About Surveys

Qualtrics provides great data analysis.  Its survey software is constantly updating in real time, so results of a survey are constantly being reanalyzed and updated.  Some examples of the data analysis done by this survey software are: basic descriptive statistics, cross tabulations (chi-squared, etc.), graphic displays, and more.  I like it because it is much less work than calculating it out by hand, and it doesn't need to be exported to another program to do the initial data analysis, though it may be exported for more in depth analysis.

Recently I was trying to figure out a way to do Least Square Regression without having to use matrices.  I looked for quite awhile online for some ideas on how I could do this.  Using Matrices to tackle regression problems become a problem themselves because the matrix computations required to determine regression take a ton of computer power and often bog down systems.  It is just too much for the computer to do quickly. So a way around this is by using summations.

With Least Squares Regression we are trying to determine our intercept and our coefficients of x.  You do have to be familiar with summation notation to understand this.  What we are basically doing in this approach is trying to minimize the difference between are dependent variable, y, and our function of x, f(x).  The summation notation for this is:

∑[y-f(x)]^2=minimum

Because our f(x) is essentially f(x)=y=a+bx, so then we can have a summation of:

∏=∑[y-(a+bx)]^2=minimum

In a Psychology of Gender class, my group did a study on gender preferences in relation to desirable characteristics of the other gender. Qualtrics online survey software allowed us to create gender subgroups and analyze how males and females answered each question differently. The subgroups allowed us to find out which characteristics are more desirable for each gender. Graphs and tables are easily created for each subgroup with Qualtrics online survey software.

With W-2's, 1099-T's, and 1040s we come to truly appreciate our beloved tax bureaucracy, the IRS. Tis the season for paying taxes. With the passage of April 15th, I once again am grateful for little tools that help me prepare, the barely legible tax forms. I personally use H&R Block for my taxes, but my brother uses Turbotax, both cost about the same. Yet, this tax season I was truly inspired by an accounting companies ingenuity. They used Qualtrics, to import the tax forms and sent the forms to their employees. Brilliance!

I actually was able to help them import one of their forms regarding research and development, it was about 10 pages long and only took me about an hour to import streamlining the whole process. I imagine that the hour I spent uploading this form saved their accountants a lot of time. Corporate taxes are much more complex than personal taxes, hence the need for a good CFO, but I was amazed at how Qualtrics was able to integrate and organize their data. I've been thinking about this myself and I might just  steal this idea for my personal taxes next year.

Determining what customers want and determining the trade-offs they are willing to make can be very useful information for a company to have.   Conjoint Analysis is a statistical technique that allows you to quantitatively assess the relative importance of individual components of a product or a marketing strategy.  It magnifies the joint effects of mulitiple product characteristics.  It can predict the customer switch rate from one product to another.  It can predict the reaction to new strategies and products.  It can predict the customer response to alternative pricing strategies.  It is a great tool that aids in decision making. 

Conjoint analysis starts off with a survey of the customer base you are targeting.  Qualtrics.com has conjoint functionality with a template that really makes easy the process of putting a conjoint survey together.  It is under their "advanced elements" option.  An example of a basic scenario in which this technique would be helpful follows:

A marketing manager of a athletic shorts company wants to get a better understanding of the trade-offs their customers are willing to make and their happiness level associated with those trade-offs.

They determine four factors they feel are important with different attributes within each factor:

Short Color: Red, Blue, Black

Price: $15, $20, $25

Inseam Length: 14 inches, 18 inches, 20 inches 

Pockets: Pockets, No Pockets

The survey will ask questions about the importance of these different factors to the individual customers.  The questions will ask how much more important one factor is than another. 

The actual analysis of the a conjoint study is difficult, but valuable.  It provides beneficial intelligence about the best interactions of product factors and want customers want.   There are programs that can aid in the analysis (SPSS, SAS, Qualtrics, etc.) and this is probably the best route to take.