on target
User Analytics: Why you need them
No, I am not talking about Web Analytics (used to optimize web pages). If software is your business, User Analytics are as important as Web Analytics and, implementing them before competition can give you a differential advantage.
User Analytics (UA) refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of software application usage.
Here are some typical answers you would expect from UA:
Who are the users of my application? What are their profiles?
How often they use my application?
How much data / information they manage through my application?
Which are the most usual tasks?
Which are the most common error?
Which is the actual learning curve, which are main obstacles?
How long does it take to become proficient with my application?
Which users are defeating? Why?
Even if software applications (compared, for example, to electronic appliance) can collect with ease all data needed to answer those questions, UA are still underused.
Only recently several applications started to systematically collect UA data. If, for example, you are an Eclipse user, you shall have noticed that Eclipse started asking you permission to transmit collected data only about one year ago.
Implementing User Analytics requires a little effort, but provides many advantages. You will be able to:
Improve user satisfaction, making your application more usable
Reduce support cost identifying and preventing common errors
Refine sales estimates by knowing who is using your application and how much
Reinforce marketing by better identifying your target profiles and your application value.
What if you could graph with a mouse click the most performed tasks by different user profiles? Their most common errors? Their usage pattern? How much they use your application? Whatever extra quantitative information you wish through a simple API call?
Requirements
In order to implement UA you need:
A clean, extensible data model that can fit with ease new needs.
Some small instrumentation (a simple API) to collect usage data.
Possibly some little automation to transmit usage data.
Cleansing and loading procedures to feed an analytic data store.
An interactive tool to explore collected information.
This may frighten at first glance, but, if you follow a systematic approach you can obtain a scalable solution with little effort that can grow to fit new needs.
I will address each one of those points in future posts from a practical and pragmatic point of view. I will show you how to a detailed data model and its SQL implementation to retrieve information in a flexible and integrated way and how to build a simple API to collect the data you need.
If you are interested, please, come back to this blog or join our mailing list (right column) to be notified of future posts.
Continued in User Analytics: the Information Model.
Are you a management consultant?
Would like to try or coach this technique with your clients, do you need any additional or technical detail? Please let me know! Component Bases Solutions has great interest in partnership with business consultants. We can help you automate your proposed solutions in a very short time. We can also help to increase your visibility through links from many management tools we make freely available on the Web. Please contact for more detail.
Did you like this post?
Please, spend a few seconds and click on button below to socially bookmark it or tweet it. It will help to promote this blog and improve its content, Thank you!
|
 |
 |
Posted at 12:00AM Jan 05, 2010 by admin in IT | Comments[0]
