Many articles have been written on the topic of social media analysis. So, what difference does this article make? Well, it makes a huge lot of difference, starting from the very core indicators of social networks to the complex derived quantity.This article is based on the 3326 data on Twitter Social Networks for each individual, collected within the time frame of 1 week. So let’s get started:

Remember, I am only about to talk from the perspective of product marketer only, this way there is less confusion.

The first thing is to know is your fundamental goal and its relation to the people in your network:

1. Are you selling your product to the people on your network?
2. Are the people in your network already utilizing your service or product?

Both may sound similar question but are quite different in the context. And handling both questions requires different approach in the social network.

When you are selling or launching new products, you really have to be at the edge of your seat and track down each tweet made by the people. But when you are analyzing the user response to your products, you have to listen to the tweets related to your company or products. This is some hard and manual work. But from this you will know exactly know what kinds of tweets are going to drive those mass into your sites. It’s not some SEO that I am suggesting. It’s what you can hear these days as Social Media Optimization.

The post will mainly deal with ways of measuring your networks. Some of the parameters which will allow you to analyze tweets are:

1. Tweets per week.
2. Tweets with link.
3. Tweets without link.
4. Number of redundant tweets.
5. Number of replies made by the user.
6. Number of Retweets made on the tweets.

Lets discuss few parameters:

1. Tweets per week will allow you to analyze the energy of your network. Staying in a dead network is the last thing you want to do, if u are marketing. Also, staying in a highly energetic network is going to dissolve your tweets in to the mass. Hence an optimization is required which can be done through proper decision management.

The above graph shows the activity of 3326 people in one random network. You can see that there are 2 people withmaximum tweets identify such tweets and configure their usefulness. It’s important to understand the characteristicsof tweets frequency and its nature to the people.

2. Tweets with links and tweets without linksAdding a link to the tweets is one of the major components of the twitter marketing. Therefore, knowing the distribution of the number to tweets with and without link is going to describe your network much better.

The above chart shows a relation-ship between the numbers of tweets with the number of RTs done for those tweets.

In this network you can find that there is an individual whose tweets has not been retweeted but has maximum tweets links. What do you make of it?I would certainly remove such users. The other interesting thing is the profile with maximum RT but less number of tweets, now that is what I consider quality and is the very goal of each marketer – to float the links as many as possible.

The other parameters like number of replies and identifying redundant tweets are important factor to know your network much better.

The process and the system for these kinds of analysis are new. The reason is that for the first time we are able to collect large amount of data regarding the consumer’s behavior.Online social network has opened a new domain of analysis. The fact and the points being mentioned are only the tip of the ice-berg. With more enhanced analysis on the matter, soon we can have a collection of useful metrics that can clearly identify the needs of market researcher or any other professional to help them understand what consumer want.