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    conjoint analysis for smart phones conjoint analysis for smart phones Document Transcript

    • The Smartphones inIndia – A ConjointAnalysis and Simulation CFPP Project Report Date of submission: 17-Feb-2012Group 16 FT12425)Dhruv Anand (FT12425)Sudhanva FT12264)Sudhanva D V (FT12264) FT12477)Anamika Roy (FT12477) FT12417)Bikram Satapathy (FT12417) FT12467)Srinivas Dhenuvukonda (FT124671|Page
    • ContentsIntroduction .......................................................................................................................................................3Objectives ...........................................................................................................................................................4Methodology ......................................................................................................................................................5 Pre-study and selection of attributes.............................................................................................................5RESULTS AND ANALYSIS .....................................................................................................................................7 Participation Level ..........................................................................................................................................7Conjoint Analysis ................................................................................................................................................8 Introduction ...................................................................................................................................................8 Part worth utility curves ............................................................................................................................... 10Demographic Analysis ......................................................................................................................................11 Benefit segment Analysis .............................................................................................................................13Market simulation ............................................................................................................................................16 Sensitivity Analysis .......................................................................................................................................17 Issues and recommendations to full-scale study .........................................................................................19 Conclusions ..................................................................................................................................................19Exhibit-1 ...........................................................................................................................................................202|Page
    • IntroductionA smart phone is can be found in every second hand nowadays – from a white collaredprofessional to a student! This pervasive entry of smart phones into our lives is due to twoprimary reasons. One reason being the rapid advancement in technology and R&D whichmakes the present technology redundant within weeks. The second is the drastic drop inprices which occur every few days.So the question now is why is the Smart Phone such an in demand product when comparedwith our traditional Feature phone; for a multitude of reasons. A smart phone is a mobilephone built on a mobile computing platform, with more advanced computing ability andconnectivity than a feature phone. The presence of Application Programming Interface (APIs)on the smart phones is used for running the third party applications which bring in life to themobile phone.The first smartphones were devices that mainly combined the functions of a personal digitalassistant (PDA) and a mobile phone or camera phone. Smart phones now have well-developedtouchscreens, web browsers that can access any page on the web and not just sites designedspecifically for mobile phones, and high-speed data access via Wi-Fi and mobile broadband.We were immensely interested in understanding the consumer’s preferences in this everchanging dynamic market. The cell phone from being a product of utility at the beginningturned into an accessory and a hand held device with multiple features. We are in a verycrucial phase for a country like India where the purchasing power of the consumer isincreasing and they don’t think too much about spending a little more.We designed our project with the intention to understand how the different attributes andfeatures provided by the manufacturers hold how much value to the consumer. When there isa tradeoff between different attributes the consumer makes a choice based on the attributeshe considers the most favorable to his taste. This process is as much a scientific process as ispsychological.The study is conducted among urban individuals who are part of the workforce and amongstudents who are old enough to own mobile phones. The Smart phone manufacturers canenhance their products and better position their phones to the consumers. After all, thecustomer is the king!3|Page
    • ObjectivesThe objective of this study is to understand the consumers preference in the purchase ofSmart Phones and the attributes he/she thinks are of importance during the time of purchase.We are trying to understand how the five attributes – price, design, brand, shape and userfriendliness, interact with each other to shape the purchase decision of the consumer.We hope this conjoint project will help prioritize the most desired attributes of the SmartPhone so as to maximize revenue by understanding the consumer utility. By using thisconjoint analysis, we can conclude what are the most significant attributes and what is eachattributes’ relative value. This study gives us insights into what are the consumer’spreferences in a Smart phone and how changes in each attribute effect the likelihood ofpurchase.4|Page
    • MethodologyPre-study and selection of attributesIn order to select the attributes of the service, we conducted qualitative research. Two Focusgroup discussion and 6 interviews were conducted to understand the participants’preferences. This formed as a good base to arrive at attributes and further frame the levels ofthe attributes. As the product is smart phones so the Participants were enthusiastic inexpressing about the latest trends and style of the smart phone.Attributes and Levels Price • Rs 40000 • Rs 30000 • Rs 20000 User-friendliness • Low • Medium • High Brand • Nokia • Apple • HTC • Samsung Design • Trendy • Sleek • Changeable Skin Shape • Touch screen • Qwerty • Slider5|Page
    • Survey Development and DesignIn order to make the survey effective, a two part conjoint survey was designed. The survey askedthe survey takers to first rate the importance of various attributes. The survey takers were thengiven various options to choose between mock purchase scenarios, in this case job offerings. Thiswas developed using ASEMAP which is a computer adaptive survey generator. This survey waslinked to the demographic survey which was developed using Survey gizmo. The purpose of linkingboth was to have consistency in data and also not to break the flow of the survey for the surveytakers. The survey was then tested by the team and a few participants to gauge the user-friendliness and usability. Based on the feedback, changes were made in the survey design.Survey Administration.Our target response size was 75 in order (15 per member) to complete our survey. Thechallenge was to get the respondents fill all the four sections of the survey. We tracked thevalidity of the responses based on the Rank order correlation, Adjusted R-Square, LogitAdjusted R conversation and made sure that 50 valid responses are available for analysis.6|Page
    • RESULTS AND ANALYSISParticipation LevelValidity of DataWe got 65 responses for the survey. On analysis of the data, it was found that few of theresponses were not valid. Following criteria was used to determine the validity of the data • Rank order should be greater than 0.5 • Adjusted R square should be greater than 0.25 • Logit Adjusted R square should be greater than 0.25Only those responses were considered which satisfied all the three conditions mentionedabove. It was found that 23 responses did not satisfy at least one of the conditions mentionedabove and hence they were removed. The demographic data for these respondents was alsoremoved. Analysis was done for the remaining 54 valid responses.7|Page
    • Conjoint AnalysisIntroductionBased on the ASEMAP output, we calculated the mean utilities and importance levels for thevarious attributes and individual levels. All 5 attributes were then ranked according to theirimportance levels. Table 1 shows the importance rankings of different attributes as well asthe mean part worth utilities of a given attribute level.A review of Table 1 shows that price is the most important attribute, across all participantswith its importance level being 37.3%. Brand, User-friendliness, shape & design formed thenext set of important attributes with the important percentages being 25%, 21.7%, 8.7% and7.3% respectively.It is also prevailed and common observation that brand and price are the two most importantattributes for buyers in the consumer market before purchasing any smart phone.Table 1 Mean MeanSl No Rank Attributes Levels utilities importance Apple 10.83 1 2 Brand Nokia -1.00 25.0% Samsung 1.14 HTC -10.97 20000 17.12 2 1 Price 30000 -1.67 37.3% 40000 -15.45 Sleek 2.93 3 5 Design Trend 0.49 7.3% Changeable skins -3.42 Slider -3.52 4 4 Shape Qwerty -0.58 8.7% Touch screen 4.10 Low -9.56 User 5 3 Medium 0.15 21.7% friendliness High 9.408|Page
    • From the conjoint analysis one can says that consumers are more interested in price of thesmartphone and followed by brand. This could be the reason that Samsung captured marketfrom Nokia in smartphone segment due to Samsung decreased prices for the same phonesegment.The next best attribute is brand with nearly 25% importance for consumers in the market. Itwill also tell that consumers will prefer brands to other attributes while purchasing a mobile.User-friendliness is the third most important for consumers of softphone segment. As themost of the consumers go for smartphones only for the sake of sophistication, versatility andfully functional. Only user-friendly mobiles will have all those qualities.The utility curves of conjoint analysis are given in the figures9|Page
    • Part worth utility curvesThe mean part worth utility curves are drwan for the 5 attributes and as given above10 | P a g e
    • Demographic AnalysisWe collected demographic data in 12 categories: • Age • Gender • Family income • Profession • Usage Level per day (hours) • Location • Brand • Persons influencing brand selection • Price • Style • Features • User friendlinessGender based preferences for Brands:Of all female respondents 78% preferred Apple brand of smart phones. For males thepreferences vary with Apple being preferred by 46% of respondents, 33% preferringSamsung. Preferred Brand Apple Samsung Female 78% 22% Male 46% 33%11 | P a g e
    • Gender based Usage level patterns:The level of usage per day for females suggests that 67% use it for more than 4 hours a day.The percentage of males that use it for less than 4 hours is 67 %. Of these 50% preferredApple brands of smart phones. Usage Pattern per day 3-4 4-6 hours hours Female 30% 67% Male 67% 21%Inference from Importance Ratings:The importance rating show the contrast in the preference when it comes to Price as a factor,almost equal percentage of respondents have preferred Price as most and Least importantcriteria.This shows that Price is a critical factor and has extreme reactions from respondents.Similarly, more than 50% of respondents have chosen Style as 2nd or 3rd in ratings indicatingthat relative unimportance compared to Price.Features comes across as a criteria in which there is almost equal distribution whereby therespondents are divided and hence there may be a clarity required in terms of explaining orunderstanding the meaning attached to what all is covered in features when respondents rateit.User-friendliness as criteria seems to the 1st preference for minimum number of respondentsand hence gives insight that even for a complex product like smart phones the user attachesless importance to it.12 | P a g e
    • Importance (1 - high, 4 - Low Priority 1 2 3 4 Price 30% 12% 6% 33% Style 12% 24% 30% 18% Features 21% 15% 24% 24% User-friendliness 10% 24% 27% 24%Benefit segment AnalysisTable 2: Product category tableDemovariable 1 2 3 4 5 6Sex 0-female 1-maleLocation NCR/DELHI Mumbai Chennai Bangalore Hyderabad OthersIncome <50000 50000- >100000monthly 100000Profession Private Govt Others employed employedWe have Performed Cluster Analysis (Benefit Segmentation) and Pseudo-F calculations. Thevalue of Pseudo-F is max for 3 segment levels. The value of maximum Pseudo-F is 8.3704. Cluster No Pseudo-F 2 clusters 7.662908 3 clusters 8.373043 4 clusters 8.11905213 | P a g e
    • Table 3: part worth utilities segment wise Final Cluster Centers Cluster Cluster(importance) 1 2 3 1 2 3 Rs 40000 -10.44 -9.28 -19.05 Rs 30000 -.46 -1.88 -2.03 22.70 21.26 48.00 Rs 20000 10.91 11.16 21.08 Slider -1.37 -4.32 -4.04 Qwerty -3.23 1.31 -.21 8.33 7.63 9.92 Touch 4.60 3.01 4.25 screen Low -7.22 -25.37 -5.63 Medium -1.84 3.25 -.08 17.33 49.41 13.56 High 9.07 22.12 5.71 Sleek .08 1.46 4.37 Trendy 1.90 1.02 -.17 4.13 4.10 10.26 Changeable -1.98 -2.48 -4.20 skin Apple 19.08 6.65 9.19 Nokia -6.18 4.66 -.89 47.51 17.59 18.26 HTC -25.59 -10.25 -6.07 Samsung 12.68 -1.06 -2.24Segment 3 is a of price sensitive than segment than segments 1&2 as its part worth utility importance ismore for price. Segment 1 is more of brand oriented. Mostly all segments are not much worried abouteither design or shape of the smartphone. It is widely assumed statement that any normally availablesmart phone must be a good shaped phone and will have touch screen compulsorily. Henceconsumers may not feel those two attributes are not as important as others such as brand, price anduser-friendliness.14 | P a g e
    • Table 4 : Anova table for segmentation ANOVA Cluster Error Mean Square df Mean Square df F Sig.Rs 40000 331.756 2 32.959 30 10.066 .000Rs 30000 6.522 2 28.210 30 .231 .795Rs 20000 398.522 2 53.657 30 7.427 .002Slider 20.861 2 22.022 30 .947 .399Qwerty 36.612 2 44.667 30 .820 .450Touch screen 4.653 2 31.434 30 .148 .863Low 923.569 2 33.384 30 27.665 .000Medium 43.339 2 7.427 30 5.835 .007High 621.743 2 36.544 30 17.014 .000Sleek 55.791 2 8.424 30 6.623 .004Trendy 12.172 2 12.170 30 1.000 .380Changeable skin 16.034 2 12.186 30 1.316 .283Apple 317.433 2 32.432 30 9.788 .001Nokia 190.143 2 74.542 30 2.551 .095HTC 989.509 2 57.211 30 17.296 .000Samsung 594.829 2 57.754 30 10.299 .000The F tests should be used only for descriptive purposes because the clusters have been chosen tomaximize the differences among cases in different clusters. The observed significance levels are notcorrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means areequal.From Anova table of cluster analysis, it is also found that, changing price from Rs 40000 to Rs 30000 isa significant rather changing to Rs 30000. Also, Apple has been chosen by consumers as a significantplayer as a brand in the smartphone market.15 | P a g e
    • Market simulationOur primary objective of this market simulation is to find the product attributes thatmaximizes the share of the product. Profitability cannot be an objective in this simulationbecause we are not known of costs of features of the product.The best segments from the benefit segment analysis is given belowTable 5: Best features of the 3 segments User- Segment Price Design friendliness shape Brand Segment1 20000 T/s High Trend Apple Segment2 20000 T/s High sleek Apple Segment 3 20000 T/s High sleek AppleThe following table gives the various attributes of various brands in the market.Table 6 User- Segment Price Design friendly shape Brand Product 1 40000 Touch screen High Trend Apple Product 2 35000 Touch screen High sleek Nokia Product 3 25000 Touch screen Medium sleek SamsungThe choice shares of the products are calculated by conjoint simulator using the principles ofmaximum choice or log it choice rules. If the three brands Apple, Nokia and Samsung launchthose products in the market, then the choice shares of the above products by the consumerscan be calculated as follow.Table 7 Choice share Choice share (Max choice (Logit choice Segment Brand rule) rule) Product 1 Apple 26.94% 24.34% product 2 Nokia 14.18% 19.86% Product 3 Samsung 30.56% 27.47% No purchase None 28.32% 28.32%16 | P a g e
    • Samsung would emerge as a most preferable consumer choice, if the same configurations arecompeting in the market. It is purely due to price advantage over the others. There is slightchange in choice shares from the both choice rules. It is most preferable to use log it choicerule for FMCG kind of products.Sensitivity AnalysisWhat if suddenly Google launches a phone with the following configuration? Let us see thecalculations of the choice shares of the consumers. It is assumed that, since Google is new tosmartphone market, it is brand is perceived as in between Apple and Nokia. Now let us seehow the dynamics of the smartphone market changes with the launch of Google smartphone.Table 8 Segment Price Design Uf shape Brand Product 1 40000 Touch screen High Trend Apple product 2 35000 Touch screen High sleek Nokia Product 3 25000 Touch screen Medium sleek Samsung (middle of Apple and Product 3 36000 Touch screen High sleek Nokia)The following table will give us the consumer choice shares of the various smartphones.Table 9: Choice shares Choice share (Logit choice Segment Brand rule) Product 1 Apple 18.54% product 2 Nokia 14.88% Product 3 Samsung 21.44% Product4 Google 17.09% No purchase None 28.05%So, with the introduction of Google with the above specified configuration, there is hugedamage to Both Apple and Samsung by 8% and 13% approximately assuming no reaction ofcompetitors with the new launch of the smartphone by Google.17 | P a g e
    • Suppose, in reaction to the Google’s launch, if Samsung changed its one of the attributes priceto Rs 22000/-Hence, the following table will give us the choice shares post Samsung’s reaction to Google.Table 9: choice shares Choice share (Logit choice Segment Brand rule) Product 1 Apple 17.89% product 2 Nokia 14.27% Product 3 Samsung 25.77% Product4 Google 16.41% No purchase None 25.66%There is slight gain of choice share for Samsung, but Google loses slightly. Whereas Apple andNokia don’t get any affect out of Samsung’s change of price. The entire usage conjointsimulator is captured in screenshot as an Exhibit1.18 | P a g e
    • Issues and recommendations to full-scale studyThere are several limitations in the study including limited sample set. The sample size issmall and the lack of details regarding the cost the sample is limited only to regular studentswhich should have been extended to staff, weekend batch students the more diverse samplewould have given more robust and better results. One more concern in the survey is manyrespondents did not complete the ASEMAP survey. Also we need to go for heterogeneoussamples to get perfect utility values.Conclusions 1. The five attributes we chose as key features for a Smart Phone gave us insights into the purchasing behavior of the consumers. The tradeoffs they had to make while making a choice of a Smart Phone among the attributes force them to choose few and leave out others. For certain individuals certain attributes were more important than others. The sequence of questioning ensured the consumer’s picked the attributes which really mattered to them. 2. Conjoint analysis helps us to understand the part worth utilities, there by importance levels and choice shares of any products. 3. Conjoint simulator can be used to strategically position the product or introduce the product into the existing market. 4. Apple remained undisputed leader in the smartphone market according to consumer preferences. Samsung is emerging as an alternative to Nokia.19 | P a g e
    • Exhibit-1Conjoint simulator for calculating choice shares20 | P a g e