Market Segmentation and Pricing

You have been hired as the new marketing manager of a company that sells a commodity cement product in two regions in South Africa. Your MD asks you to assess the company's current pricing strategy.

The company has traditionally segmented its customers into Low, Medium and High Value segments based on the volumes derived from each. Effectively you have three market segments across two regions

The company's pricing policy has been to reward volumes with lower prices.

A new competitor is entering the market and you are well aware that their strategy in other markets has been to target a specific segment and then capture them through aggressive pricing.

In order to understand the relationships between pricing across segments and regions, you run an ANOVA study as detailed in the outputs.

The variables in the ANOVA are:

Region: Region A and Region B

Segment: Consists of three segments, Low Medium and High Value customers

The dependent variable is The Rand price paid by customer per equivalent delivery of cement.

3a Review the ANOVA output and assess the company's pricing policy. (10)

3b Your MD asks you to specifically comment on whether any segments may be in danger of attack by the new competitor. What is your response? (5)

NOTE The SPSS ANOVAoutput is in the excel ouputs file.

Found Below

Univariate Analysis of Variance

Between-Subjects Factors

Value Label N

Segment 1.00 Low 12

2.00 Medium 12

3.00 High 12

type 1.00 Region A 18

2.00 Region B 18

Descriptive Statistics

Dependent Variable:

Segment Mean Std. Deviation N

Low Region A 825,8333 10,68488 6

Region B 822,5000 2,73861 6

Total 824,1667 7,63763 12

Medium Region A 845,8333 5,84523 6

Region B 821,6667 4,08248 6

Total 833,7500 13,50505 12

High Region A 775,0000 13,41641 6

Region B 770,0000 6,32456 6

Total 772,5000 10,33529 12

Total Region A 815,5556 32,21659 18

Region B 804,7222 25,63730 18

Total 810,1389 29,21561 36

Tests of Between-Subjects Effects

Dependent Variable:

Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Noncent. Parameter Observed Powerb

Corrected Model 27911.806a 5 5582,361 85,335 0,000 0,934 426,677 1,000

Intercept 23627700,694 1 23627700,694 361187,781 0,000 1,000 361187,781 1,000

Segment 26051,389 2 13025,694 199,119 0,000 0,930 398,238 1,000

region 1056,250 1 1056,250 16,146 0,000 0,350 16,146 0,973

Segment * region 804,167 2 402,083 6,146 0,006 0,291 12,293 0,856

Error 1962,500 30 65,417

Total 23657575,000 36

Corrected Total 29874,306 35

a. R Squared = .934 (Adjusted R Squared = .923)

b. Computed using alpha = .05

Post Hoc Tests

Segment

Multiple Comparisons

Dependent Variable:

Tukey HSD

(I) Segment Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Low Medium -9.5833* 3,30194 0,018 -17,7235 -1,4432

High 51.6667* 3,30194 0,000 43,5265 59,8068

Medium Low 9.5833* 3,30194 0,018 1,4432 17,7235

High 61.2500* 3,30194 0,000 53,1098 69,3902

High Low -51.6667* 3,30194 0,000 -59,8068 -43,5265

Medium -61.2500* 3,30194 0,000 -69,3902 -53,1098

Based on observed means.

The error term is Mean Square(Error) = 65.417.

*. The mean difference is significant at the .05 level.