Short Note on Long Tail

The title must have caught the attention of every one. Nevertheless I feel it is very apt and as you read through the blog you will also find the same.


Long Tail is a concept pioneered by e-commerce giants like Amazon and e-Bay to leverage the benefits of selling those goods that are rare to find in the shelves of stores and super markets. The unique selling point of this concept is making everything and anything available to the customers by leveraging the fact that esoteric items are hard to find in the store shelves. In short a large number of less frequently sold items have as much sales as a small number of more frequently sold items.


Long Tail Keywords also known as narrow keywords are those  keyword phrases that bring up as much traffic to the website as those few generic keywords that account for a majority of the traffic. There are two unique selling points for this kind of strategy. Firstly, long tail key words are less competitive and hence it is easy to get ranked first on the google ads than short tail key words. Secondly, when the customer is looking to purchase something specific, they tend to use specific search terms and hence you are quiet likely to have more conversions in this case than when you are using short tail generic keywords.


Here are some interesting links to learn more about Long Tail Keywords


Long Tail Vs Short Tail Keywords


Keyword Strategies - Long Tail vs Short Tail


Research and Find Out Long Tail Keyword for your ROI


Three Good Reasons to Target Long Tail Keywords

Networks, analyses and predictions

We live in a age of social networks. Independent of wherever we go, we are always connected to the people we want to. Added to that we maintain different types of contacts depending upon the people we befriend. However, most of these connections are implicit and are not disclosed for the reasons of privacy.But we might end up in a situation where we need to investigating these connections becomes a necessity.

The figure shown above represents the pattern of e-mail communication inside Enron at the time of Scandal. The size of the nodes represents the relative importance of the personnel in the network and the thickness of the edges represent the number of messages communicated.  At the first sight it is clearly palpable that Tim Belden is in the middle of the communication during the crisis with a few others like Amy FitzPatrick and Chirstopher F. Calger  playing an important role in the crisis communication. Thus we can clearly identify the crisis leaders just from the visualization of the network.

The example in the previous paragraph is one of a rare case and company e-mail networks are not investigated unless a scandal of the sort of Enron breaks out. However, in our daily life we come across many networks. Twitter is an example of a network which if visualized can unravel daily communication patterns.  Of course, we have other networks in the form of Wikipedia - where authors collaboratively edit articles and YouTube- where users post comments and replies. An analysis of all of these can reveal significant hidden information that can be exploited in various area like advertising, investigation, prediction etc ..

Lecture 5: Network Analysis

In short, the theme of this lecture is "Networks in an Online World".

We live in a world dominated by Online Social Networks. While people connect with each other in different ways, it would be interesting to know whether there are any connection patterns that can reveal some interesting patterns about the way they connect and about them in general.

The figure below is an example of  a network for a Linkedin User.

While we can see many clusters on the network, it is clearly palpable that there is one big cluster that is densely connected. This reveals that the user has a strong connected network in one area.

The network shown above doesn't have any directionality. However, there are some social networks that have directionality like the Twitter network. Visualization of these networks can reveal some interesting properties.

However, studying networks goes far beyond visualization and gets into the study of objective parameters like authority, hub, density etc., In short network analysis is a comprehensive tool for objective analysis.