A Statistical Approach to Pick the Most Impactful Advertising Channel for your product
In the wake of ZMOT (Zero Moment of Truth) it becomes pivotal for any product company to choose the most appropriate advertisement channel for the promotion of their products. This not only helps the organizations to maximize their chances of creating the best first impression but will also help them to be discovered by today’s tech savvy consumers.
Today we will talk about a very interesting method of performing a statistical analysis to pick the most appropriate Ad channel to introduce your product or service to your potential customers. This analysis is called as Simple Correspondence Analysis which is very simple and straight forward.
This analysis can help to isolate specific Ad Channel corresponding the most to a particular product that was sold to a potential customer.
So let’s get started !!!
What do we need?
We need historic data which tells us which product was sold via which channel and how many times. So, for the purposes of this tutorial I created a dummy data set which shows the count of a particular product being sold post its add on a particular channel.
Sep 1: Get Data
Step 2: Start “The Data Crunching” (I used Minitab to perform this analysis)
- Open Minitab
- Go To Stat
- In Stat select Multivariate
- Within Multivariate Select Simple Correspondence Analysis
- Once in the Simple Correspondence Analysis Console is up. Start putting in the stuff
- Also Click on “Graphs” and check the box labeled “Symmetric plot showing rows and columns”
Once all the options are selected Minitab creates the following plot:
Looking at the plot it is pretty evident that majority of the products, Product 1,4,5 tend to associate pretty nicely with Social Media (positioned close to each other) and Product 3 & 2 are more closely related to Paper Ads and Television.
This gives the business a much better understanding of its potential sales strategy associated with a particular ad channel and pretty strongly position’s the organization to know how their consumer reacts to a particular touch-point.
In my next article I will talk about another statistical tool that can help the business to glean more insights out of the data with a real impact on the business’s profit margins.