or transit users pass through without stopping, and whether peak periods align with tenant categories.

C-Site’s commercial site analysis has observed that a shopping center can demonstrate a strong visitor rate, also referred to as “traffic catch,” exceeding normative benchmarks by approximately 20% when access, visibility, tenant mix, and customer behavior are favorable. That kind of metric is more useful for underwriting than simply stating that a center is busy. It translates traffic into likely commercial performance.

Why AADT alone is not enough for sales projection

Annual Average Daily Traffic remains a core feasibility metric, but it should not be treated as a sales forecast by itself. Two sites can have similar AADT and produce very different sales outcomes because directionality, speed, congestion, road configuration, and trip purpose all affect capture.

C-Site reports are built around the exact address of interest, not a ZIP code, broad polygon, or generalized road segment. Ticon’s traffic information is based on continuous 24/7/365 observation and can be current to within one week of the report period. Depending on the report level, C-Site provides directional AADT for primary and secondary roads, adjacent highways and offramps, intraday traffic volumes, weekday and weekend patterns, monthly seasonality, hourly or 15-minute traffic intervals, speed distributions, congestion, and rush-hour analysis.

This granularity is especially important for bankable sales projection. A travel center near an interstate, a QSR pad at a power center, and a convenience store on an arterial may all depend on passing vehicles, but each requires a different interpretation of stop probability. Professional drivers may value parking availability and lighting. Morning commuters may respond to coffee and breakfast access. Grocery shoppers may support co-tenants through linked trips. A feasibility model should reflect these distinctions instead of applying one generic capture rate.