Design a Marketing Experiment Sample Report

Introduction

This report fundamentally aims to develop a marketing experiment for Instituto´s drinks by The UTEC Uruguay Company. The campaign is all about TV advertising campaign highlighting “feeling the taste”. With  the growing taste consciousness among the audience, the taste of drinks is increasingly becoming an  important consideration of the consumers. The experiment is going be a before –after design  experiment. I am not going to focus on full factorial, as it will be difficult & time-consuming to quantify  impact on sales if several parameters are changed at the same time.

Experiment Design

In this experiment, the independent variable is increased TV advertising campaign. On the other side,  the dependent variable observed here is amount of sales. The experiment will be run in Philadelphia,  PA. The control market observed will be San Antanio, TX. Both are the two resemble cities of USA. The  test and control markets are so chosen that they resemble closely in terms of population, demographics  and other city attributes. Both Philadelphia and Antanio are similarly sized cities with a population of  around 16, 000, and 00. Since the entire cities will be exposed to the experiment, the sample size would  be big enough to be statistically significant. Since it is a before-after design experiment, sales will be  recorded for both control and test markets for a 3 month average from June-August. The experiment  will be run for the next three months from September – November. The change in sales during the  experiment will be then used to calculate the lift in sales. The experiment certainly adheres to the first  three rules of causality. However, the experiment has no control over the fourth rule, which deals with  the presence of external factor. Prima facie, there appears to be no external factor influencing the  experiment, however there might be competitive response that shall be accounted for.

Anticipated Issues

Both the before and during experiment results are collected during the summer months from June to  August. If the field implementation is executed anywhere between September to November, the winter  months might see the dampening in the impact due to the seasonality involved. Any other external  factor during implementation such as a new competitor entering the market or decrease in prices from  competitors could adversely affect the field results.

The above-mentioned issues might have an adverse impact on the sales; however, the experiment will  still demonstrate the impact of TV advertising on sales. The seasonality and external factors  notwithstanding, the experiment will provide a fair guideline on whether to go ahead with the  nationwide marketing campaign. The lift in sales would also provide a concrete idea on the appropriate  amount of spending on the campaign.

Experiment 2.0

Another version of the experiment can be through paid web advertising, which is mostly used, now days  in the marketing. Web advertising is so popular because it provides much better control on the target  audience, test markets and analytics. Hence, it can be a full factorial design with the independent  variables as both price and advertising theme. This will also yield or generate more informative results  such as:

 It demonstrates the impact of more than one independent variable    The web analytics gives far more insights on the buying preferences of the audience.    This version of experiment is also generally cheaper and quicker to implement than the offline

campaigns such as TV or billboard advertising.

The only concern with the web experiment is that it does not include the chunk of audience that is  not so active on web. In the context of this particular product, that chunk of inactive users could be  huge.


Design a Marketing Experiment Sample Report Introduction This report fundamentally aims to develop a marketing experiment for Instituto´s drinks by The UTEC Uruguay Company . The campaign is all about TV advertising campaign highlighting “ feeling the taste ” . With the growing taste consciousness among the audience , the taste of drinks is increasingly becoming an important consideration of the consumers . The experiment is going be a before – after design experiment . I am not going to focus on full factorial , as it will be difficult & time - consuming to quantify impact on sales if several parameters are changed at the same time . Experiment Design In this experiment , the independent variable is increased TV advertising campaign . On the other side , the dependent variable observed here is amount of sales . The experiment will be run in Philadelphia , PA . The control market observed will be San Antanio , TX . Both are the two resemble cities of USA . The test and control markets are so chosen that they resemble closely in terms of population , demographics and other city attributes . Both Philadelphia and Antanio are similarly sized cities with a population of around 16 , 000 , and 00 . Since the entire cities will be exposed to the experiment , the sample size would be big enough to be statistically significant . Since it is a before - after design experiment , sales will be recorded for both control and test markets for a 3 month average from June - August . The experiment will be run for the next three months from September – November . The change in sales during the experiment will be then used to calculate the lift in sales . The experiment certainly adheres to the first three rules of causality . However , the experiment has no control over the fourth rule , which deals with the presence of external factor . Prima facie , there appears to be no external factor influencing the experiment , however there might be competitive response that shall be accounted for . Anticipated Issues Both the before and during experiment results are collected during the summer months from June to August . If the field implementation is executed anywhere between September to November , the winter months might see the dampening in the impact due to the seasonality involved . Any other external factor during implementation such as a new competitor entering the market or decrease in prices from competitors could adversely affect the field results . The above - mentioned issues might have an adverse impact on the sales ; however , the experiment will still demonstrate the impact of TV advertising on sales . The seasonality and external factors notwithstanding , the experiment will provide a fair guideline on whether to go ahead with the nationwide marketing campaign . The lift in sales would also provide a concrete idea on the appropriate amount of spending on the campaign . Experiment 2.0 Another version of the experiment can be through paid web advertising , which is mostly used , now days in the marketing . Web advertising is so popular because it provides much better control on the target audience , test markets and analytics . Hence , it can be a full factorial design with the independent variables as both price and advertising theme . This will also yield or generate more informative results such as :  It demonstrates the impact of more than one independent variable  The web analytics gives far more insights on the buying preferences of the audience .  This version of experiment is also generally cheaper and quicker to implement than the offline campaigns such as TV or billboard advertising . The only concern with the web experiment is that it does not include the chunk of audience that is not so active on web . In the context of this particular product , that chunk of inactive users could be huge .