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MARKETING MANAGEMENT PORTFOLIO MODULE 1 2º SEMESTER Adela García González Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests Definition of Market Research: A market research process is carried out in order to: a. b. c. d. identify and define marketing opportunities and problems Understand the market in matter make , evaluate and improve marketing actions Make new and better marketing strategies A marketing research gathers the process required in order to achive the objectives mentioned above. 1.Problem identification 2.Research design selection 3.Sampling Design 4.Measurement and scaling 5.Questionnaire development First of all, we have to get to know our customers in matter. For this reasons we have to collect primary or secondary data to understand the whole process of the buying behaviour that customers go through when shopping. Once we know the buying behaviour of our customers we can start with the segmentation process. Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests 1. Research problem development and objectives Why do we want to make a market research? An overload in the market as well as the increasing competition of online-shopping was the problem identification for the Lyngby Storcenter questionnaire. Our purpose of sampling was to study the habits and behaviour of Lyngby Storcenter, from now on referred to as LSC, customers in order to narrow their target market and find a positing that can be more beneficial for LSC, when trying to compete with the rapidly growing online market. Our main question, which we based our questionnaire on, was; how do customers interact with LSC? We have based our sub-questions on the 7 O’s framework and created specified questions according to them. We have then further developed some follow-up questions to get a more specified answer Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests 2. Research design selection a. Primary Data Collection Exploratory research (quantitative): In this point we know there a problem in the market, but we do not know what the problem is. Hence we want to find out the problem and the reasons. The data collected is quantitative, as the data that can be counted (discrete data) or measured (continuous data) There are several techniques: - In-depth interviews - Focus groups - Proyective tecniques (pictorical construction , word association and sentence completion tecniques) Conclusive research (qualitative): In this point, I have made an hypothesis of the potential problem, and now I want to make a description for making an strategy to solve it. (when, how, who…?) The data collected os qualitative since the data is information that describes something. There are two types: -Descriptive designs (dummy tables) ~ surveys or observation ~ -Causal: I make something and I want to see the effects. For instance with the launc of a new female shampoo. b. Secondary Data Collection Internal data External data It describes s.t It counts It measures Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests 2. Research design selection (probability or non-probability) The research design used in our questionnaire is exploratory research, because we want to understand how customers interact with LSC and since we are conducting a survey we are using quantitative primary research. 3. Sampling Design Who should I ask? We have conducted 100 interviews in Lyngby and used the sampling design called an optimal stratified sample method, in order to be as accurate as possible to the estimate of the population in Lyngby. According to Danmarks Statistik there are around 52% females and 48% males living in Lyngby. We tried to take this into account when conducting our interviews. http://www.statistikbanken.dk/statbank5a/default.asp?w=1366 4. Measurement and scaling (Comparative or non-comparative scaling) Our questionnaire is built on fixed-alternative questions. We are using comparative and non-comparative scaling when measuring our answers. Our reliability for the population is slightly compromised because we have conducted 10% more interviews on females according to the population numbers in Lyngby. We have taken this into account when studying our data but we feel it will not compromise our validity; hence there are a lot of articles that conclude women shop more than men. http://www.commutemedia.com/update-og-nyheder/saadan-naar-du-kvinderne---lige-foer-de-griberdankortet.aspx 5. Questionnaire development https://docs.google.com/forms/d/15i5PO8RzyHU99EkxehwISup7q_7GqcNYiU5ZtaXZuGk/viewform?c=0&w= 1 ANALYSIS From our questionnaire we have identified that there are several trends that we want to highlight. Out of the 100 we asked 92% of them if they go to LSC, even though only 39% of them said they live in Lyngby. This means that 56% of our sample visits a LSC even though they do not live in its commune. The mean for the overall age registered in our survey is 33,12 with a standard deviation of 16. Group data Age Frequency Mean (x ̅ ) xi fi sumfi*xi/n (xi-xline) 15 19 285 -18,12765957 328,6120416 6243,628791 22 26 572 -11,12765957 123,8248076 3219,444998 30,5 15 457,5 -2,627659574 6,904594839 103,5689226 40,5 6 243 7,372340426 54,35140335 326,1084201 50,5 9 454,5 17,37234043 301,7982119 2716,183907 58 19 1102 24,87234043 618,6333182 11754,03305 Total (n) 94 3114 … Mean 33,12765957 Variance sum f*(xi-xline)/n-1 261,9673988 St.Deviation 16,18540697 (xi-xline)^2 … fi*(xi-x)^2 24362,96809 We can conclude from our contingency table and chi-test we have found that there is no relationship between age and spending in our sample. The outcome might have shown a relationship had our sample been larger and our spending intervals more general. In light of these results we have chosen not to segment based on income and age. The three models below show us that 82% of all people asked are initiators and 85% are also the deciders. There is a trend that almost half (45%) of all people asked gets influenced while shopping and about half of those gets influenced by their friends. Who makes the decision to go shopping? Who makes the decision to buy? Who influences your choice when shopping? With this knowledge we can establish that a persons own wants and desires goes before the ones of others and that they are in control of the whole buying process. People want to feel unique and feel that their needs are catered and the offers they receive are customized to them. We live in a world where we as individuals measure ourselves and reflect on our surroundings, in other words, self-promotion. That is why we let our surroundings have an influence on our buying behavior. Objectives Malls are the perfect stage for us to cover our need to consume, to own, to experience and to be inspired to even more consumption. The desire is insatiable, as mentioned people are driven by self-promotion, more now than ever in this digital age with Facebook, Twitter and Instagram. The motivation for customers to buy revolves around our connection with our surroundings and approval of those, but we do it for ourselves. http://jyllands-posten.dk/indland/kbh/ECE3301933/begaer-i-trygge-rammer/ http://www.medscape.com/viewarticle/814649 Operations According to the data collected by the questionnaires, we figured out that: -20% of all our respondents usually visit LSC once a week and 47% once a month. - While they are shopping around the mall, 52% of them visit some restaurants or cafes. -49% of customers usually spend between 1 and 2 hours in the mall, while only a 31% spend less than 1 hour shopping. - During this period, 67% of consumers visit between 2 and 5 shops and only a 20% visit 6 or more shops. Another aspect to focus on is the way of providing information about LSC for customers. Besides the fact that the most of respondents, representing 30% of all interviewed, stated that they do not wish to have other information about LSC, there is a significant demand for information using different technology methods. The most frequent answer was to receive information: -via social media ,17% of respondents -using email , 11% of sample -in-app advertisments , 9% - This gives us a foundation to focus on technology when talking about positioning strategy. Almost every individual has access to these already by using their smartphones. We have gathered some data on how many people in our sample, shop online and why. The approximate confidence interval for two proportions shows that between 55-75% of our sample shop online, with a level of confidence of 95%. We can also conclude that 43% of them shop online for convenience and 33% shop online due to the wider selection (see excel appendix for calculations). The approximate confidence interval for two proportions shows that between 24-45% of online shoppers would like to see more social events and experiences in LSC. Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests STP MODEL SEGMENTATION Segmentation consist of dividing the population or customer into different groups depending on common characteristics or different criteria. One can conducting a segmentation by classifying their customers : -Demographically -Geographically -Psychographic AIO (Activities, Interests, Opinions) VALS (Values and Lifestyles) -Behavior: how the act towards, feel about and use the product/service. Criteria for behavioural segmentation: Users and non users 80/20 rule Long tail Usage occasions Segmentation ~~ Lyngby Storcenter Psychographic factors: We have defined the different segments after criteria in our data. Here we can conclude that the psychographic parameters was the most important. We have chosen to use the factors of influences, and buying behavior to find the perfect segments. To start with we have the individualist, this is a person who has answered myself for question 7,8 and 9, which is the categories about influences (43 people out of 100). Then we have the family orientated. This is a person who mostly does shopping for the whole family and not just for them self. They have answered that they mostly do family shopping in question 14 (22 people put of 100), and last but not least we have the listener, This a person who is influenced by the people around him/her when they decide when, where and why they buy. They have answered that he/she is influenced by someone else when buying in question 7 (42/100) Buying behavior We have decided to focus on where the costumers normally go shopping. According to question 20 there is 4 groups. Behavior 1: goes to a local store Behavior 2: many smaller shops like a shopping street Behavior 3: goes to malls Behavior 4: shops online The individual (43) The family oriented The listener (42) (22) Behavior 1 I1 (7) F1 (10) L1 (13) Behavior 2 I2 (6) F2 (4) L2 (8) Behavior 3 I3 (23) F3 (7) L3 (17) Behavior 4 I4 (7) F4 (1) L4 (4) We have chosen the segment of I3 since this is the biggest segment and the one which also use the most money monthly on both groceries and leisure items of the segments (substantial and measurable market segment). Even more they also have a higher use of technology, social media and other technology’s like this, which gives us many ways of advertising to them. Therefore these features make the segment accessible for LSC. As mentioned before, the segment has individual tendencies in the buying process and might react differently to various marketing strategies; hence it is a differentiable segment. As uniqueness as the main feature of this segment, we consider the best marketing strategy for this market is concentrated marketing strategy, which consists of carrying out a single marketing mix to this specific segment, as they value the customized products, newer ways promotion, particular prices and specific places for shopping Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests TARGETING Targeting consists of selecting the most appropiate market segment or segment to serve. Steps in targeting: 1. Evaluate market segment 2. Develop Segment Profiles 3. Choose a targeting strategy -Undifferentiated targeting strategy (coca-cola): the same marketing strategy for all the segments -Differentiated targeting strategy: different marketing strategies for each different segment -Concentrated targeting strategy (Toy industry): a specifc marketing strategy for a single segment. Factors to look at: -Company resources, skills ans strategies -Market/segment attractiveness and variability -Character and product lifecyle -Competitive issues EVALUATION OF MARKET SEGMENT MEASURABLE : size, purchasing power, characteristics SUBSTANTIAL: adequate size, profitable this is the biggest segment and the one which also use the most money monthly on both groceries and leisure items of the segments ACCESIBLE: can it be reached they also have a higher use of technology, social media and other technology’s like this, which gives us many ways of advertising to them DIFFERENTIABLE:respond differently ACTIONABLE the segment has individual tendencies in the buying process and might react differently to various marketing strategies; hence it is a differentiable segment. DEVELOP A SEGMENT PROFILE The perfect target group o Trendy o Cares about experiences o Uses technology o Want experiences o Material self-expression o Moral o Look o Lifestyle SELECTION OF TARGETING STRATEGY As uniqueness as the main feature of this segment, we consider the best marketing strategy for this market is concentrated marketing strategy, which consists of carrying out a single marketing mix to this specific segment, as they value the customized products, newer ways promotion, particular prices and specific places for shopping. Positioning Positioning means to decide how the company wants its products, brand and/or cooperation to be perceived and evaluated by target markets, and how this should be achieved. The Position is the idea customers have in mind of our brand or company. It is the “brand personality” Process: 1. Analyze competitor’s position 2. Perceptual mapping is a visualization of how customers view products/brands within a market. It is used to determine the position of a product/service. 3. Offer a good/service with competitive advantage 4. Finalize marketing mix 5. Evaluate respones and modify as needed Types of positioning: a. Unique selling proposition (it describes the benefits “HSBC The world’s local bank”) b. Emotional selling proposition (non-functional attribute “apple ~ think different” it motivates you to act) c. The positioning statement ( it explain the brand position) Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests Positioning Strategy If we look at the perceptual map here to the right, then we can conclude that LSC has a high popularity, 40% of our sample preferred LSC and 92% of our sample went to LSC. Lyngby Storcenter should strive to create unique experiences and new and intriguing store selection in order to be perceived as a possible contender with the online market. Through the competitive strategy of differentiation we gain a larger part of the market, as supported by the current trend in the individualists uniqueness and personality. Positioning Statement Lyngby Storcenter is a shopping center for all unique individuals that deliver a wide variety and special experiences for shoppers by incorporating personalized offers and experiences when an individual strives to find unique items while shopping. Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests INTRODUCTION DATA DATA: are the facts and figures collected, analyzed and summarized for presentattion and interpretation. All the data collected is called “data set” ELEMENTS: are the entities on which data are collected (each individual European exchange – second column- the data set contains 10 elements) VARIABLE: is a characteristics of interest for the elements (exporters, value, share, annual change) OBSERVATION: the set of measurement obtained for a particular element. ( 880-25.0-5) INTRODUCTION SCALES OF MEASUREMENT The scale of measurement determines the amount of information contained in the data and indicates the most appropriate data summarization and statistical analyses. o Nominal scale: when the data for a variable consist of labels or names used to identify an attribute of the element. In some cases the scale of measurement is nominal with a numeric code or non numeric codes are used. It facilitates the collection of data into a computer. o Ordinal scale: the data exhibit the properties of nominal data and the order or rank of the data is meaningful. o Interval scale: the data shows the properties of ordinal data and the interval between values is expressed in terms of a fixed unit of measure. Interval data is always numeric. E.g: 3 students with different scores, 3-6-10, there are three points of difference between students 1 and 2, and there are four points between student 2 and 3. o Ratio scale: the data have all the properties of interval data and the ratio of two variables is meaningful. Variables such as distance, height, weight and time use the ratio scale of measurement. This scale requires that a 0 value be included to indicate that nothing exists for the variable at 0 point. E.g: the costs of a car. A 0 value means that the cars cost nothing, it’s free. If we compare the costs of 30.000 eur for one car to the cost of 15.000eur for a second car, the ratio property shows that the first car is 2 times the cost of the second car. QUALITATIVE & QUANTITATIVE DATA Qualitative data include labels or names used to identify an attribute of each element. It uses either the nominal or ordinal scale of measurement and may be non-numeric or numeric. Quantitative data require numeric values that indicate how much or how many. It is obtained using either the interval or ratio scale measurement. DESCRIPTIVE STATISTICS Measures of location: a. Mean the average value . It can be used with open intervals, it is affected by high or low value. (sample data) = ∑xi (nº sample) / n- nº observation a. Median the value in the middle from the smallest to the largest value. The median is not affected by extreme value, it works with open intervals ( relevant for income/wealth) 1º arrange the data in ascending order 2ºmedian calculation: middle (2)1 value / 2 c. Mode the value that occurs with the greatest frequency Measures of variability: how disperse, spred out a distribution is. a. Variance: the difference between the value of each data and the mean “deviation about the mean” ∑ (xi - xline )^2 / n - 1 a. Standard deviation: the average spread around the mean square root of the variance Sample: xline : sample mean S: sample variance S2: sample standard deviation p̂ : sample proportion: 15/30= 0,50% We have always a sample error = population mean – sample mean, p - p̂ The bigger sample size, better real size we approach These are point estimates for the same values of population The bigger the deviation is, higher probability of making an error. Confidence level: how certain do you want to be X line +- = confidence level + standard error (n, s^2) Distribution: Standard normal distribution: It has the mean value of 0 and the standard deviation of 1. There are different distribution. We use it in certain situations. If I know the population variance, then I use Z distribution in my calculation. I f n is bigger than 30 is good, I have a Z distribution, which is used to calculate the confidence level. If I have a small sample, I do not know nothing, my confidence should be broader, and I have a t distribution. If n is smaller than 30 we use t distribution. Population: μ: data from a population : population variance : population standard deviation p: probability statistics, the probability of having females marketing students X: the number of female marketing students (eg. 15 females) n: 30 If n is bigger than 40, we use a Z distribution If n is smaller than 40 we use a T distribution Market Research During this module our main learning focus consisted of understanding, conducting and analyzing a market research plan, in order to analyze consumer behaviour and identify target groups and positioning strategies. Moreover we used different statistical method to backup our findings. This is the agenda that we followed during this module: 1. Market research process Problem identification Research design selection Sampling Design Measurement and scaling Questionnaire development 2. STP Model Segmentation Targeting Positioning 3. Statistics: Descriptive statistics Interval stimation Confidence intervals and sample size Goodness of fit and independency tests CONFIDENCE INTERVAL Statisticians use a confidence interval to describe the amount of uncertainty associated with a sample estimate of a population parameter. A confidence interval is the probability that a value will fall between an upper and lower bound of a probability distribution. The confidence interval can take any number of probabilities, with the most common being 95% or 99%. We cannot conclude anything, if the difference is a negative value. A random sample of 1562 students was asked about their attitude on a scale from 1 (strongly disagree) to 7 (strongly agree) to the following statement: “Most advertisements are insulting the intelligence of the average consumer”. The sample average answer (attitude) was 3,92 while the sample standard deviation was 1,57. Calculate a 95% confidence interval for the population average attitude. Confidence interval for mean (z-distribution) Sample size 1562 Average 3,92 Standard deviation 1,57 Level of confidence 95% The result Lower limit 3,84214129 Upper limit 3,99785871very small interval Conclusion: With 95% probability , the population mean is between 3,84 and 4.00 GOODNESS OF FIT The goodness of fit of a statistical model describes how well it fits a set of observations. The conformity between an experimental result and theoretical expectation or between data. In order to calculate a chi-square goodness-of-fit, it is necessary to first state the null hypothesis and the alternative hypothesis; Ho is maintained until there is sufficient evident to the contrary. Ho is supported by experience. Hi is selected if the null hypothesis is rejected. H1 is supported by the sample data. a significance level / test level (such as α = 0.05) is used, it means that the test is being conducted with 5% probability of rejecting a true Ho. Goodness of fit is used to test: If the same is representative If the observations are equall distributed among th categories Conclusion: Ho is accepted when the p-value is higher than the significance level, which means that the sample is representative according to the specific criteria. Ho is rejected when the p-value is lower than the significance level. Therefore the p-value shows the significance level that should be used in order to change the conclusion. Then the farther away the p-value is from the used test level the more significant is the conclusion. When Ho is rejected… We have to figure out what is wrong in our sample. 1st. we look at the tests. The bigger the test result is, the bigger the difference between the observations numbers and the expected numbers is. Conclusion: The p value is above the test level (0,5), then we accept it. Ho is accepted since p-value 0,5952 is higher than the test level 0,05. The sample is representative according to age. Our conclusion is extremely significance since the p-value is much higher than the test level. Hypotheses H0 : The distribution is the given distribution HA : The distribution is not the given distribution Calculations i Category 1under 31 231-40 341-50 451-60 5over 60 Sum pi Ei 0,18 0,24 0,22 0,19 0,17 1 Oi 36 48 44 38 34 200 Testst 32 0,44444444(32-36)^2/336 41 1,02083333 50 0,81818182 39 0,02631579 38 0,47058824 200 2,78036362 The result Degrees of freedom Test statistic p-value 4 2,78036362 0,59522704 CONTINGENCY TABLES Contingency tables are used to test if there is relationship/dependency between 2 criteria- if not there is no purpose in dividing the data according to that criteria. The result Degrees of freedom Test statistic p-value 3 1,91 0,59090393 Conclusion: Ho: The p-value is above the test level (0,05), then we can accept it. The conclusion is highly significance. I reject Ho, since there is no relationship/depenency between origin and interests. The expected values are bigger than 3. Adela García González Marketing Management Module 1, Second semester