Ford Ka’s Marketing Strategy_ Critical Analysis

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Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Case Assignment 1 Ford Ka Marketing Strategy & Cluster Analysis MSBA 46894 M3 - Team G Ayan Saraf: ayananas Bo Suk Yoon: bosuky Lazuli Abel: laabel Peter Laughlin: pmlaughl 1

Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Historical Strategies 1 Ford (and car manufacturers in general) have traditionally segmented the car market to meet specific needs of customer groups through age, income, and household segregation. Different cars manufactured cater to different segments of the market based on these needs. Despite leveraging economies of scale to reduce production costs, there are also still considerations beyond just customer needs that manufacturers need to consider. The bigger the car, for example, the more expensive it is, since more resources are required in manufacturing and sales. The marketing strategy for smaller (and less expensive) cars, therefore, was to target young, low income people that focussed on affordability. An increase in the availability and quantity of data has allowed companies to take a more nuanced approach to segmenting customers. While the older segmentation strategy is somewhat applicable, this segmentation strategy has now evolved by introducing additional factors like fuel consumption, the increase in female earners, parking availability, overall design and functionality. As a result, the small car market has become increasingly challenging for the manufacturers to meet all those consumer needs in their cars. Ford produced the Ka as a means to provide requirements prioritized by consumers. Psychographic Insights 2 A psychographic survey conducted by Ford helped to reveal the distinctions between different customer segments. 250 respondents answered a series of questions posed by researchers at the company using a scale from one, “strongly disagree,” to seven, “strongly agree.” In addition to these psychographic questions, survey respondents were asked to rank the Ford Ka among nine other competitive offerings. The survey data, a combination of general preferences and explicit choices among cars that are similar to the Ka, allows us to begin to answer the question as to why customers might purchase the Ka. The first survey question, “I want a car that is trendy,” was answered by most customers in the neutral to affirmative range. However, Ka Choosers (those customers who placed the Ka in their top three favorite models among the Ka and nine other competitive offerings) seem to be slightly more trend-conscious than Ka Non-Choosers (customers who placed the Ka in their bottom three favorite models). 47% of Ka Choosers (55 respondents out of 116 Ka Choosers) answered this first question with either a 6 or 7 (1 = strongly disagree; 7 = strongly agree), whereas only 31% of Ka Non-Choosers (67 respondents out of 72 2 Question 2 1 Question 1 2

Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Ka Non-Choosers) answered this question with a 6 or 7. Similarly, just 3% (4 respondents) of Ka Choosers answered with a 1 or a 2; however, 7% (5 respondents out of 72) Ka Non-Choosers answered this question with a 1 or 2. (Appendix A, B & C) In order to achieve many of the economic benefits of mass-marketing while realizing the benefits of precise, one-to-one marketing, Ford needs to strike a balance between the general segmentation of Ka Choosers versus Non-Choosers without going into as granular a level of detail as reviewing each respondent’s answer to every question. We can use clustering techniques to further develop our understanding of not only commonalities that exist within segments of the population of car-buyers, but also how the Ford Ka might appeal (or not appeal) to those different segments. We explore two broad approaches to clustering customer data: demographic, and psychographic. Segmentation Using k-Means Clustering - Demographic Data 3 A five-group clustering solution was chosen based on an optimal balance between within-group similarity and between-group difference. This number of clusters revealed intuitive descriptions based on characteristics of customers falling within each cluster. Below is an interpretation: (Appendix D & E) 1. Cluster 1 - Working females with a family : medium age, female, married with children, medium income, including some first time purchasers. 2. Cluster 2 - Young females without children : youngest people, mostly female with no children, low to medium income. Most are first time purchases. 3. Cluster 3 - Single male elderly group : single older males without children. This is the highest income group, who are typically not first time purchasers. 4. Cluster 4 - Male group with high income : young males with children. This group has a relatively high income, and are also typically not first time purchasers. 5. Cluster 5 - Young married couples with low income : the youngest cluster, consisting of both males and females with no children. This group is lower income yet not first time purchasers. Our choice of five clusters is supported by a within sum of squares (WSS) scree chart which demonstrates that the most data is explained with five clusters, without gaining much value in including additional clusters beyond that. (Appendix F) 3 Question 3 3

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Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Segmentation Using k-Means Clustering - Psychographic Data 4 Similar to the approach using demographic data, an optimal five-group clustering solution was chosen for many of the same reasons previously described. Below is an interpretation: (Appendix G, H, I) 1. Cluster 1 - No-nonsense Neutrals : Everyday driver that desires masculine, trendy cars and does not care about quality. 2. Cluster 2 - Sensible Classics : Practical focus: wants an efficient, reliable car and gives no weight to appearance. 3. Cluster 3 - Freedom Lovers : Simple desire: functional and masculine. 4. Cluster 4 - Attention Seekers : Very appearance-driven; want a trendy, bold, masculine car. 5. Cluster 5 - Easy Goers : Any car that works. A WSS Scree plot illustrating the differences among customers within each cluster for various numbers of clusters is included in our appendix. (Appendix J) Segmentation Recommendation 5 We would recommend using the demographic segmentation over the psychographic segmentation since the strategy has lower risk and ability to capture a larger customer base without being too specific. While the psychographic segmentation has greater reward with being able to get customers with a higher chance of converting to purchase, it is equally important to outweigh the resources that will be used to conduct such an in-depth survey. Assuming that the company wants to continue investing in research and development of other cars, their marketing budget is better spent on product design. If Ford were to choose a niche cluster within psychographic, they would likely be too focused, and lose a larger sum of the audience despite higher conversion in one segment. Based on our results, Cluster 2 and Cluster 5 within our demographic segmentation are the focus group to whom the product should be marketed. Their attributes, females and married couples with no children who are not first time purchasers, are most likely to be Ka buyers. The analysis reveals that the business has evolved their marketing strategy to meet the changing needs of its target market, conducting a study on demographic and psychographic insights. Since there are a variety of preferences from the customers, however, there remains a need to constantly evolve and monitor Ford’s approach. 5 Quesion 5 4 Question 4 4

Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Appendix Appendix A Appendix B Appendix C Appendix D Demographic Variable Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Age 0.220 -0.575 0.910 -0.106 -0.680 ChildrenCategory 1.230 -0.408 -0.637 1.478 -0.600 FirstTimePurchase 0.233 -2.395 0.416 0.135 0.416 Gender 1.039 0.394 -0.459 -0.959 0.000 IncomeCategory 0.176 -0.228 0.438 0.395 -0.569 MaritalStatus -0.235 -0.036 0.294 0.137 -0.163 NumberChildren 1.143 -0.422 -0.603 1.484 -0.574 5

Ayan Saraf, Bo Suk Yoon, Lazuli Abel, Peter Laughlin MSBA 46894 M3 - Team G Appendix E Appendix F Appendix G Appendix H Centroids 1 2 3 4 5 Q12 -0.06 0.55 0.06 -0.17 -0.44 Q4 -0.13 -0.18 1.09 -1.68 0.00 Q1 0.92 -0.63 -0.71 0.91 -0.85 Q53 -1.14 0.29 0.20 1.56 0.40 Q57 -0.23 -0.07 -0.34 1.60 -0.23 Q30 0.44 -1.16 0.43 0.61 -1.00 Appendix I Appendix J 6 Clusters 4 and 5 contain members that, on average, are more likely than not to fall into preference group 1 % of Total Average Group 1: Desires masculine, trendy cars and does not care about quality. 31% 1.96 2: Desires an efficient, reliable car. No weight on appearance. 16% 1.88 3: Only focused on a functional, masculine car. 26% 1.62 4: Very appearance-driven; wants a trendy, loud, masculine car that they can keep clean. 13% 1.75 5: Would be fine with any car that works. 14% 1.63

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