# Simon Property turns 77 million annual mall visitors into off-site targeting inventory for brand advertisers *Mall owner monetizes first-party location data by letting brands follow shoppers beyond the food court.* By **Jenny Huang Goodman MPA MSc MHSA, Principal** — The Stash Edge, Hako Shikin LLC. Published 2026-09-02. Canonical: https://www.pops4.com/stash/articles/location-data-retail-media-2026-09-02t21-7 Subject: Location Data (Retail Media) Tags: location data, retail media, audience targeting, attribution, first-party data, offline-to-online --- Simon Property Group, the largest mall owner in the United States, is selling access to first-party location data from its **77 million** annual visitors, according to Digiday. The pitch: brands can now target people who visited a Simon mall — not just while they're inside the property, but across digital environments after they leave. Simon pairs this with measurement tools that tie ad exposure back to foot traffic and purchase behavior captured in its physical locations. The mechanics are straightforward. Simon collects location signals from shoppers who visit its properties, then packages that audience for programmatic targeting. A brand selling athletic apparel, for example, can serve display or video ads to people who recently walked through a Simon mall, whether those shoppers are browsing Instagram an hour later or reading news sites the next day. Simon also offers attribution: brands can measure whether someone who saw the ad later returned to a Simon property or made a purchase at a tenant store. The data comes from Simon's owned footprint, which includes more than **200** properties across North America, giving the company a dense map of high-intent retail behavior. This works because location data converts physical movement into addressable media inventory. Most retail media networks monetize attention inside the store — endcaps, search ads on a retailer's site, sampling stations. Simon is monetizing the *having been there*. The shopper who spent twenty minutes in a Foot Locker at a Simon mall has demonstrated category interest, discretionary income, and willingness to travel for retail. That behavioral profile is more valuable to an advertiser than a generic demographic guess. By extending targeting beyond the mall visit, Simon turns a fleeting piece of foot traffic into a persistent media asset. The measurement layer closes the loop. Brands historically struggled to connect offline ads to offline outcomes. Simon's dataset lets them track whether a digital impression influenced a store visit or a point-of-sale transaction at a tenant retailer. That feedback tightens budget allocation: if targeting recent mall visitors drives a **3x** higher visit rate than cold targeting, the brand shifts spend accordingly. Simon benefits twice — once from selling the media, again from proving its malls are demand generators worth occupying. A small physical-product brand can run the same play without owning a mall. Start with first-party behavioral data you already capture: email list, SMS subscribers, people who visited your Shopify site, attendees at a pop-up or event. Export those audiences and upload them to Meta or Google as custom audiences for lookalike targeting. If you sold candles at a farmers market, build a Meta lookalike from the phone numbers you collected. If you ran a booth at a trade show, retarget badge scans with carousel ads featuring the product they handled. The principle is identical — convert a known offline behavior into addressable online reach. Next, close the attribution loop with a lightweight tracking mechanism. Use a unique discount code in the retargeting ad, specific to that audience. When someone redeems it, you know the mall visit (or market appearance, or event) drove the online conversion. If you have a physical retail presence, set up a geofence around your store or stockist locations using a tool like Radar or Foursquare and measure whether people who saw your Meta ads later visited in person. Cost: under **$100** per month for basic geofencing on a few locations. The data won't be as clean as Simon's **77 million**-visitor dataset, but it will tell you whether your offline activity is worth amplifying with paid media. The broader pattern is retail real estate becoming media infrastructure. Malls, pop-ups, and physical distribution points are no longer just transaction venues — they're data collection surfaces. The brand that treats every customer interaction as a trackable event, then feeds that data back into targeting and attribution, turns inventory into intelligence. Simon Property is selling that intelligence at scale. You build the same asset one event, one email capture, one SKU at a time. ## The takeaway Turn offline customer touchpoints into retargetable audiences and measure whether digital ads drive physical visits or repeat purchases. --- ## Publisher **Hako Shikin LLC** — Virginia Beach, Virginia. Founded 1997. ASI 217876 · DUNS 18-204-6339. Principal and author: **Jenny Huang Goodman MPA MSc MHSA**. - Author: https://www.huanggoodman.com/about - LLM context: https://www.pops4.com/stash/llms.txt - MCP endpoint, for AI agents: https://mcp.pops4.com/mcp - Client dashboard: https://dashboard.pops4.com/ - Catalogue: 70,000+ products, 200+ brands