- Incomparable scalability
- Pinpoint accuracy
- Granular localization via custom shapes and sizes
- Boost mobile performance and reach
- Retarget customers who visit or commute through any geo-fenced location
- Leverage targeted campaigns only to customers within a predetermined psychical proximity to your business
- The most reliable way to target mobile users in your business’s proximity.
- Track offline and “last mile” conversions to measure your campaign’s effectiveness.
Self Managed or Managed- Services
- Campaigns can be built, launched, optimized, and reported on all in the user interface
- Customers can fully customize targeting shapes and sizes in the user interface
- All facets of Geo-Fencing campaigns from budget to shape configurations are instantly searchable in the user interface
- Brandendo’s platform supports bulk uploads of shape data files (GeoJSON) to target larger areas like political and school districts, street and highway boundaries, municipalities, etc.
- Brandendo’s Geo-Fence Finder tool curates a list of relevant commercial properties to target based on geographic parameters and location types for more than 5,000 categories and brands. Lists can then be
- filtered, downloaded, and uploaded in bulk directly to a Geo-Fencing campaign
Unstructured data allows for efficient and effective campaign scaling without needing to adjust the parameters of the geo-fenced locations. Brandendo sees approximately 600,000 apps and our data is scalable to multiple petabytes and is currently utilizing a petabyte size cluster.
A location-based campaign is only as good as the accuracy of its data. Brandendo targets based upon actual latitude and longitude coordinates and not derived latitude and longitude. Target physical addresses with digital advertising based on actual GPS data and not on IP-based targeting.
Our location data is not stored in grids (segments) which allows our targeting of custom shapes to utilize the actual latitude and longitude of the drawn shape. Other solutions that have a grid-based data retrieval system inherently pull users from a grid, which may fall outside of a custom shape.