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Practice Exam

MARK 2010 Marketing Analytics

SP2 - 2023

· Question 1

For the data below calculate the:

· market share;

· purchase rate;

· penetration;

· purchase frequency;

· share of category requirements;

· 100% loyals.

Shopper	Brand A	Brand B	Brand C	Brand D
01	4	1	2	3
02	3	0	0	0
03	3	1	2	0
04	1	6	0	2
05	4	2	0	2

· Question 2

Use the actual data below and the Dirichlet model to generate the estimated penetration and estimated purchase frequency and complete the table below

	Penetration			Purchase frequency
Category	92%			9.4
Brand	Actual	Estimated	Deviation	Actual	Estimated	Deviation
Brand 1	57%			5.3
Brand 2	41%			4.6
Brand 3	34%			4.2
Brand 4	27%			3.8
Brand 5	20%			3.6
Brand 6	16%			3.5
Number of tests passed

Does the model give good fit to the actual data?

Is there any niche or change of pace brand?

How do brand 3 performance measures compare to the model estimates?

What would be the targets of penetration and purchase frequency if we want to increase brand 3 market share by 5 percentage points?

· Question 3

Using the observed shoppers of a brand (data in Table 3.1) and the CTA excel program, estimate parameters k and a of the NBD model, and the predicted shoppers (from the Estimation by loglikelihood worksheet)

Table 3.1: Distribution of purchases of a brand

Numbers of purchases (x)	Observed shoppers	Predicted shoppers
0	260
1	106
2	48
3	29
4	14
5	12
6	9
7	6
8	5
9	2
10	3
11	2
12	2
13	0
14	1
15	1
Parameter values	a =	k =

The brand has recently increased the advertising budget and there is an increase in sales in period 2 (data in Table 3.2). Get Predicted period 2 sales from the CTA LL worksheet, calculate the deviations between Observed period 2 sales in Table 2 and Predicted period 2 sales. Which shopper class is affected most by the advertising increase?

Table 3.2: Period 2 sales

Shopper class	Predicted period 2 sales	Observed period 2 sales	Deviation
Non buyers		179
Light buyers (bought 1 unit)		132
Medium buyers (bought 2-3 units)		187
Heavy buyers (bought 4+units)		302
Total		800

· Question 4

Table 4.1 contains the results of a BW score conducted on a sample of 253 respondents about the slogans Australian consumers like most to promote wine regionality. The BW experiment was designed according to a balanced incomplete block design (13, 4, 1).

Table 4.1: Count Best and Count Worst

#	Attributes	Count Best	Count Worst
1	Australian regions - discover your own backyard	153	206
2	Austalian wine - take time to rediscover	198	309
3	Australian regions – every one has a story	135	312
4	There’s always more to discover	233	216
5	Your regions, your passion	54	384
6	Australian regions – a choice to trust	106	286
7	The regions you love	369	119
8	Your regions, your love	490	80
9	Regional! Not just another wine	204	403
10	Quintessentially Australian	469	291
11	Go Regional!	80	506
12	A+ Australia	544	51
13	There must be a Region for…	254	126