Interesting Read - "Appily ever after: A smartphone shrink"

A proliferation of psychology smartphone apps - with names like BreakkUp, iStress and myinstantCOACH - purports to help us live happier, less anxious lives. As Mark McGonigle, a therapist in Kansas City, Mo., who invented the app Fix a Fight, puts it: "Electronic devices don't have to drive us apart. They can bring us together." Which sounds so good. A few bucks and a lot of squinting into my phone: that certainly beats a $300-an-hour psychiatrist, right?

Read the full article here: http://gadgets.ndtv.com/apps/news/appily-ever-after-a-smartphone-shrink-351299
Funny stuff, this !!

Cluster Analysis - What it is?

Cluster analysis is a class of statistical techniques that can be applied to data that exhibit “natural” groupings. Cluster analysis sorts through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases or observations. Objects in a cluster are similar to each other. They are also dissimilar to objects outside the cluster, particularly objects in other clusters.

In marketing, cluster analysis is used for

·         Segmenting the market and determining target markets

·         Product Positioning and New Product Development

·         Selecting test markets

Examples

The diagram below illustrates the results of a survey that studied drinkers’ perceptions of spirits (alcohol). Each point represents the results from one respondent. The research indicates there are four clusters in this market. The axes represent two traits of the market. In more complex cluster analyses you may have more than that number.

Another example is the vacation travel market. Recent research has identified three clusters or market segments. They are: 1) The demanders - they want exceptional service and expect to be pampered; 2) The escapists - they want to get away and just relax; 3) The educationalist - they want to see new things, go to museums, go on a safari, or experience new cultures.

Cluster analysis, like factor analysis and multi-dimensional scaling, is an interdependence technique: it makes no distinction between dependent and independent variables. The entire set of interdependent relationships is examined. It is similar to multi-dimensional scaling in that both examine inter-object similarity by examining the complete set of interdependent relationships. The difference is that multi-dimensional scaling identifies underlying dimensions, while cluster analysis identifies clusters. Cluster analysis is the obverse of factor analysis. Whereas factor analysis reduces the number of variables by grouping them into a smaller set of factors, cluster analysis reduces the number of observations or cases by grouping them into a smaller set of clusters.

Apps dominate smartphone usage, survey finds

According to figures collated by analytics firm Flurry, over the past five years smartphone usage has become increasingly tilted towards heavy app use.

Read more at http://www.trustedreviews.com/news/apps-dominate-smartphone-usage-survey-finds

Relative Importance of purchase determinants

Based on the responses received, the relative importance of purchase determinants for apps for different categories was assessed, and charts were created in MS Excel for ease of presentation.
(The charts represent average importance of various factors on a five point scale, 5 representing highest importance)

Questionnaire Snapshot

A snapshot of the questionnaire developed to assess the relative importance of purchase determinants of Smartphone apps, and to cluster the users of apps.

A broad Classification of Smartphone Apps (to study purchase determinants)

Now that we have established the validity of extended TAM for acceptance of Smartphone apps, let us examine the key determinants in deciding the purchase of Smartphone Apps. Because customers may have different consideration factors in deciding the purchase depending on the App type, we first classified Apps into 4 categories:

Productivity Entertainment, Information, and Networking

Let's dive deeper !!

The scope of this research has been extended to dive deeper into the world of Smartphone apps. The objectives of the study are three-fold:

• To propose an integrated theoretical framework of Smartphone Applications’ acceptance and intention to use based mainly on the Technology Acceptance Model (TAM). 
• To identify the key determinants in deciding purchase of Smartphone applications and establish their order of importance.
• To analyze the usage pattern of Smartphone apps and to classify the users into different groups based on their usage of apps and factors they consider during purchase of apps.