Thursday, May 2, 2013

Mobile Web and App Analytics: 8 Common Mistakes you want to Avoid

        Even after the advent of mobile devices, it took a while for them to offer advanced access to the internet. iPhone was the mobile device that broke this ice and initiated more web interaction through mobile.
Now, all the major mobile device makers have implemented advanced web access and majority of them have been fairly successful in providing a superior web experience. So what does all this indicate to the digital analyst? Of course that there is another important area where we can dig and can be sure to reap some great benefits with the number of people using it and the hours spent on it. 

        Mobile websites can be tracked in a way similar to how regular websites are tracked. Some of the data collection options are

Log-based solutions: The website’s web server files contain information that might help identify mobile traffic in their headers and the URL string.
 Packet-sniffing based solution: Here incoming and outgoing packets are sniffed to read important visitor information.
Tag-based solution: are of two types, Java Script or image. [1]Java Script runs data collection scripts which analyses user requests to the servers. In the latter an image tag is used to collect data.

        These do have some drawbacks like if a phone does not have JavaScript enabled, we will be missing several information about our traffic. Some solutions also need cookies enabled and some of the phones might not even have even cookies enabled, which again causes some loss of data.

There have been severe challenges in tracking the analytics for mobile apps because of their nature. Once an app has been downloaded there was no way to track how the app was being used, unless the user provided some feedback. There was no explicit way of tracking the intended user behavior. As Avinash Kaushik puts it, many analysts stop at analyzing the devices used and the browsers. Though these do give us some information about the users, it does not represent any info related to customer satisfaction of using the apps, how they navigate from one screen to the other, are they using the app as intended, are they able to complete the tasks easily, how often are the apps used, etc.

How to Track Mobile App Analytics:

The solution to this was to apply a strategy similar to the the basic Event Tracking model. A simple database can be used to track the offline activities/events happening on the app and these can be forwarded to the Analytics tool when connected to the net. Thus we can track the user pattern and understand about customer behavior beyond the device used. The big players in the digital analytics field, which also offers mobile app tracking, are Google Universal Analytics and Adobe Site Catalyst. We have several others focusing on the vertical like Bango, Mobilytics, Flurry, etc.

“To err is human” hold true even here and there are some facts that we have to understand to glean maximum benefits from mobile app analytics. Here are some tips from [2]Mashable to avoid common mistakes.

1.      [3]Start using app analytics even before your app is in the store

If you are waiting to start using analytics after your app is added to the store then you are very late, as there is already much information relevant to the app out there.

2.      Users won’t use the app the way you expect them to

App makers might be biased about how the product should be used and hence will be in for surprises, when checking how others users use it. Hence it is better to test the app with different users and account for all the different scenarios that might arise.

3.      Pick KPIs that is relevant for your target audience

There is no universal KPI for all the apps. Apps can be of different types like content publishing, social networking, utilities, commerce and gaming. Hence the ideal KPI should be picked based on what is attempted to be achieved.

4.      Choose Analytics Provider based on the Type of App

Again, we have different Analytics provider focusing on different verticals of the app based on its type. Ex: if we are developing a mobile game Playtomic might be an ideal fit, and if it is a content delivery app Localytics or Flurry would be better.

5.      Install the Analytics Platform Correctly

 Follow proper installation protocol to ensure that it does not affect the speed of the app and also that accurate data is being collected.

6.      Analyze Market Data to Avoid Mistakes Competitors Have Already Made

Check for apps developed by your competitors so that you can learn from their mistakes and have a better understanding of the market.

7.      Pick a Provider You Can Grow With

Choose a provider who can meet the requirements as you scale. Ex: if you are using iOS now and later want an Android app as well, if you intend to monetize through ads, then the provider should cover that as well.

8.      Mobile App Analytics Shouldn’t End With Your Mobile App

Mobile app analytics should not be considered as silo. Integrating data from all of the areas where your brand is collecting data will give a comprehensive understanding of your app’s position in the marketplace. Ex: Analyzing social media with respect to the app can point us to the general sentiment toward the product, as well as identify flaws that customers are talking about.

Here is a little video from appMobi on Moble App analytics.

Concluding Statements:

Mobile app analytics is indeed an emerging field. [4]Nearly 40% of internet time is spent on mobile and [5]it is predicted that for the next five years the usage is going to increase by 66% per year. Also, [6]“the number of people regularly using mobile apps is now approximately equal to the number of people who use desktop or laptop computers to connect to the Internet, one analytics firm reported on Thursday”. With these numbers we can affirm that the future of the Mobile app analaytics field is bright and is something we should allocate resources to and learn in more detail. Inferior knowledge in the field and not being able to track analytics for mobile sites and app might not be favorable.

To learn more about this refer to
1. Web Analytics 2.0, chapter on Emerging Analytics
2. The links provided below

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