Location-Based Targeting on Dochase Adx

Location-Based Targeting on Dochase Adx

A greater understanding of where consumers have been, where they are, and where they’re going leads to a clearer picture of who the consumer is–revealing patterns and enabling predictions. For example, if a consumer commutes into the center of a city from a wealthy suburb every day, they can be assumed to be an affluent individual. The shops and restaurants they visit might support this assumption. Similarly, if someone visits a university campus each day and returns to a student hall at night, they might be assumed to be a student.

Dochase has been able to harness Location-Based Data to target customers when they are close to your store. Our access to location data makes it possible to create highly relevant mobile targeting campaigns by ensuring your target audience receive personalized and useful content at the best possible time.

Location data comes in quite handy to target mobile devices effectively, enabling real-time message delivery based on a device’s location. Besides, real-time location intelligence can be used to build audience profiles that make it possible to create highly personal mobile campaigns by applying the offline behavior of users to the targeting process.

In the past year Dochase has used location data to transform mobile marketing,  Location-based marketing introduce both new targeting technologies and improving the ability to define and track audiences and behaviors.

Here are a few examples of how location-based data is driving marketing innovation on mobile, going far beyond the standard geo-fencing methodologies:

  • Proximity Targeting:

Delivering ads based on users’ real-time location, typically defined as proximity to specific place(s). For example, “all users within 100 meters of a Domino Pizza store” or “users in Lagos who are currently at a Shoprite Mall”.

  • Location-based Audiences:

Deriving an understanding of a user, based on analyzing that specific user’s location history. Analysis of geo-behavioral patterns can be used to infer demographics, behavioral attributes, and geographic attributes (i.e. where the user lives or works). 3rd party data (e.g. purchase data, TV viewership, car ownership etc.) can be joined to provide an understanding of home location. (MMA Location Committee Guidance Report: Location Audience Targeting)

  • Attribution:

Measuring store visitation or attaching purchase data (as described above) from location data. These metrics can be used to measure the ROI of ad campaigns.

  • Location-based Creatives:

Dynamically modifying ad creative based on the user’s location. Typically this breaks down into two categories: modifying the creative itself (e.g. inserting the address or phone number of a location in the creative or inserting a localized offer) and modifying the click action on the creative (e.g. click-to-call and click-to-map/navigation actions.)

Location data makes it possible for marketers to effectively target omnichannel customers, most of whom start research on a smartphone but end on a different device.

Finally, location data offers much more than highly targeted ad experiences for brands. With increasing access to real-time location intelligence that is quite accurate, you can use location intelligence to gain competitive insights, solve the issues of offline attribution and create more personalized ad campaigns for your brand, resulting in more conversions.

Comments are closed.