What’s Up with Pasta

Whats Up With Pasta Q1 We deficiency to understand and look into wherefore the Spaniards ar spending relatively less on Pasta than its European neighbors. Current grocery query make by AEFPA offers insufficient data, so we privation to improve data quality. The main goal is the get a clear demographic segmented grocery store overview. One of the problems is that we s runnot clearly depict the potential and current alimentary paste consumers clearly we simply do not love enough about of core target group. In add-on we need insights on consumer behavior and habits as we do not know what drives the consumer decision when choosing pasta and when declining pasta.Another advantage of a broad food market correction would be that it would become clear if there be segments in the market currently not being explored. As a result we get out be able to clearly identify the market entry barriers for pasta. agree to our calculations (Appendix 1), there is an underutilized yearly market cracking of EUR 87Mln. Given this signifi potentiometert come up we find it justified to spend 0. 2% (Eur 175. 000) of the market gap initializing the market search plan, collect the data and train the analysis.Costs to merchandising strategy, marketing cooking and implementation are not included in this figure. We estimate the general cost of the market research exit be Eur 132. 800 Judging from unaffixed discussions with contacts in Unilever and Kraft Foods, our estimate seems to be on the low side. Q2 methodological analysis We are interested in conducting both quantitative and qualitative research. In our opinion we need both elements to fully understand the market. This volition onlyow us to better segment the market. Starting point of the quantitative research is the detailed quantitative research already d iodine by AEFPA.The geographical sales overview, distribution channels and sales pr. pasta image, mustiness be investigated muchover. We suggest co nducting a demographic naval division overlay to this data, as the segmentation give serve us by dividing a large creation/ model into specific customer groups. We are opting for the demographical segmentation as we comport to receive a large amount of data that otherwise would not be feasible to analyze. Therefore, we cluster the in mixed bagation to make patterns of sub-groups visible and lead enable to identify consumer profile and behaviors.We refer to this as top-down market research. The consumer behavior can only be partly captured in the demographic segmentation, so to ensure we choose a bulky experiment of data, we interpose a bottom-up process by initiating Shopper Insights research. Shopper Insights will in accompaniment to bring to additional data on behavior also go out invaluable insights to the customers perception of pasta. The aim with Shoppers Insight is to passively monitor the customers behavior in the situation of purchase at point-of-buying to learn about the conversion rate.Unilever defines Shoppers Insight as focus on the process that takes place mingled with that first pattern the consumer has about buy an contingent, all the way through the selection of that item. This is further underlined by practical examples from Kraft Foods Switzerland, who has provided access to their methodology to this group. We will be adopting the methods of 5 Ss to conduct our Shopper insights research and conduct this across the difference distribution channels menti unrivaledd in the case.Detailed explanation in Appendix 2 By making use of both top-down and bottom-up quantitative research, we feel we have adequate data quality. nevertheless it is critical to maintain a satisfactory sample surface. We assume our sample pool will be the entire Spanish population. There are many considerations when choosing a sampling size. We consider it a tradeoff between costs and sampling quality as there is a genius-dimensional relationship between t he sampling size and the cost. We estimate that the sampling size must be at least 384 people. See further dilate in appendix 3.To finish the research we introduce Consumer Insight which is a qualitative overlay. Personal interviews with customers will be done immediately aft(prenominal) the consumer has been observed in the Shoppers Insight. The sample size when conducting qualitative research is less important as there is no need for statistical significance, so we will be highly selective when choosing participants. Actually we will aim to only interview the High-Consumer and Non-consumer segments found in the top-down demographic segmentation research.This will provide strong qualitative data for creating the marketing strategy and planning. These topics will not be discussed in this paper. Q3 Implementation As we want to build in the existing data from AEPFA, significantly more(prenominal) data collecting must be done. We would conduct a look back on a large sample, using these four variables Age, flavor-cycle stage (the life cycle stage of a consumer group defines what will be the need of that particular customer), Gender and Income. In addition questions in pasta purchasing history and frequency would be asked.The questions will be designed so the answers can be directly comparable across the entire sample. This can be achieved by having a 1-5 scale designed on which the answers must fit one of the numbers. Example Question How often do you eat pasta, Possible answers 1 Never, 2 ones a day, 3 ones a week, 4 ones a month, 5 ones a year. By constructing all questions to fit such answer-schedule, we will be able to achieve statistical significance. The result will be a clear segmented group, where we can establish who are the current consumers (core buying segment) and non-consumers (core anti-buyers).We commit these segments should be targeted for further pe cabbageration. Next step we passively and discretely monitor the consumer at point-of-buyin g using the 5 Ss approach (See appendix 2). We will be have in all the distribution channels mentioned. This can be done via video or via physical presents. It is paramount the customer is unaware she/he is being monitored as this potentially would influence the buying habits. The consumer segments found higher up the consumer and non-consumer will be specifically targeted in the monitoring. I. e. hen a consumer fits one of the segments, the monitoring will be initiated. We wish to focus on these segments callable to costs, but could increase the sampling to all customers across all segments if cipher would allow. As the quantitative research should not stand alone, we would initiate in-depth interviews with more open-ended questions to better grasp the motivation behind the choice make by the customer. Such questions could be Why did you buy pasta, What type of pasta do you normally buy, why did you buy pasta instead of rice or potatoes. . For the non-consumers questions coul d be Why do you hold rice/potatoes instead of pasta, Which pasta products are you missing in the shop etc. We believe the quantitative and qualitative output of this vast research plan, by identifying the two interesting segments and dwell into their motivations behind their choice, would form an excellent base for developing an effective market strategy and for creating an overall marketing strategy for Pasta in Spain. ? cecal appendage 1For the calculations of the market gap difference in current and potential market we have anticipate the following Current year is 1990. Potential year is 1992. Population has increase by 0. 6% from 1990 to 1992. Euro/Pesetas exchange rate is 166. 386. (Official final fixing when Spain choose the Euro) Consumer behavior in terms of demand of the different pasta types is idempotent from 1990 1992 Pasta determine was inflated with 4% from 1990 1992. Consumption of pasta arise 1 kg pr. Capita from 1990 1992 Pasta securities industry in 1 990 Pasta Market in 1992 ? APPENDIX 2The 5 Ss method is designed so marketers can observe a customer from move into point-of-buying (POB) to final transaction. The method works on two takes 1. Consumer level The consumer are monitored so we follow the target discreetly around the POB. We observe how the consumer Sees, Scans, Spot, make interest and (potentially) Select the product we represent. This gives us valuable information as we can identifies were in the process we lose the customer (also call Fall-out). The communication rate is computed as number of consumers selecting our product out of shoppers entering the POB.The net sales for a given party is highly sensitive to changes in conversation rate Only a small increase in conversion will generate a (relative) large increase in sales. 2. Store layout and the category placement in POB. We can observe the customers superpower to find the product in POB is the product visible to the consumer, where on the shelve is it plac ed, is it placed with complementary goods? or supplementary goods? After the research is concluded feedback will be delivered to POB to improve visibility if required. ? APPENDIX 3 We recognize the sample size of 1067 is a (very) rough estimate.We opted for an net resource from Creative Research Systems as we decided to focus our resources on the research planning and method. The sample size is computed using Confidence level 95% Confidence Interval (margin of error) 5% Population 40000000 We believe these input factors are comparable with real-life statistical simulations. ? APPENDIX 4 As we require a specialized set of data and therefore need a specialized report, we assume such report must be order and bought directly at a Market Research company or institute under normal circumstances.As it is specialized we assume the price will be high, so budget with a one-time payment of EUR 75. 000. We have only very little foundation for making this estimate. It was the conclusion of a co nversation between marketing executives on Linkedin. The bottom-up research will need to conduct 384 observations in order to fulfill to the minimum sample size requirement found in appendix 3. Based on information from marketing sources at Kraft Foods, we consider it realistic one market researcher can conduct 25 observations in one day. This results in 15. 3 days of work at an assumed casual rate of EUR 1000