For years, many business owners have encouraged customers to check in at their physical locations, tag themselves on social media, share photos, or use branded hashtags as a form of digital word-of-mouth (WOM). These tactics are still valid in many cases, but what most businesses fail to realize is that location-based data in social media goes far beyond public check-ins. And increasingly, that data is being used in ways that not only help your marketing but potentially help your competitors more.
Social media applications track and utilize location-based data, often without explicit user consent, which is why businesses should reconsider their approach to encouraging and managing customer engagement online.
Location Data: It’s More Than Check-ins
The idea that social media only tracks your location when you post it is a myth. Most major social apps collect and use location data in passive, persistent ways. Here’s how they do it:
GPS and device location services: When a user installs an app and grants location permissions—even just while using the app—the app gains access to GPS signals, Wi-Fi data, cellular tower triangulation, and Bluetooth beacons. Snapchat, for example, collects GPS, Wi-Fi, and Bluetooth-based location data to power Snap Map and other features, even if location isn’t actively shared. Snap’s own privacy disclosures confirm that it stores GPS locations to improve features.
IP address and network data: Even if a user denies GPS access, social apps can infer their general location using IP address data. This is less precise, but still valuable for regional targeting. Facebook and Instagram utilize this method to help determine users’ locations and serve geographically relevant content or ads.
Media metadata: Smartphones often embed GPS coordinates in the metadata of photos and videos. If users upload this media to platforms like Instagram or Facebook, the app may access the metadata, even if the post isn’t geotagged. Instagram is known to read EXIF data automatically upon upload, and privacy watchdogs have long flagged this as a concern.
Activity patterns and motion sensors: Some apps access accelerometer or gyroscope data to determine whether a person is walking, running, or driving. While this may seem unrelated, it helps enhance behavioral profiles and predict location-based patterns.
How Location Data Powers Targeting… Of Your Customers By Competitors
Social platforms like Meta (Facebook and Instagram), TikTok, and Snapchat are not just collecting this data passively—they’re using it to enhance their advertising engines in highly granular ways.
Geofencing: Advertisers can serve ads to users who have physically visited a specific place or area, such as your store or your competitor’s. This is commonly used in retail, food service, and automotive to target recent visitors with promotional offers.
Lookalike audiences: Platforms analyze behavioral and demographic data—including places visited—to find users with similar traits. If your customer base frequently visits your location, a competitor can use that data to target new users who match your audience profile. Facebook and Instagram offer this feature natively in their ad tools.
Interest targeting via behavior: Repeated visits to gyms, salons, restaurants, or shopping centers contribute to behavioral inference. This data then places users into interest buckets, available for advertiser targeting. These profiles are not visible to the public, but advertisers can access them through interest filters.
Ad performance optimization: Social platforms use historical and real-time location data to optimize ad delivery. If the system believes someone is likely to convert in a particular area, it may automatically shift budget or impressions to prioritize that geography.
This targeting ecosystem has become so advanced that Meta faced a $37.5 million settlement over allegations it tracked user locations even after users disabled location services.
This is where the tradeoff becomes clear. Encouraging customers to check in or tag your location helps build visibility and credibility—it tells their friends where they’ve been and can increase organic reach. But check-ins also reinforce to the platform that these individuals are part of your business’s location-based audience.
That audience profile is then made available for competitors to target. While the data itself isn’t sold or shown to competitors directly, your encouragement may be helping the algorithm draw a circle around your customer base, making it easier for others to find and influence them.
When Word of Mouth Becomes a Competitive Dataset
Imagine this: you run a local venue and decide to launch an open mic night for musicians. You promote it heavily through your social media accounts, invite local artists, and encourage attendees to:
Follow your venue’s Instagram and Facebook pages
RSVP to events using social media apps
Post videos and photos from the night using a branded hashtag
Tag your venue’s location in their stories and reels
It works. Over the next few months, the event becomes a local sensation. Your social media is full of activity. People check in, tag your business, and the engagement grows organically. You’re thrilled—it feels like textbook word-of-mouth success.
But behind the scenes, a different story is unfolding—one that has nothing to do with malicious intent but everything to do with algorithmic targeting.
Just a few miles away, a competing venue also wants to grow its presence in the local music scene. They set up a new live music night, and as part of their ad campaign, they target:
People within a 15-mile radius
People who have shown interest in live music, bars, local events, and nightlife
Lookalike audiences based on followers of regional music influencers
They’re not targeting your business by name. But machine learning algorithms on platforms like Facebook, Instagram, and TikTok do the rest. Based on your customers’ location check-ins, event RSVPs, and tagged media, the platforms infer their affinity for live music events in the area, and your customers end up in the competitor’s ad audience.
Here’s how it happens step-by-step:
Engagement signals are generated: Your attendees share content with geotags, follow your accounts, and RSVP to your events. This activity feeds social platforms with detailed behavioral and interest data.
The platforms build a behavioral profile: Your customers are now seen not just as fans of your venue but as people who attend live music events in your region, which becomes part of their interest graph.
Your competitor launches a campaign: They choose broad but relevant ad targeting live music fans near me. This activates platform algorithms to identify individuals who match that pattern.
Machine learning matches your audience: Social ad algorithms use engagement data to optimize ad delivery. Since your customers already show behavior that matches the campaign criteria, they are prime targets.
Your customers see the competitor’s ads. Even without knowing your brand or your event, your competitor is now advertising to your audience with potentially better offers, easier parking, or a more polished act. Some of your loyal visitors start exploring other options.
You thought you were building momentum through word of mouth. Instead, the very data that indicated your event’s success became an asset that the ad platform repackaged and sold to someone else.
This scenario isn’t hypothetical—it’s the standard operating procedure of data-driven advertising platforms. The more successful and engaging your events are, the more valuable your audience becomes in the ad ecosystem, not just for you, but for anyone willing to pay to reach similar people.
The takeaway isn’t to stop building community or sharing your success. However, it’s crucial to acknowledge that in the social media economy, audience engagement not only creates visibility but also generates data. And once that data enters the machine, you don’t control where it ends up.
Should You Still Encourage Check-ins?
Encouraging check-ins and customer engagement isn’t inherently risky, but it must be done with strategy and awareness. Here are some ways to protect your customer relationships and use location-based tools wisely:
Be aware of the data trail: Understand that customer interaction on mobile apps often results in passive data collection. Posts, media uploads, and simple app usage can all contribute to their behavioral profiles.
Use geofencing for yourself: Turn the same tools your competitors use into assets for your brand. Build custom audiences around your store or rival businesses to reach high-intent consumers.
Balance visibility and privacy: Consider promoting content and reviews over check-ins. These still provide social proof without necessarily feeding location signals into ad platforms.
Capture first-party data: Create loyalty programs, QR-based campaigns, or gated content that encourages customers to share their information directly with you, bypassing third-party platforms.
Educate your staff: Anyone responsible for managing your social media or customer engagement should understand the implications of metadata, background tracking, and ad targeting mechanics.
Data power social media platforms, and location is one of the most powerful signals they track. While this data helps businesses reach the right people, it also enables competitors to target your customers based on the very behaviors you’re encouraging.
The more your audience interacts with you on mobile apps, the more detailed their behavioral and location profile becomes, making them prime candidates for competitor campaigns that offer convenience, discounts, or novelty.
It’s time for businesses to move beyond casual digital engagement and think critically about how social activity feeds into advertising systems. Location data is not just a user setting—it’s a strategic asset that, if overlooked, can work against you.
©2025 DK New Media, LLC, All rights reserved | Disclosure
Originally Published on Martech Zone: How Social Media Apps Use Location-Based Data… and Why It Matters For Your Business