1) Using the forecast model for pasta shown in Exhibit 5, what is your forecast of the demand for pizza?
In Annex I, we see that the forecasted demand for pizza is 1.6MM, which is represented by the Trial Households. We calculated this by using the calculation in pasta that BASES used for pasta case. We found that the trial rate for “actual definitely would buy” for pizza will be 80% of the definitely would buy rate of the BASEL research. The actual probably would by is taken as 30% of the research’s probably would buy rate. After calculating the actual rates, we summed “definitely would buy” and “probably would buy” in order to calculate the trial rate, which is 27%. Before estimating the demand, we should calculate “marketing adjusted trial rate”. In order to calculate that rate, we took the average of the three different awareness ratios. Therefore, according to our analysis, the awareness ratio is 24%. The marketing adjusted trial rate is 2.7%. The demand for the pizza is the multiplication of marketing adjusted trial rate and the target households, which is 1.6MM, in our analysis.
2) How do the pizza concept test results (Exhibits 7 and 8) compare with the findings for pasta (Exhibits 3 and 4)?
In the table below shows that the pasta “definitely would buy” ratio and “probably would buy” ratio are greater than that of pizza case.
The table below, which represents the research on likes and dislikes for the pasta and pizza products, shows that the like ratios for pasta are greater than that of pizza. Therefore, we can say that people looks more favorable to fresh pasta concept rather that fresh pizza concept. Moreover, the people also rated the pizza dislikes more that pasta case. For example, the people finds the price too expensive is 27% in total, whereas, that ratio for pasta is only 8%. Therefore, there are definite signs that show people do not like the fresh pizza case but they like fresh pasta case.