First, can the value of data be on par with resources such as gold or oil?
Well, Wired magazine seems to think so in their 2014 article “Data is the New Oil of the Digital Economy”. This has led to the belief that data is becoming an invaluable resource, but what exactly do we mean by ‘data’?
With the rapid development of AI technologies in recent years, without a doubt, there are more tools and services that help to extract valuable information from untapped sources. In addition, this information can be applied to market analysis, advertisement placement, risk assessment, and more.
Secondly, where does this information come from? Where are the rich oil mines? What are the untapped resources? The answer is
“Mobile Telco Data.”
Groundhog has been processing telecom data for over 20 years. Especially from geolocation to enriching data for Marketing Intelligence and digital advertising. Some telco data assets that we have experience with are the following:
As long as a phone is connected to a network, we can triangulate the latitude and longitude of phones in proximity to cell towers in order to determine location behaviors. In addition to this, we are able to find target audiences based on their moving behavior, categorizing areas based on their lifestyles (e.g. residential, business, activities, office workers who commute by public transportation vs their own vehicles), interests, and hobbies (e.g. city lover vs outdoor adventurer).
Above all, our Marketing Intelligence covers raw telco data into “labels” which can be used by advertisers to create audiences and target them more accurately. As well as that, brands and advertisers can identify specific patterns and cycles from location and moving behaviors, then predict where a target audience may be at a certain point in time, reaching out to potential customers who will pass by their stores in advance.
Internet browsing history
Telcos analyze internet browsing behavior through Deep Packet Inspection (DPI) probes or DNS query log analysis. The online behavior patterns of visiting specific website domains or categories of parts can be used to create labels based on behavioral characteristics, preferences, and other information. These tags can then be used to find out target user groups with specific behaviors or interests for subsequent applications.