This is the output of the group assignment for the course 'Market Research' managed by prof. Alberto Saccardi, Bocconi University. The objetive was to create a questionnaire on a specific market and develop insights on the basis of both univariate and multivariate quantitative analisys. I collaborated with Francesco Maria Saviotti, Elena Gasan, Irene Nucida, Paula.Andreea Rotaru and Tommaso Tini. As it is evident, we didn't master the aesthetic quality of a PPT presentation. Nonetheless we tried to apply various quantitative techniques and in the end some interesting thoughts came out as the result of our analysis.

1. The new trends in the Italian mobile telephony market and the Smartphone revolution

2. AGENDA INTRODUCTION -BUSINESS DESCRIPTION -FOCUS on main phenomena affecting the market -TREND -QUESTIONS -SAMPLE AND DATA QUALITY CONTROL UNIVARIATE AND BIVARIATE, SAMPLE POPULATION MULTIVARIATE ANALYSIS FACTOR ANALYSIS CLUSTER ANALYSIS CONJOIT ANALYSIS DISCRIMINANT ANALYSIS BOCCONI MARKET CONCLUSION

4. what impresses is the continuous demand with respects of the other phone categories that since June 2009 registered a drop of 6%,

5. It’s the only segment that continue to grow despite the crisis and market saturation. A study from Pyramid Research reveals that in 5 years (2010-2014) the amount of smartphones sold will be equal to 1.8 billion in the whole word, reaching the 37% of the tot market (currently is the 16%).

7. total subscriber accounts in Italy will increase from 90.5 million in 2008 to 91.8 million in 2013 21- Results from the research conducted by “Autorità Garante della concorrenza e del Mercato” together with the “Autorità per le Garanzie delle comunicazioni” 2- Fonte: EMIT

9. Smartphone revolution: born to satisfy business men’s instances, now this expensive phone has become an object of desire of many customers’ segments, especially young people who pay great attention to the latest fashion and technology trends.

10. Customers, especially the one highly price-sensitive, are more demanding and so they tend to be more disloyal

11. This has generated in companies the need to design new strategies to keep their customers loyal

13. WHAT’S NEW? IEMR FORECAST(2008 – 2013) WHY THESE TRENDS ???

15. Are the “bundling strategies” winning?

16. What people like in smartphones?

17. Smarthphones are all perceived in the same way, or are there any differences?

18. Can we identify different customers for different smartphones’ type, so that phone operator companies can try to differentiate their offering from competitors according to the specific features of their customers?

20. BIVARIATE AN.

21. FACTOR AN.

22. CLUSTER AN. 1

23. DISCRIMINANT AN.

24. UNIVARIATE AN.

25. BIVARIATE AN.

26. CONJOINT AN.

27. CLUSTER AN. 2IDENTIFY current and future WINNING STRATEGIES

28. OUR SAMPLE The unit of analysis was composed by people living in Milan, aged between 16 and 30. The sampling procedure was based on a internet survey sent to our closest network of acquaintances. The sample size is 230 but our final dataset is composed by 153 interviewees (see Data Check in next slide). We decided to target young people because in our opinion they represent that part of the population that shows some characteristics that are in line with our analysis: price-sensitivity fashion and technology driven attitudes

29. DATA QUALITY CONTROL From 230 interviewees we arrived to a dataset of 153 cases because we deleted all the incomplete questionnaires. Missing values: the only type of missing value we detected referred to specific questions to which some people were not required to answer. We have filled those blank spaces with the 3-digit number 999 with the following procedure: in the value field of the variable view, we assigned the label “no answer required” to all 999 numbers. Afterwards, in the missing value field we wrote 999 in order to indentify the missing values. Before proceeding with Univariate, Bivariate and Multivariate analysis, data quality control procedures were performed, namely the consistency check, in order to prevent biases and mistakes (e.g., studying the averages of variables we could the detect the presence of some wrong responses, slide 27). Preliminary results of conjoint analysis, though showing some interesting outcomes, were affected by a bias in interviewee responses (that’s why the total number of responses in the conjoint analysis results in 149 instead of 153).

30. Univariate & Bivariate analysis Sample population

31. Proceeding Method For a better internal consistency, we decided to put together the Univariate Analysis with the Bivariate. We inserted more charts and graphs than tables because we believe that in such a way our results could be more understandable. In any case, all our analysis have been performed together with a step by step check of the significance and relevance of all different indexes ( V Cramer, Pearson, Eta Square, etc). Below we report the 4 main areas we decided to study:

32. Gender Our sample is composed by a total of 153 interviewees, specifically by 41.2% males and 58.8% females.

34. The distribution is slightly skewed to the right.

35. The Range between 21 and 25 embraces almost 76% of our sample.As we didn’t use a stratified sample, the 3 categories are very heterogeneous. Therefore, our conclusions will certainly be more sound for the middle segment (the largest) and less for the other 2 segments.

36. Occupation The bar chart shows that 81% of our sample is composed by students and working-students. The rest is composed by all other categories of workers (15.03%) and by unemployed-seeking for a job (3.92%).

37. Bocconi 39.87% of our whole sample – 153 interviewees – is the Bocconi market

38. Type of contract From this table we can deduce that our sample is more attracted by pre-paid card solutions; the second choice option may be a fixed tariff contract. As shown below, our student segment is affecting positively and greatly the pre-paid card subscriber’s share. In fact the percentage average of students who has a pre-paid card is the only one that is above the overall average.

39. Age range vs. type contract It’s clear that young people do not want any contractual obligation with the operator and prefer to have a pre-paid card. The 3rd age-range of customers instead tend to switch to a contract with a variable tariff and even more heavily towards a fixed price contract. % within AGE Range OUR GOAL We will afterwards check how many of these interviewees with a pre-paid card would accept to switch to a long-run contract if a very appealing smartphone is given to them at half of the price (see slide 43).

40. Monthly Expenses The mean expense of our sample population is €34 and the median is €30. Therefore the distribution is skewed to the right. We define as outliers those cases that position themselves three std. deviations to the right of the mean. Such cases are 4.

42. The four outliers we detected (that spend above 132 euro per month) may represent some profitable nichesVodafonewent even further our conclusions: it has decided to maximally stratify its offering according to each specific willingness to pay (from XS size to L). In this way it can target either the very big segments, but also the niches. Even though this is certainly a winning strategy, Tre was able to offer an even better tariff: a 30 euro “all inclusive” contract (See Slide 41) The phone offering is a omnipresent bundling tool.

43. Occupation vs. Monthly expanses % within occupation

44. Occupation vs. Monthly expanses From the above chart we can define two situations: Students vs. working-students: on one hand, non-working students tend to spend between 30 and 50 euro per month, which is quite a lot. On the other hand, the great part of working student tend to spend below 30 euro. We can say that students, being sustained by parents, tend to spend more; whereas working-students are more money conscious. N.B.the fact that our student segment spends quite a lot may be due to the strong presence of Bocconi Students which, as it is widely known, are, in great part, well-off. 2. Workers: the more their profession is managerial, the more they tend to spend on phone services. This is due to the increasing need to use the phone as an instrument of communication and business. For example, managers & independents, who travels a lot, may strongly need the mobile phone to stay in contact with their families or to manage their activities from abroad. N.B. Our analysis is limited due to the fact that our sample is not large enough to accurately establish the actual situation in the worker segment.

45. Service Importance Calls are the most important service, closely followed by sms. On the other hand internet and mms are of little importance. The mode of the internet service is 1, this is because there are still a lot of people who can’t have access to internet through the mobile phone (see slide 26). The low interest shown for the MMS can be explained by the fact that this is still a very expensive service that can be easily substituted by other technologies like the Bluetooth, Social Network and Chat. In the next slide there is the representation of the histogram and the skewness.

47. Phone internet access vs. importance_Internet 49% 71.3% Internet is perceived unimportant more by those who do not have an internet access on their phone (71.3%) compared to those who have mobile internet (49%). Hence, the perception of the Internet Importance is negatively biased by the high number (38.6%) of people who cannot access internet from their cellphones.

48. Service Usage IMPORTANCE VS USAGE: If we compare this frequency table about the usage of the 3 services with the importance our respondents gave to (calls, SMS, internet) we found a perfect correspondence between these 2 answers. Calls are the most important service as well as the most used service. Following, we found SMS, internet and mms. DATA CHECK: During this analysis we noticed that the mean for “calls” overcame the 100% threshold. By checking the dataset we found out that 2 respondents had made an error while typing the number (200% instead of 20%). So, through the “select case” command, we deleted those answer that did not respect the following condition: X < 100%

50. Phone operator Our sample is composed mainly by people who has got Vodafone as phone operator, followed by Wind, Tim and Tre. However, our sample does not represent the overall Italian trend. Below there is the Italian official subscription data.

51. Type of Contract vs. Operator Vodafone, Tim and Wind are strongly present in the young segment with the pre-paid cards. This may be due to the fact that Vodafone, for example, makes a very strong advertising of pre-paid cards appealing especially young people. Tre instead goes into a complete different direction if compared with competitors: it offers very competitive contracts. Specifically, it has some of the most convenient contracts that comprehends also the possibility to have one of the latest-generation smartphone at 1/3 of the price. % within phone operator

52. Overall Operator Satisfaction From an overall perspective, people are quite satisfied with their phone operator. Only less of 25% of them are unsatisfied (See Percentiles).

54. Tre is the only operator that manages to keep more than half of its customers (53.8%) very satisfied. It is also the one that has fewer unsatisfied subscribers (15.4%).

56. The plan customization importance proves to have a strong grade of independency in regards to many other features

57. not surprisingly, the entertainment results quite in apart from ease of use and information completenessWe can resume this complex ‘picture’ saying that there is a general strong correlation between the 3 various aspect of each of the 4 characters. In general this within correlation is around 0.6-0.8 (Pearson coeff.) between the importance side and around 0.2-0.3 between the satisfaction side.

58. Operator reputation

59. Relationship customer-phone operator

60. Operator website

61. Customer service

62. Operator Satisfaction Vs. Think to Change Operator % within Plan Satisfaction Range The pie chart shows that 23.53% of respondents want to change operator. 36 interviewees The bar chart shows that just half of those that are not satisfied actually consider changing their operator.

63. Operator Satisfaction vs. Monthly Expense The marketing concept that the more you are satisfied, the more you spend doesn’t apply to the mobile phone market. People spend the necessary amount to satisfy their needs.

64. What Phone Operator are subscribed to those who consider switching operators? Even though half of the people who consider changing operators are currently Vodafone subscribers, a more interesting reality is the one concerning Tim. Among our sample Tim is slightly behind Wind with respect to the number of subscribers, nevertheless almost twice as many unsatisfied customers form Tim consider switching operators compared to those of Wind. 36 interviewees To small a sample to draw any definite conclusions about the market. % within those who think to change phone operator N.B. By proposing innovative offers Wind and Tre should try to attract those who think of leaving Vodafone and Tim.

65. Toward which phone operator would you move? Our results show that Vodafone, Tim and Wind are on the same level of preferences. But since for this question only 36 interviewees were considered we can not say that our findings are conclusive for the overall market.

66. Belowwe Preferred Phone As we can see from the pie chart, iPhone is the most appreciated smartphone, followed by Nokia. Which are the drivers that lead iPhone to a such positive situation will be shown in details during the following Multivariate Analysis, in particular the Discriminant Analysis Worldwide smartphone Company sales, 12th November 2009 Source: Gartner BlackBerry and iPhone companies are gaining on a lot in a short term thanks to their successful product concept. Nokia proves to still exploit the positive overall market trend whereas it also suffers from the market share point of view. This is comprehensible because it is probably difficult to maintain such a dominant position being currently under attack indeed due to the arrival of the smartphones revolution

69. 500 minutes

70. 350 SMS

71. 4 GB of Internet% within type of contract The bundling Phone-contract strategy is successful!!!

72. Tre’s winning strategy Forecasts says that Tre is acquiring more & more market share. This may be explained by the fact that it has foreseen the trend and has invested strongly on it. Thanks to these contract it was able to establish long-lasting relationship with its customers It stays within the 30 euro => perfectly in line with our results

74. the share of Fixed Monthly Tariff Contract increases from 6.3%, among those who spend less than €30, to 33.3% , among those who fall under the highest expense category. Hence, our target sample shows that there is a strong tendency to move from a pre-paid card to a contract as the monthly expense increases. % within monthly expanse range

75. Monthly expanse vs. operator

77. Wind, on the other hand, is preferred more by those who spend a smaller amount of money per month.

79. A N A L Y S I S

80. Factor Analysis: Steps

82. We asked interviewees to give a score from 1 to 10 (1: “Not important” 10: “Very important”)

84. Kaiser-Meyer-Olkin(KMO) measure of sampling adequacy, which if it is between 0.5 and 1.0 indicates that the factor analysis is appropriate. Values below 0.5 imply that FA may not be appropriate1 2 2 1

85. 3. Determine the method of Factor analysis Principal Component Analysis The total variance in the data is considered recommended when the primary concern is to determine the minimum number of factors that will account for maximum variance in the data for use in subsequent multivariate analysis APPLICABLE to our study, since we will use the result of the factor analysis in the cluster analysis (market segmentation)

86. 4. Determine the number of factors Number of factors: 4 Extraction: Principal Component Analysis Max number of iteration: 100 Hypothesis: The percentage of the explained variance : 74% - the optimal range is in between 60% - 70% OK

87. Ratio between the factors’ number and variables’ number : for a set of 6 variables, the ideal number of factors is 2 (book example). In this case for a set of 13 variables, we have considered 4 factors=>ADEQUATE Communalities:the values vary among 0.571 and 0.842=> ADEQUATE

88. At the 3rd factor we can see the strongest point of discontinuity. However, according to the fact that the 3rd and the 4th factors have a very similar importance in overall variance explained, besides the coherence between the variables inside the 4th factor is very high (slide51)… …we have decided to keep 4 factors.

91. Factor Analysis: Interpretation

92. CLUSTER ANALYSIS

95. Cluster Analysis - K-means Method NUMBER OF CASES IN EACH CLUSTER The number of cases in each cluster is satisfactory. Therefore clusters are more or less homogeneous There do not appear to be any outliers

96. Cluster Analysis - K-means Method ANOVA The F-test is sound all p-values are < 5%

97. Cluster Analysis - K-means Method FINAL CLUSTER CENTERS Next we look on how much weight each factor has on each cluster

98. Cluster Analysis - K-means Method FINAL CLUSTER CENTERS Now we can define each cluster based on cases’ preferences and attitudes toward each factor.

99. Cluster Analysis - K-means Method 5 CLUSTERS: Showing off customers Technology updaters Technologically Indifferent customers Practical customers Aesthetical customers

100. Crosstabulation – clusters vs. sex

101. Crosstabulation – clusters vs. sex

102. Crosstabulation – clusters vs. preferred cellphone

103. Crosstabulation – clusters vs. preferred cellphone

104. Based on the results provided by the Final Cluster Centers table and those of the crosstabulations between Cluster & Sex and Cluster & Preferred cellphone, we determined the characteristics of each cluster. Cluster Analysis

106. They like the entertainment part of their cellphones. These people like playing games, listening to the music and taking pictures.

107. They are indifferent about any other features a cellphone can provide, like functionality and image (design)

108. They prefer iPhone 3GS 16GB and Nokia N97 Mini over BlackBerry Curve 8900.

110. Brand, design, trendiness (image) of a cellphone are also very important to them.

111. All other features of a cellphone are unimportant to them, they don’t care neither about the social position a cellphone can offer, nor its functionality.

113. These people do not give any preferenceto either brand or version of cell phones.

115. They do not like anything related to the social status offered by cellphones

116. They do not like the Media & Entertainment part of a cellphone

117. The Image of a brand is unimportant to them

119. Their social positioning due to cellphones they possess is insignificant to them

120. They do not like other features of a cellphone, like functionality or entertainment

121. iPhone 3GS 16GB is far ahead of any other preferences

123. CONJOINT ANALYSIS We conducted a conjoint analysis to check our customers preference choices in terms of tariffs and afterwards to check whether a new trend is coming up among the different offerings. We believe that the detection of the best tariff could be carried out through the construction of different “packages”. The packages presented to our respondents are composed by a combination of what we consider the most important features that a tariff should have :calls, sms and internet offerings.

124. Through the orthogonal design technique, we were able to present our respondents 9 scenarios characterized by 3 attributes. Each attributes had 3 levels. The 3 levels have been constructed considering the most common offerings our national mobile phone operators are currently providing to their customers. LEVEL attribute N.B: From the beginning we were conscious that constructing offerings based on real precise prices would certainly have been more interesting for us and better evaluable for our respondents, but we also knew that it would have brought us to a very complicated analysis out of our knowledge. Therefore, we decided to provide just qualitative information about contract types, even though we recognize that in this way we may have left some space for free interpretation on the meaning of each level.

125. Proceeding methods

127. Specifically, the general preference trend is the monthly charge, either for calls or sms.

128. Interviewees do not even want to be bound to ‘number of accesses’ or ‘data downloaded’ calculations: they prefer to pay for internet according to the time they spend on it.=> First conclusion: young customers want to communicate freely with their network of acquaintances and therefore mobile telephone companies must offer tariffs that guarantee this “freedom”.

131. ex: a manager has more economical resources than a student and use calls more then a laborer due to different duties.

133. they have more economical means

136. ID_46: very strong importance to internet service.

137. ID_60: very little importance to sms service.

138. ID_70: very strong evaluation of the level “convenience vs. same operator” both for calls and sms.These respondents, even though are only a few cases in our sample, they may represent a good part of the population in the whole market and therefore they may be interesting for mobile telephony companies from a profit perspective. N.B: we should highlight an inconsistency. At first sight we said that subject 60 gave very little importance to sms in the choice of the packages in the conjoint. But, analyzing how she replied to question 5 (“evaluate the importance of Calls/Sms/Internet”), we noticed that she rated 9 both for calls and sms, and only 1 to internet.

139. ID_26 ID_46 ID_71 ID_60

140. Conjoint analysis: SIMULATION We decided to simulate the preferences also according to 3 new scenarios that were not included (by the technique of the orthogonal design) in the 9 scenarios of the conjoint analysis and that in our opinion can draw some interesting results and allow us to make a second cluster analysis regarding again tariff.

141. Conjoint analysis: SIMULATION The results are in line with what we obtained previously: the monthly based tariff (profile 10) is the most preferred one, with a value equal to 6.6.

142. Cluster analysis 2: the Dendogram By conducting a hierarchical cluster analysis we identified 3 major clusters.

143. Why not 3 clusters? –k-means method Even though the number of cases seems satisfactory (clusters are more or less homogeneous), the F-test is not sound because not all p-values are < 5%

144. 4 clusters By choosing 4 clusters we noticed that the number of cases was satisfactory but also the F-test was sound: all p-values are less than 5%

145. Final cluster centers This is the result of the final cluster centres considering 4 clusters

146. In the hierarchical and k-means analysis we inserted only 6 variable out of 9 because, as the sum of all the levels must be zero, it would be redundant to put all 9 levels. Therefore we put only 2 out of 3 levels for each attributes. In this table instead we decided to put all 9 variables in order to make the description of the clusters clearer.

147. 4 Clusters

149. you pay a fixed amount per month to have a fixed amount of minutes to call whomever you want (so freedom),

150. The 3 tariffs prices stay within the 30 euro cost (convenience seeker: maybe that’s why no phone bundling strategy are used).

152. In order to understand the influence of various quantitative variables on crucial qualitative variables we decided to begin 9many discriminant analysis (D.A.). crossed with our target’s characters such as type of usage of internet, preferred services. SMARTPHONE chosen VS target’s demographic and psychographic data phone features PHONE OPERATOR (current) Importance and convenience of different services (call, sms, mms, web) VS PHONE OPERATOR (desired) Importance and satisfaction on various operator aspects Unfortunately we have only 36 interviewees who answered the question related to the desired operator and this not enabled us to do a meaningful D.A. In fact the significance of the independent variables was not under the necessary threshold of p<0,5

153. We are going to present the only 2 D.A. which overtake the first two steps: -verification of the hypothesis of equality of the means of each variable in the groups -significance of variables CURRENT OPERATOR VS SERVICE CONVENIENCE/IMPORTANCE The variables which are significant, then potentially the most discriminant, are the following: -importance calls -importance sms -convenience internet -convenience sms BUT We have to pick up 2 discriminant functions, but with this value we can not go on with the analysis WARNING

154. SMARTPHONE VERSUS PHONE FEATURES

158. Easy of use and Adv.TechServices are written lighter because they did not pass the significance test, then they are less important NOKIA N97mini Brand HighDef.Camera Easy of use Keyboard Ease Y-AXIS :BRAND & CAMERA Entertaining Scr.&Visibility Adv.TechServices Design Trendy BlackBerry Curve8900 iPhone 3GS 16GB X-AXIS: VISIBILITY & IMAGE

159. BUSINESS IMPLICATIONS

160. Now we are going to create additional axis in order to understand the weaknesses of each product thanks to relative distance comparisons NOKIA N97mini Marketing suggestions Brand HighDef.Camera Screen & Visibility Y-AXIS :BRAND & CAMERA Easy of use Keyboard Ease Entertaining Scr.&Visibility Adv.TechServices Design Trendy BlackBerry Curve8900 iPhone 3GS 16GB X-AXIS: VISIBILITY & IMAGE

161. BLACKBERRY Yes: BB is principally oriented to older business men and our interviewees are mainly students (65%) No: our students interviewees are in a great extent Bocconians (50%) and their reference group is in many cases already ‘manager-carrier seeker’ Are there any justifications? 1 BLACKBERRY is completely negatively evaluated on both axis and it is has not a relevant advantage on any value-driven variables. No strong competitive advantage 2 BlackBerry’s ‘niche’ is easily conquerable it should perhaps rethink its positioning and value drivers (NB. Blackberry is increasing in both volumes and market share) The most evident modification applied on the last model (BlackBerry Storm) is indeed on the Screen&Visibility variable (biggest weakness according to relative map’s distance) A strong change that allow BlackBerry to catch up the i-Phone on this important value-driver 3

162. Keyboard Ease NOKIA N97mini Brand HighDef.Camera Y-AXIS :BRAND & CAMERA Easy of use Keyboard Ease Entertaining Scr.&Visibility Adv.TechServices Design Trendy BlackBerry Curve8900 iPhone 3GS 16GB X-AXIS: VISIBILITY & IMAGE

163. Brand NOKIA N97mini Brand HighDef.Camera Y-AXIS :BRAND & CAMERA Easy of use Keyboard Ease Entertaining Scr.&Visibility Adv.TechServices Design Trendy BlackBerry Curve8900 iPhone 3GS 16GB X-AXIS: VISIBILITY & IMAGE

164. iPHONE iPHONE is very well-positioned on variables such as Trendy, Design and Visibility Well aligned with the Visibility&Image axis The short presence in the market may explain the low perception of this variable Considering its strong brand awareness and brand recognition, it is curious that it is substantially far from the Brand value-driver. Probably the brand identity in the cell-phone market is not so solid and well-structured as Nokia TheKeyboard Ease variable is very interesting On one side, it tells us that iPhone is not aligned with this driver at all For iPhone is advisable a strong change On the other side, from previous coefficient’s chart we can also see that it is negatively correlated with the 2nd function, Visibility&Image (-,114) Therefore, iPhone should improve its virtual keyboard software instead of thinking on the option of a ‘physical’ keyboard But, iPhone cannot “smear” its competitive advantage features represented by the 2nd function

165. Camera NOKIA N97mini Brand HighDef.Camera Y-AXIS :BRAND & CAMERA Easy of use Keyboard Ease Entertaining Scr.&Visibility Adv.TechServices Design Trendy BlackBerry Curve8900 iPhone 3GS 16GB X-AXIS: VISIBILITY & IMAGE

166. NOKIA Since that ‘Brand’ is a variable based on an intangible asset which probably needs to be continuously ‘fed’ by other values…. Strong Brand identity Since that the Nokia 5 Mpx high-definition camera is perceived as stunning if compared with the competitor’s cameras (BB= 3.15 iP=3.2)……. Since that Keyboard Ease has not a very strong importance in discriminating the purchasing choice between smartphones….. “Camera” is the most important variable which enable the Nokia brand to differentiate itself and to stand out from competitors Nokia must be AWARE of it because it could be risky

167. Bocconi Market Bocconi students have approximately the same attitude toward our offer – 41% answered “YES” 40.52% of our interviewees would agree to make a long lasting contract with an operator if they can receive their preferred phone at half its market price

169. Functionality