1 . Executive summary
The NEWFOOD Corporation is a company that is looking to expand their market by introducing a new low carbohydrate food product. The new product has been dubbed K-Pack and will be packaged similar to a candy bar. Mr. Johnson, CEO of NEWFOOD Corporation, expressed interest for determining the K-pack demand and a good marketing mix impact. The marketing mix will incorporate variables such as price, advertising and promotion strategies. Susan, the NEWFOOD marketing director, predicted a positive result from introducing the K-pack to the diet/snack food market. As a marketing initiative, NEWFOOD decided to conduct a 4-month test market study of sales at 24 stores in 4 different cities. Susan’s prediction states that NEWFOOD’s K-pack sales in cases of 24 packages will be 750,000 and total revenue of $6.3 million. This is under the assumption that 70% of retail price is revenue to the manufacturer. Manufacturing costs are projected at $1.75 million, the sum of the manufacturing fixed cost of $1 million and a total variable cost of $1 variable cost per case. After adding the advertising expense of $3 million, the total net margin was calculated to be $1.55 million. Based on our analysis, we suggest launching the K-Pack at the $0.50 price per package with a $3.5 million advertising plan. Our regression model information is as follows:
Avg Sales = 18.7 + 54.0 Advertising + 3.62 Volume + 49.1 Price 50 + 17.3 Price 60
24 cases used
Predictor Coef SE Coef T P
Constant 18.69 53.91 0.35 0.733
Advertising 53.98 10.33 5.23 0.000
Volume 3.622 1.012 3.58 0.002
Price 50 49.10 13.28 3.70 0.002
Price 60 17.35 13.03 1.33 0.199
S = 24.8515 R-Sq = 69.1% R-Sq(adj) = 62.6%
Analysis of Variance
Source DF SS MS F P
Regression 4 26260.7 6565.2 10.63 0.000
Residual Error 19 11734.4 617.6
Total 23 37995.1
Source DF Seq SS
Advertising 1 13277.5
Volume 1 4089.8
Price 50 1 7798.4
Price 60 1 1095.0
2. Background of the problem (problem setup and experimental design) (1 pt) NEWFOOD is planning to introduce K-Pack, a new product, to markets. To ensure success, the company decided to test the market by putting several variables that need to be considered in order to better evaluate K-Pack sale. To find the optimal marketing mix ,those variables include difference in pricing - 50 cents, 60 cents, and 70 cents per package- ,advertising cost which is either at 3million or at 3.5 million, and location option either in bakery section or in breakfast food section. Prices and location were to be varied across stores within a city while advertising was varied across cities.
With all 3 mentioned variables (price, advertising level, and location), the company designed their experiment by putting those variables differently to each 24 different stores in 4 different cities and run them for 4 months.
In order to incorporate all variables in our experiment & analysis, we rely on dummy variables technique to add in some aforementioned categorical variables. Using Minitab analysis, we derive Regression Model used to predict the profitability of the product.
Planning and Experimental Assumptions
The most important assumption that we have made is that the test market results are an accurate reflection of national market reception. Another assumption is that the local spot TV ads would have the same impact of national ads. Our sales assumption is that we make is that future average sales per store of the four months will be consistent throughout the year with little competition in the first year. Analysis assumptions
As with all regression analysis, we assume that the regression conducted has normality and independence of errors, and a constant variance. Our analysis in this case scenario assumes...