Lecture 3: Getting Deeper into Analytics!!

In the previous lecture, we had an introduction to Google Analytics (GA).  We also had a warm-up exercise on GA over the weekend. It was the first time for all of us and I was very curious about it.  Because, we all know GA is used for monitoring and analyzing the website traffic but I haven’t seen it before! I haven’t seen what it does, what it displays on the screen.  I was running into wild imaginations – was wondering if it would be something like that screen you get to see in the Space Research Centers,  which is shown on news channels when a rocket is launched.  It would have all possible lines and curves – technically called a graph. But, when I first logged into the Analytics account, I got a feeling that it was no rocket science. The first (main) page on GA is simple and clear and most of all, it makes sense! Thanks to Google J. It had all the metrics which we discussed in class, listed on one side and it had a graph at the top which tells you how many pageviews the website has had over a certain period.

Our Professor told us that GA has two aspects to it. One is the Mechanical aspect and the other is the Analytical aspect. Mechanical aspect of the GA involves setting the timeline for your analysis, choosing the metric you want, etc. Analytical aspect is when you interpret and derive meaning outta the results(graphs or tables) displayed on the screen. Both the aspects are very important and can greatly influence your analysis results/decisions.

The most important metric of all is the Bounce Rate, which is used to measure the visit Quality. According to Google, Bounce Rate is defined as the percentage of single-page visits or visits in which the person left your site from the entrance (landing) page. At first, it was pretty confusing as it is very similar to another metric called Exit Rate. Exit Rate is defined as the percentage of site exits that occurred from a page or set of pages – Google. We had an interesting debate over this and all are doubts were cleared by our Professor.

This is where the lecture came to an end and we all left the class, thinking about our first homework – to analyze the traffic on our own MIS-Eller website and come up with recommendations to the least performing sections of the site.

Business Intelligence – 2nd Lecture

The second lecture started off with the definition again and so is my second blog on BI.  You can define BI in a lotta different ways. BI is such a big field. Putting it all together, BI can simply be defined as any tool, technology or technique used for collection, measurement, understanding, analysis and prediction using (past) data for Performance Management. Our Professor stressed on ‘Performance Management’, as it is the whole point of using BI for your business. BI is used to help improve business, keep track of your performance, establish goals and targets for the future and find out ways to achieve it. This is exactly where KPIs come into play.

Now, what is KPI?

KPI stands for Key Performance Indicator.

KPIs are commonly used to measure the performance of a business towards a specified target/goal which involves monitoring and measuring metrics. Metrics are defined pertinent to the business. A good example of a metric for a sales company could be: Amount of Dollars earned by sales of a product over a period of time.

Our Professor also talked about different types of data which are Unstructured, Historical and Real-time data. Data can also be broadly classified into two:

Internal – Data that a company or an organization possesses which are mainly about the operations and transactions performed.

External – Data that a company collects from discussion forums, review sites, blogs, etc. which will be helpful for its business.

I understood how data collected from these various sources is being used by companies. They don’t just use it blindly. The data that is collected is first cleansed and then it undergoes a process called ‘Data Profiling’ by which you eliminate fake, unnecessary and useless information. At this point, you will have to use the 6Ws which are called the Web Metrics: What, When, Why, Where, Who & Which.

Ex: What does a customer expect from your business? Where does he come from? Which category or age group does he belong to?

These questions help you derive some meaning outta the data that has been collected which is obviously useful for your company/business.

What makes BI interesting?

Of late, B and I are the two letters thats on everyone's mind.I was trying to figure out what makes it so interesting.

The very idea of using BI is to help improve your business, based on (past)data analysis. It helps you foresee the future and get yourself prepared for the demand/trend/rise/downfall of the market. But which part of this makes it interesting?

Is it because of the fact that it is related to social media? Of course not!

Is it because it fetches you awesome money?
Okay, this is something that you can't plainly refuse.But, it can't be a proper reason as there are loads of other things in this world which could fetch you even more money.

I guess it is probably because of the human nature. We, as humans, love to predict the future. We always think about future and we always work towards it.

When you have this kinda inborn-curiosity, you are obviously gonna like BI. It gives you a chance to analyse data and find out what customers think about a company, what opinions they have, what they like, which/what attracts them to a product/service, which are lows and highs of a company, what's the trend gonna be like in the near future, etc...obviously sounds interesting to you! After doing all of this, you also get the privilege of suggesting or recommending some solutions to the business which is like icing on the cake.

Just to test :P