Wednesday, February 13, 2013

Mobile Analytics

Data analytics, big data, data scientists, etc., are terms that you hear about more and more every day. The ability to collect and turn data into knowledge and make decisions based on that knowledge can give one company a competitive advantage over another.

Another technological area that is taking over the world is mobile. Smart phones and tablets are popping up everywhere and are quickly replacing laptops and desktops as the main source people use to access the internet.

Put these two fast growing areas together and what do you get? Mobile analytics.

As more and more people use mobile devices to access the internets, it is going to be crucial that business be able to track and analyze how they are interacting with their websites. Some of the types of data collected as part of mobile analytics typically include page views, visits, visitors, and countries, as well as information specific to mobile devices, such as device model, manufacturer, screen resolution, device capabilities, service provider, and preferred user language.

 Collecting and analyzing this data is not only needed to help improve marketing and sales, but is also important for maintain and updating company websites. With cell phones and operating system versions being released a break neck speeds, it is important to know exactly what devices are accessing sites so that the site can be continually optimized to function with each successive device and operating system.

Unfortunately, traditional analytics do not always work well when applied in a mobile environment. Traditional analytics software on a mobile website may only provide data for HTTP requests coming from the most advanced mobile browsers, such as those found in the iPhone and other smart phones and PDAs, with no data on other mobile devices browsing the site.

Traditional web analytics software that uses server log parsing and associates different IPs with "unique visitors" may fail to identify unique visitors, because the IPs from which cellular wireless network HTTP requests originate are the gateway IPs of the network access providers. Several dynamic server-side platforms are used to develop mobile sites. Server-side tracking code is recommended for more accurate analytics reporting.

 Solutions for Mobile Analytics

So what are some good solutions that business can use to improve their ability to analyze mobile traffic?
  1. Bango 
  2. Google Analytics
  3. Pinch Media & Flurry Analytics


Bango is an analytics platform for both mobile apps and the mobile web. Bango provides identification for every user accessing the app, providing information like the user’s carrier and connection speeds. You can also use Bango to drive mobile app campaigns and implement tracking for other application features. Bango offers integration of their analytics into most major mobile smart phones, including Blackberry, iPhone, Android, Palm, Windows Mobile and Symbian.

Google Analytics 

Google Analytics is most famous for providing a free and powerful analytics platform for websites, but unknown to most, it also offers a leading mobile analytics platform. The platform is easily incorporated into a mobile app for Android and iPhone, in addition to mobile web applications and sites. Their mobile web analytics are available to developers in PHP, JSP, ASP.NET and Perl to allow for easy implementation. The service is free and the interface is very similar to their website analytics.

 Pinch Media & Flurry Analytics

Pinch Media, and Flurry, two leading mobile analytics platforms, recently merged. They provide a free specialized service for analytics in mobile apps. They allow you to tap into user info with the approval of the user, giving you location, age, time, session lengths and more. You are also able to send messages and information to the analytics for later analysis. Sending information about what the user does while in the application is a great way to take advantage of such features. Pinch and Flurry also offer advanced analysis features like the ability to judge a user’s loyalty based on the number of sessions they have spent within the app.


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