Device detection is a flexible tool that companies may use in many ways to get a better understanding of their customers. Detecting a web visitor's mobile network is a useful but little-known technique which you can get access to by using DeviceAtlas.
Detecting mobile and WiFi networks – here’s how it works
DeviceAtlas makes it possible to detect a user’s mobile network (carrier ID) based on an IP address using our Carrier API. The functionality makes it possible for customers to detect the name of the network and a number of related properties. Consequently, this functionality allows you to distinguish between mobile networks and WiFi connectivity.
The Carrier API relies on a separate data file to function which gets weekly updates. Similar to the device data file, the file can be manually downloaded from your account page or you can set up automated downloads via the RESTful API.
Here is an example showing how the Carrier API works:
from mobi.mtld.da.carrier.carrier_api import CarrierApi
ip = "62.40.34.220";
carrier_api = CarrierApi()
carrier_api.load_data_from_file("/path/to/sample.dat") // multiple calls
will reload the data file each time
// get all properties
props = carrier_api.get_properties(ip);
// .... use the properties ....
if "networkOperator" in props:
property = props["networkOperator"]
operatorName = str(property)
print("networkOperator: %s" % operatorName)
// get a single property
mccProp = carrier_api.get_property(ip, "mcc")
if mccProp is not None:
mcc = str(mccProp)
print("MCC: %s" % mcc)
The Carrier Identification functionality includes detecting the following properties:
- Network Operator
- Network Brand
- MCC (Mobile Country Code)
- MNC (Mobile Network Code)
- Country Code
- Network Type (MNO/MVNO/Proxy)
Here you can learn more on how Carrier Identification works.
Of course you can also identify if a device is 3G, LTE or WiFi-capable even if it is not using that carrier method at the moment of detection. These Boolean properties are available to all customers.
For the web, native apps and mobile operator environments.
Potential use cases
Detecting mobile networks and WiFi connectivity is often used to determine the size of content that should be transmitted to the device. You can assume that WiFi connectivity is more stable and faster than mobile network. To get more information on the possible download speed you can also use DeviceAtlas Connectivity Analysis.
Other use cases may relate to managing sales and marketing campaigns which are often targeted at users of a particular mobile network. In this way you can make sure that you reach the right audience.
Mobile Network Operators generating the most web traffic
Mobile Network Operators’ market share is typically based on the number of subscribers but it is also important to take into consideration how mobile services are used. A decade ago they were used mostly for phone calls and texting while today data consumption is arguably the most important aspect. With the Carrier Identification functionality, DeviceAtlas can track the amount of web traffic generated by mobile operators.
Here are the statistics on the browsing share of MNOs in selected local markets in 2015.
France
Mobile network | Web traffic share | |
---|---|---|
1 | Bouygues | 31.4% |
2 | Orange | 27.8% |
3 | SFR | 20.6% |
Germany
Mobile network | Web traffic share | |
---|---|---|
1 | Vodafone | 43.6% |
2 | E-Plus | 25.2% |
3 | O2 | 25% |
Italy
Mobile network | Web traffic share | |
---|---|---|
1 | Vodafone | 41% |
2 | Telecom Italia | 32.6% |
3 | 3 Italy | 25.5% |
Spain
Mobile network | Web traffic share | |
---|---|---|
1 | Vodafone | 32% |
2 | movistar | 28.3% |
3 | Orange | 25% |
UK
Mobile network | Web traffic share | |
---|---|---|
1 | 3 UK | 28.5% |
2 | Orange (EE) | 27.2% |
3 | Vodafone | 20.6% |
USA
Mobile network | Web traffic share | |
---|---|---|
1 | Verizon | 37.4% |
2 | AT&T | 29.8% |
3 | T-Mobile | 16.9% |
If you'd like to learn more on the popularity of MNOs, head over to our Mobile Web Report.
Why Device Detection Is Important For The Operator Environment
Download our free e-book to learn:
- Why today it is essential to understand all devices on the network
- How network operators can utilize deep device awareness
- How network operators can use DeviceAtlas to plan and optimize networks