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Syfte - Att undersöka hur en kundsegmenteringsprocess kan utformas samt vilka variabler man bör iaktta för att kunna erbjuda en lämplig kundservicenivå. För att uppnå detta syfte skall följande frågeställningar besvaras: 1. Vilka variabler bör ingå i en kundsegmentering? 2. Hur kan en kundsegmenteringsprocess utformas? Metod - En generell kundsegmenteringsprocess utformades. Processen har utvecklats genom kvalitativ forskning baserad på litteraturstudier samt intervjuer i en fallstudie. Under litteraturstudien granskades teorier i ämnet för att besvara frågeställningarna. Detta jämfördes senare med empirin som samlats under fallstudien. Resultat - Den utformade processen innehåller sju dimensioner med tillhörande variabler. Under studien har variablerna utvärderats för att ta reda på hur de påverkar situationen. Endast de variabler som hade ett stort inflytande på situationen togs med i processen. Studien visade att det finns olika strategier för att utföra en kundsegmentering. Vid utformning av en kundsegmenteringsprocess är det viktigt att veta vilka variabler som passar organisationens bransch samt hur de påverkar resultatet. Omfång och Avgränsningar - Rapporten är begränsad till att utforma ett förslag på en kundsegmenteringsprocess. Processen kommer därför inte att tillämpas på fallföretaget under fallstudien. Processen kan fortfarande generaliseras och användas av företag med liknade egenskaper. Ytterligare forskning skulle kunna sträva efter att inkludera andra variabler som passar in på fler branscher. Implikationer - Den utformade processen hjälper till vid beslutssituationer avseende kundsegmentering. Genom att balansera de variabler som föreslagits möjliggör dem en grund för olika kundserviceerbjudanden. Dessa variabler beaktar den eftersträvade generaliseringen. Bidrag och Rekommendationer - Kundsegmenteringsprocessen som presenteras i denna rapport är, såvitt författarna vet, den första i sitt slag med sin layout. Variablerna kan även användas i andra segmenteringsprocesser vilket visar en hög grad av generalisering. Vad som är unikt med den designade processen i denna rapport är att den innehåller en mix av två väl beprövade teorier inom kundsegmentering nämligen, Kotler’s (2009) Bottom-Up-Approach och Weinstein’s (2004) B2B Market Segmentation. / Purpose – To examine how the process of customer segmentation can be designed, and which variables to consider to offer an appropriate customer service. To achieve this purpose the following questions will be answered: 1. Which variables should be included in customer segmentation? 2. How can a customer segmentation process be designed? Method – A general process was designed. The process has been developed through qualitative research based on literature review and interviews conducted in a case study. During the literature review the authors sought for theories on the subject in order to answer the research questions. This was later compared to the empirical evidence collected from the case study. Findings – The designed process contains seven dimensions with related variables. During the study the variables were evaluated concerning their impact on the situation. Only variables that had a high influence on the situation were implemented in the process. The study showed that that there are various approaches towards performing customer segmentation. When designing a customer segmentation process, it is of high importance to know which variables suit the organizations line of business and how they affect the outcome. Research limitations – The thesis is restricted into designing a customer segmentation process, the process will therefore not be applied on the case company during the case study. The process can still be generalized and usable for companies with similar distribution setup. Further research could strive to include other variables. Implications – The designed process assists in the decision-making situation regarding customer segmentation. By balancing the variables it enables a basis for customer service offering. These variables take the requested generalization in consideration. Originality/value – The customer segmentation process presented in this thesis is, as far as the authors know, the first in its kind with its layout. The variables could be used in other segmentation processes as well which show a high grade of generalization. What is unique with the designed process in this thesis is that it contains a mixture of two well proven customer segmentation theories namely, Kotler’s (2009) Bottom-Up-Approach and Weinstein’s (2004) B2B Market Segmentation.

The main goal of this Master's Thesis is to discover and describe significant differences in consumer's behavior on the Czech tablet chocolate market. Based on these found differences reveal, characterize and develop segment's profiles. Further goal is to design relevant marketing recommendations for these segments. The theoretical part contains the explanation of the segmentation process. The analytical part includes main characteristics of the Czech tablet chocolate market and the analysis of the secondary and primary data. The market segmentation was performed based on the results of these analyses. For the segmentation process was used the IBM SPSS Statistics program. The outcome of the thesis discovers four market segments and proposes corresponding marketing strategies for them.

The main objective of this Masters thesis is to identify and describe segments of customers in coffee market in Czech republic. Furthermore objective is to formulate marketing recommendation on how to address those customers. To fullfil this goal is not be possible without deep knowledge of whole coffee market and of those customer segments. To understand the market itself, data from Nielsen agency are used. As to complete whole segmentation process MML-TGI data of Median agency are used. To paint the final picture of coffee market and to verify formulated hypothesis further qualitative research has been conducted in for of individual interviews.

Rapportens namn: Vilka är egentligen våra kunder?- en kvalitativ studie om segmentering i B2B företag Frågeställning: Hur utarbetas och genomförs segmentering av företag verksamma på B2B marknaden? Syfte: Syftet med arbetet är att undersöka hur företag utarbetar och genomför segmentering på B2B marknaden. Vidare undersöka vilka faktorer som är viktiga att ta i beaktning för företag vid utförandet av segmentering på B2B marknaden.Vi ämnar även att presentera både teoretiska och praktiska förslag på hur B2B företag bör arbeta med segmenteringsstrategier. Metod: Uppsatsen är en kvalitativ fallstudie som antagit en abduktiv forskningsansats. Datainsamlingen har skett vi semistrukturerade djupintervjuer med sju olika B2B företag. Resultat och slutsatser: Resultatet visar hur företag idag utarbetar och genomför segmentering. Vidare vilka kunskaper och vilken förståelse de besitter utifrån de segmenteringsvariabler som framkommit i studiens teoretiska referensram. Slutsatser kunde dras kring att företag i dagsläget inte i många fall arbetar aktivt och iterativt med att segmentera sin marknad och har inte följt en specifik och tydlig process vid utförandet. De besitter kunskaper som hade kommit till användning vid en vidare utveckling av de segment de arbetar utifrån idag. Teoretiskt och praktiskt bidrag: Uppsatsen presenterar en reviderad segmenteringsmodell utifrån den teoretiska referensramen i kombination med den insamlade empirin. Behov och potential framkommer som kompletterande faktorer att ta i beaktning. Det praktiska bidraget ger förslag på hur företag bör utarbeta och genomföra segmentering. Vidare presenteras förslag till segmenteringsstrategi till uppsatsens uppdragsgivare. / Name of report: - a qualitative study of segmenting the B2B market Research question: Who are actually our customers?- a qualitative study concerning segmentation in B2B companies Purpose: The purpose of this thesis is to examine how companies active in the B2B market prepare and implement segmentation. Furthermore to examine which different factors to take into consideration when segmenting the B2B market. We also intend to provide theoretical as well as practical implications of how B2B companies should work with segmentation. Method: This thesis is of qualitative character and follows an abductive research approach. The empirical data of this study have been gathered through semi-structured interviews with seven different B2B companies. Results and conclusions: The results shows how companies work with segmentation today, furthermore which knowledge they possess concerning the presented segmentation variables from the study’s theoretical framework. Conlusions have been made that in many cases companies do not actively and ongoing work with segmenting their market. Furthermore they have not followed an specific and clear process when segmenting. Companies do however possess knowledge which can come to use in order to develop the segment for which they work with today. Theoretical and practical contribution: The thesis presents a revised segmentation model based on the theoretical framework in combination with the collected empirical results. Customers needs and potential emerged as complementary factors to take into account. The practical contribution provides suggestions on how companies should develop and implement segmentation. Furthermore, proposals for segmentation strategy are presented to the principal of this thesis.

The main objective of the diploma thesis is to determine the perception of the Kolonáda brand by young people and how to become relevant for them. This would not be possible without specific knowledge of the whole market and without knowledge regarding the segments of biscuits and wafers consumers. The market segmentation is based on MML-TGI data collected by the research agency Median, five segments are revealed. I have also implemented my own questionnaire research on a sample of 480 respondents aged up to 34 years including. Based on the results of the practical part, recommendations for the Kolonáda brand are proposed -- how to become more relevant for the young consumers and stay attractive for the current consumers.

Als Datengrundlage für die Erhebung von Flächennutzungsparametern, wie sie in geografischen Informationssystemen (GIS) abgelegt und verwaltet werden, dienen oft Bilddaten aus der Erdfernerkundung. Die zur Erkennung und Unterscheidung der Objekte notwendige hohe Pixelauflösung führt bei der Erfassung eines Zielgebiets wie beispielsweise einer Stadt zu enormen Datenmengen. Aus diesen Bilddaten gilt es, möglichst schnell und preiswert die für ein GIS notwendigen Informationen, wie Umrissvektoren und Objektattribute, zu extrahieren. Diese Arbeit ist ein Beitrag zur Automatisierung dieses Schritts mit besonderem Schwerpunkt auf der Gebäudeextraktion. Datengrundlage sind hochauflösende multispektrale Orthobilder und ein digitales Oberflächenmodell (DOM) der digitalen Luftbildkamera HRSC-A bzw. HRSC-AX zum Einsatz. Deswegen werden das Aufnahmeprinzip sowie die Datenverarbeitung der HRSC überblicksartig vorgestellt. Auf Basis dieser HRSC-Standarddatenprodukte wird ein Vorgehen zur Extraktion von Objekten entwickelt. In einer hierarchisch geordneten Abfolge an Segmentierungsschritten werden aus der Pixelinformation bedeutungstragende Einheiten extrahiert. Dieser Segmentierungsansatz lässt sich auf mehrere Objektkategorien, wie Straßen oder Ackerflächen, erweitern. So werden in der aktuellen Entwicklungsstufe neben Gebäuden auch Baumregionen detektiert. Anhand des Oberflächenmodells werden erhöhte Regionen erkannt. Dazu wird das DOM durch Berechnung eines Terrainmodells auf Grundhöhe normiert. Für erhöhte Objekte wird die Grundhöhe aus umliegenden Grundregionen abgeleitet. Die erhöhten Regionen werden anschließend in Bäume und Gebäude unterteilt. Dazu werden aus den Multispektraldaten Vegetationscharakteristika bestimmt und entsprechende Baumsegmente ermittelt. Die Gebäuderegionen resultieren aus einer Nachverarbeitung der verbleibenden Segmente. Um Gebäudekomplexe in einzelne Häuser aufzuteilen, wird ein gradientenbasierter Ansatz entwickelt. Anhand der für Brandmauern typischen Gradienteninformation werden Linienhypothesen zur Unterteilung der Gebäudesegmente generiert. Diese werden schrittweise anhand geometrischer und radiometrischer Kriterien auf ihre Plausibilität überprüft. Schließlich werden die ursprünglich aus dem DOM stammenden Konturen der Gebäudesegmente und deren Übereinstimung mit Bildkanten eines Orthobildes betrachtet. In einem adaptiven Ansatz wird das Konturpolygon durch die Gradienteninformation an angrenzende Bildkanten angepasst. Zur Umsetzung typischer Gebäudegeometrien wie rechter Winkel oder Parallelität werden innerhalb des Adaptionsprozesses entsprechende Nebenbedingungen formuliert. Die Extraktion erhöhter Objekte wie auch deren Unterteilung in Bäume und Gebäude erfolgt mit hoher Genauigkeit, z.B. liegen die Detektionsraten bei Gebäuden über 90%. Der neuartige Ansatz zur Unterteilung in einzelne Häuser ohne explizite Liniendetektion führt bereits in der vorgestellten Entwicklungsstufe zur Beschleunigung einer manuellen Interpretation. Die adaptive Verbesserung der Gebäudekontur führt zu gebäudetypischeren Umrissen ohne Beeinträchtigung der hohen Detektionsraten. / Remote sensing image data are often used as a basis for determining land use parameters, as they are stored and managed in geographic information systems (GIS). Covering a target area leads to an enormous amount of data due to the high pixel resolution required for recognizing and discriminating objects. To effectively derive GIS information like contour vectors or object attributes from these data, the extraction process has to be fast and cost-effective. This thesis is a contribution to the automization of this step with a focus on building extraction. High resolution multispectral ortho-images and a digital surface model (DSM), generated by the digital aerial camera HRSC-A or HRSC-AX, are used as data basis. Therefore, the HRSC imaging principle and data processing are summarized. Based on these HRSC standard data products, an object extraction scheme is developed. In a hierarchically ordered sequence of segmentation steps, meaningful units are extracted from pixel information. This segmentation approach is extendable to several object categories like streets or fields. Thus, tree regions, as well as buildings are detected in the current stage of implementation. Elevated regions are recognized using the digital surface model. For that purpose the DSM is normalized by calculating a terrain model. For elevated objects the terrain height is derived from surrounding ground regions. Subsequently, the elevated regions are separated into trees and buildings. Determining spectral characteristics of vegetation from the multispectral data leads to corresponding tree segments. The building regions result from post-processing the remaining segments. In order to split the building segments into single houses, a gradient based approach is developed. By means of the gradient information associated with firewalls, line hypotheses for subdividing the building segments are generated. Their plausibility is checked by gradually applying geometric and spectral criteria. Finally, the building contours, originally derived from the DSM, and their correspondence to image edges in an ortho-image, are considered. In an adaptive approach, the contour polygon is adjusted to neighboring image edges using the gradient information. Typical building geometries like right angles or parallelism are enforced by applying corresponding constraints in the adaption process. The extraction of elevated objects, as well as the separation into trees and buildings, is carried out with high accuracy, e.g. the building detection rates are over 90%. In the current development stage the novel approach for separating building segments into single houses without an explicit line detection already leads to a speeding-up of a manual interpretation. The adaptive improvement of building contours leads to building typical contours without affecting the high detection rates.