What is Location-Based Marketing?
Location-based marketing uses geospatial data to deliver targeted marketing based on a user’s real-world behavior. Instead of relying solely on digital signals like website visits or online searches, location-based marketing taps into the movement patterns of consumers in the physical world. The core idea is simple: where a person goes provides meaningful context about their interests, intent, and likelihood to engage with specific brands or products.
For ad tech companies and brands, this unlocks opportunities to refine audience segmentation, personalize messaging, and improve attribution by understanding how foot traffic correlates with marketing exposure and conversion.
Location-Based Marketing Use Cases for Ad Tech
Using mobile location data allows ad tech companies and brands to understand patterns of movement, dwell times, and location affinities that reveal deeper insights about consumer habits and preferences than traditional demographic targeting alone.
The real value in location-based marketing comes from the ability to merge spatial data with temporal patterns and cross-reference against points of interest databases. Ad tech platforms will ingest billions of location signals daily, using machine learning algorithms to interpret meaningful visits to infer consumer intent based on physical world behaviors. This processed intelligence enables advertisers to deliver contextually relevant messages based on real-time location, historical patterns, and predicted future movements.
- Geofencing campaigns use location to trigger ads when users enter, exit, or dwell within specified geographic boundaries
- Audience segmentation derived from location patterns identifies valuable consumer groups like "frequent QSR visitors" or "luxury retail shoppers," allowing for portable targeting across digital channels without requiring actual real-time location.
- Competitor conquesting strategies analyze foot traffic to identify consumers who visit competitor locations, enabling precisely timed promotional messages to intercept potential customers before purchase decisions are finalized.
- Attribution modeling uses location data to measure offline store visits following digital ad exposure, creating closed-loop analytics that quantify campaign ROI beyond traditional metrics like clicks or impressions.
Enriching Location Data: MAID to HEM and FLIP
To maximize the effectiveness of location-based marketing, it is essential to enrich location pings with other identifiers. This is where Mobile Advertising IDs (MAIDs), Hashed Emails (HEMs), and Frequently Leveraged IPs (FLIPsP are useful to create user profiles.
- MAID to HEM Mapping: A HEM is an anonymized identifier that connects a device to a known user without exposing personally identifiable information (PII). By linking a HEM to a MAID, companies can create more robust cross-channel identity graphs. This enables them to unify mobile behaviors with desktop and in-store interactions that give a clearer picture of user journeys.
- FLIP (Frequently Leveraged IP): A FLIP is an IP address that a user consistently connects to, often at home or work. Connecting MAIDs with FLIPs allows one to understand a household or office-based behaviors for more accurate attribution and audience segmentation. This is especially valuable to bridge the gap between mobile and CTV (connected TV) advertisements, where deterministic identifiers are scarce.
How Unacast Powers Smarter Location-Based Marketing
At Unacast, we specialize in refining and enriching location data to make it more actionable for ad tech companies and brands. Our approach focuses on:
- Data Quality Assurance: We process signals from multiple vetted SDK partners, ensuring accuracy and compliance with privacy standards.
- Identity Resolution & Linkage: By linking MAIDs with HEMs and FLIPs, we help advertisers build more complete user profiles, enabling better targeting and omnichannel engagement.
- Advanced Attribution & Measurement: Our enrichment process allows advertisers to accurately attribute conversions by connecting mobile behaviors to household and workplace activities.
- Privacy-Compliant Data Processing: We ensure that location data is ethically sourced and adheres to GDPR, CCPA, and evolving privacy frameworks.
The key is not just collecting location signals, but trusting the data is compliant and easier to work with. For product and engineering leaders in ad tech, this means less time, energy, and money processing raw data signals for a faster time to value. As the landscape of privacy regulations evolves, Unacast continues to invest in data transparency, compliance, and cutting-edge methodologies to keep location-based marketing both effective and ethical without losing scale.
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