Product testing, ad copy testing and concept testing are some common applications, though ANOVA Analysis Surveys can be used in retail environments or simulated lab-type environments created for the purpose.
Just like in a laboratory, we manipulate certain variables (like promotion, ad copy, display at the point of purchase), and observe changes in other variables (like sales, or consumer preferences, behavior or attitude). The application areas for experiments are wide.
Whenever a marketing-mix variable (independent variable) is changed, we can determine its effect. Such variables include price, a specific promotion or type of distribution, or specific elements like shelf space, color of packaging etc.
An experiment can be done with just one independent variable (factor) or with multiple independent variables. ANOVA is the general name for a variety of such experiments. The design of the experiments determines how useful the results are. The key to success in an ANOVA Analysis Survey is the degree of control on the various independent variable (factors) that are being manipulated during the experiment.
A common application for an ANOVA Analysis Survey is testing. Product testing, ad copy testing and concept testing are some common applications, though ANOVA can be used in retail environments or simulated
lab-type environments created for the purpose.
Outsource2india’s experienced researchers will help you take informed marketing decisions through ANOVA Analysis Surveys. Get in touch with us now.
We first list the independent variables to be controlled and the levels at which they need to occur. We then change the variables one at a time, keeping other variables constant, and measure the effect. These observations are used to test whether the different effects produced by the independent variables are statistically significant. The major conclusion drawn is whether the mean value of the dependent variable (for example, sales) changes with changes in the levels of the independent variable (say, promotion.)
For instance, we run a promotion one week, and then stop it for a week, and check if there are changes in sales, keeping other factors constant.
We can also check if there are interactions, or combined effects of two or more independent variables. An example would be the combined effect of the creative strategy and the model used, in the impact of an ad.
There are also other variables which indirectly impact the dependent variable, and these are called blocks.
For example, the day of the week can be a blocking variable in a retail shopping study.
Either simulated or experimental data is used in an Anova Analysis Survey. Categorical independent variables and numerical dependent variables are necessary.
Typical dependent variables are: sales, intention to buy, or interest in the concept.
Any design or marketing strategy variables, at different levels can be an independent variable. These are varied, and their impact is measured.
An ANOVA procedure using SPSS software is generated.
We then assess if there is a significant effect of the independents on the dependent. If there is a significant effect, the specific means are compared and the particular levels that are causing a significant difference in the dependent are identified.
The results of the Anova Analysis Survey can be used in designing marketing strategy, advertising or retailing strategy. Brand name decisions can also be made through ANOVA-based testing of all the options.
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