In Step the big decisions are made. Informed by all the insights gained during the entire market segmentation analysis, the time has come to commit. Of the many available market segments, one or a small number have to be chosen and declared target segments. This critical step builds on the segments extracted in Step 5, profiled in Step 6, and described in Step 7, as well as on the segment attractiveness criteria selected and weighted in Step 2. The process requires the involvement of the segmentation team and the advisory committee because decisions made at this point will result in a long-term organisational commitment affecting all organisational units. The two key questions that need to be answered in this step are: (1) which segment would the organisation most like to cater to; and (2) which organisation would members of the market segment most like to buy their products or services from?
1 The Targeting Decision
Step 8 is where the rubber hits the road. Now the big decision is made: which of the many possible market segments will be selected for targeting? Market segmentation is a strategic marketing tool. The selection of one or more target segments is a long-term decision significantly affecting the future performance of an organisation. This is when the flirting and dating is over; it’s time to buy a ring, pop the question, and commit.
After a global market segmentation solution has been chosen – typically at the end of Step 5 – a number of segments are available for detailed inspection. These segments are profiled in Step 6, and described in Step 7. In Step 8, one or more of those market segments need to be selected for targeting. The segmentation team can build on the outcome of Step 2. During Step 2, knock-out criteria for market segments have been agreed upon, and segment attractiveness criteria have been selected, and weighed to reflect the relative importance of each of the criteria to the organisation.
Optimally, the knock-out criteria have already been applied in previous steps. For example, in Step 6 market segments were profiled by inspecting their key characteristics in terms of the segmentation variables . It would have become obvious in Step 6 if a market segment is not large enough, not homogeneous or not distinct enough. It would have become obvious in Step 7 – in the process of detailed segment description using descriptor variables – if a market segment is not identifiable or reachable. And in both Steps 6 and 7, it would have become clear if a market segment has needs the organisation cannot satisfy. Imagine, for example, that the big spending city tourist emerged as one of the very distinct and attractive segments from a market segmentation analysis, but the destination conducting the analysis is a nature based destination in outback Australia. The chances of this destination meeting the needs of the highly attractive segment of big spending city tourist are rather slim. Optimally, therefore, all the market segments under consideration in Step 8 should already comply with the knock-out criteria . Nevertheless, it does not hurt to double check. The first task in Step 8, therefore, is to ensure that all the market segments that are still under consideration to be selected as target markets have well and truly passed the knock-out criteria test.
Once this is done, the attractiveness of the remaining segments and the relative organisational competitiveness for these segments needs to be evaluated. In other words, the segmentation team has to ask a number of questions which fall into two broad categories:
Which of the market segments would the organisation most like to target? Which segment would the organisation like to commit to?
Which of the organisations offering the same product would each of the segments most like to buy from? How likely is it that our organisation would be chosen? How likely is it that each segment would commit to us?
Answering these two questions forms the basis of the target segment decision.
2 Market Segment Evaluation
Most books that discuss target market selection (e.g., McDonald and Dunbar 1995; Lilien and Rangaswamy 2003), recommend the use of a decision matrix to visualise relative segment attractiveness and relative organisational competitiveness for each market segment. Many versions of decision matrices have been proposed in the past, and many names are used to describe them, including: Boston matrix (McDonald and Dunbar 1995; Dibb and Simkin 2008) because this type of matrix was first proposed by the Boston Consulting Group; General Electric / McKinsey matrix (McDonald and Dunbar 1995) because this extended version of the matrix was developed jointly by General Electric and McKinsey; directional policy matrix (McDonald and Dunbar 1995; Dibb and Simkin 2008) ; McDonald four-box directional policy matrix (McDonald and Dunbar 1995) ; and market attractiveness-business strength matrix (Dibb and Simkin 2008) . The aim of all these decision matrices along with their visualisations is to make it easier for the organisation to evaluate alternative market segments, and select one or a small number for targeting. It is up to the market segmentation team to decide which variation of the decision matrix offers the most useful framework to assist with decision making.
Whichever variation is chosen, the two criteria plotted along the axes cover two dimensions: segment attractiveness, and relative organisational competitiveness specific to each of the segments. Using the analogy of finding a partner for life: segment attractiveness is like the question Would you like to marry this person? given all the other people in the world you could marry. Relative organisational competitiveness is like the question Would this person marry you? given all the other people in the world they could marry.
In the following example, we use a generic segment evaluation plot that can easily be produced in R. To keep segment evaluation as intuitive as possible, we label the two axes How attractive is the segment to us? and How attractive are we to the segment? We plot segment attractiveness along the x-axis, and relative organisational competitiveness along the y-axis. Segments appear as circles. The size of the circles reflects another criterion of choice that is relevant to segment selection, such as contribution to turnover or loyalty.
Of course, there is no single best measure of segment attractiveness or relative organisational competitiveness. It is therefore necessary for users to return to their specifications of what an ideal target segment looks like for them. The ideal target segment was specified in Step 2 of the market segmentation analysis. Step 2 resulted in a number of criteria of segment attractiveness, and weights quantifying how much impact each of these criteria has on the total value of segment attractiveness.
In Step 8 , the target segment selection step of market segmentation analysis, this information is critical. However, the piece of information missing to be able to select a target segment, is the actual value each market segment has for each of the criteria specified to constitute segment attractiveness. These values emerge from the grouping, profiling, and description of each market segment. To determine the attractiveness value to be used in the segment evaluation plot for each segment, the segmentation team needs to assign a value for each attractiveness criterion to each segment.
The location of each market segment in the segment evaluation plot is then computed by multiplying the weight of the segment attractiveness criterion (agreed upon in Step 2) with the value of the segment attractiveness criterion for each market segment. The value of the segment attractiveness criterion for each market segment is determined by the market segmentation team based on the profiles and descriptions resulting from Steps 6 and 7. The result is a weighted value for each segment attractiveness criterion for each segment. Those values are added up, and represent a segment’s overall attractiveness (plotted along the x-axis). Table 10.1 contains an example of this calculation. In this case, the organisation has chosen five segment attractiveness criteria , and has assigned importance weights to them (shown in the second column). Then, based on the profiles and descriptions of each market segment, each segment is given a rating from 1 to 10 with 1 representing the worst and 10 representing the best value. Next, for each segment, the rating is multiplied with the weight, and all weighted attractiveness values are added. Looking at segment 1, for example, determining the segment attractiveness value leads to the following calculation (where 0.25 stands for 25%): 0.25 ⋅ 5 + 0.35 ⋅ 2 + 0.20 ⋅ 10 + 0.10 ⋅ 8 + 0.10 ⋅ 9 = 5.65. The value of 5.65 is therefore the x-axis location of segment 1 in the segment evaluation plot shown in Fig. 10.1.
The exact same procedure is followed for the relative organisational competitiveness. The question asked when selecting the criteria is: Which criteria do consumers use to select between alternative offers in the market? Possible criteria may include attractiveness of the product to the segment in view of the benefits segment members seek; suitability of the current price to segment willingness or ability to pay; availability of distribution channels to get the product to the segment; segment awareness of the existence of the organisation or brand image of the organisation held by segment members.
The value of each segment on the axis labelled How attractive are we to the segment? is calculated in the same way as the value for the attractiveness of each segment from the organisational perspective: first, criteria are agreed upon, next they are weighted, then each segment is rated, and finally the values are multiplied and summed up. The data underlying the segment evaluation plot based on the hypothetical example in Fig. 10.1 are given in Table 10.1.
The last aspect of the plot is the bubble size (contained in row “Size” in Table 10.1). Anything can be plotted onto the bubble size. Typically profit potential is plotted. Profit combines information about the size of the segment with spending and, as such, represents a critical value when target segments are selected. In other contexts, entirely different criteria may matter. For example, if a non for profit organisation uses market segmentation to recruit volunteers to help with land regeneration activities, they may choose to plot the number of hours volunteered as the bubble size.
Now the plot is complete and serves as a useful basis for discussions in the segmentation team. Using Fig. 10.1 as a basis, the segmentation team may, for example, eliminate from further consideration segments 3 and 7 because they are rather unattractive compared to the other available segments despite the fact that they have high profit potential (as indicated by the size of the bubbles). Segment 5 is obviously highly attractive and has high profit potential, but unfortunately the segment is not as fond of the organisation as the organisation is of the segment. It is unlikely, at this point in time, that the organisation will be able to cater successfully to segment 5. Segment 8 is excellent because it is highly attractive to the organisation, and views the organisation’s offer as highly attractive. A match made in heaven, except for the fact that the profit potential is not very high. It may be necessary, therefore to consider including segment 2. Segment 2 loves the organisation, has decent profit potential, and is about equally attractive to the organisation as segments 1, 4 and 6 (all of which, unfortunately, are not very fond of the organisation’s offer).
To re-create the plot in R, we store the upper half (without row “Total”) of Table 10.1 in the 5 × 8 matrix x, the corresponding weights from the second column in vector wx, the lower half of Table 10.1 in the 5 × 8 matrix y, and weights in vector wy. We then create the segment evaluation plot of the decision matrix using the following commands.
R> library("MSA") R> decisionMatrix(x, y, wx, wy, size = size)
where vector size controls the bubble size for each segment (e.g., profitability).
3 Step 8 Checklist
Dibb S, Simkin L (2008) Market segmentation success: making it happen! Routledge, New York
Lilien GL, Rangaswamy A (2003) Marketing engineering: computer-assisted marketing analysis and planning, 2nd edn. Prentice Hall, Upper Saddle River
McDonald M, Dunbar I (1995) Market segmentation: a step-by-step approach to creating profitable market segments. Macmillan, London
© 2018 The Authors
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Cite this chapter
Dolnicar, S., Grün, B., Leisch, F. (2018). Step 8: Selecting the Target Segment(s). In: Market Segmentation Analysis. Management for Professionals. Springer, Singapore. https://doi.org/10.1007/978-981-10-8818-6_10
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8817-9
Online ISBN: 978-981-10-8818-6