NextTech: Who Visited Times Square in Summer 2025?

Up to 330,000 pedestrians a day pass through Midtown Manhattan’s Times Square—a narrow, noisy chute of taxis, blinking billboards, and Broadway theaters. An executive weighing an ad placement, store location, or brand activation might see that number and think: Who are they, and where do they come from?

Mapping and analytics provide answers, with location technology converting raw data into valuable intelligence for businesses.

What ZIP Code Data Reveals About Times Square Visits

This video reveals the top five ZIP codes responsible for the most Times Square visits—excluding visitors from nearby locales in New York, New Jersey, and Connecticut. The analysis is performed by geographic information system (GIS) technology using footfall data from Placer.ai.

The top ZIP codes are:

1. San Diego, CA
2. Cambridge, MA
3. Miami Beach, FL
4. West Hollywood, CA
5. Washington, DC

For a company investigating the commercial potential of Times Square or any business district, high-level visitation numbers are a starting point. Understanding more about the people behind those numbers—their traits, habits, and motivations—is where analysis becomes strategy.

The GIS technology featured in the video creates maps that uncover patterns in data, including psychographics, that would otherwise remain obscured in spreadsheets. That context helps businesses better serve the communities where they operate.

Multiplying the Value of Location Analysis Through Psychographics

In the video analysis, a map-driven dashboard brings a key fact to light: Four of the five ZIP codes share a broader psychographic group. That segment includes working, well-educated professionals in their mid-thirties, many born outside the US.

The group’s subcategories paint the portrait of a particular kind of tourist: city dwellers drawn to major metropolises with the time and income for big trips. Their international origins also point to Times Square’s pull as an iconic American destination.

The GIS dashboard allows an analyst to dive into even finer distinctions with a click or two. For instance, scanning the demographic data across the five ZIP codes shows a consistent pattern: While San Diego, Cambridge, and Washington have different dominant consumer groups, all three groups have high incomes and high home values, and each makes up nearly half of the residents in its area.

Compare those locales with Miami Beach, where the dominant consumer group represents a smaller share of the population and sits at more moderate income and home wealth levels.

Transforming Insights into Business Decisions

Mapping and analytics quickly unpack the business implications of footfall data for a shopping mall, neighborhood, or high street.

Connecting footfall data to demographic insights could help a hotel opening near Times Square to set room prices or offer deals suited to visitors’ spending habits. A media agency could draw on psychographic data—average ages, brand preferences, lifestyle markers—to target ad campaigns more precisely.

Companies across sectors are using location intelligence in this way. One wellness company uses GIS to site clinics in areas popular with key customer groups, such as shopping centers with organic grocers. A major hardware chain uses GIS-based insights to inform decisions as granular as store layout and in-store music.

Times Square might be the most famous street corner in America, but it shares something with downtown districts and small-town intersections everywhere: The people passing a company’s storefront or billboards are among its most important potential customers. GIS helps businesses act on that fact.