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Regression Analysis for Sanitary napkin

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Regression Analysis for Sanitary napkin
Regression Modeling for Brand Xmarcom Strategy
Analytical approach using Tracking Research data
Approach:
The analysis of brand Sofy has been done with a two stages of statistics and model building approach.
MATRIX IDENTIFICATION
At the very first stage the data for Sofy was plotted in scatter graphs for pattern identification. The various combinations of variables for independent and dependent variables were taken to shortlist the variables for further scientific tests.
TEST AND ANALYTICS
In the next stage of scientific data analysis, test of significance was performed with 90% confidence level to understand the significance of relationship between independent and dependent variables. These tests of significance (T-test and F-Test) are followed by Regression model building approach to understand in what proportion each of these potential variables are impacting dependent (target) variables. At this stage different permutation and combination of variables were performed to understand the relationship and impact.
MODEL DEVELOPMENT
Finally, on the basis of above experiments at different stages, the entire analysis has been divided into three macro levels. These macro levels are
a. Awareness level: It was analyzed by considering Sofy awareness (aided) as the target variable (dependent) with respect to TV awareness (Aided), Newspaper and Shop display at 90% CL.

b. Brand Image level: It was analyzed by considering various messages (Trust, Well known, No leak, Absorbent, No Sideleak) of brand Sofy in relation with TV, Newspaper, Shop and heard from a friend (word of mouth) at 90% CL.

c. Purchase Intention: It level was analyzed by considering variables of previous two levels. The dependent variable was considered as Intention to purchase with respect to TV awareness (Aided), Newspaper Display, Image as Well known, Trust, Shop display and heard from a friend (Word of mouth) at 90% CL.

MATRIX IDENTIFICATION Findings:
TV awareness (Aided) is

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