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.

Multiple facets of perceived value perceptions drive loyalty intentions. However, this value-loyalty link is not uniform for all customers. In fact, the present study identifies three different segments that are internally consistent and stable across different service industries, using two data sets: the wireless telecommunication industry (sample size 1,122) and the financial services industry (sample size 982). Comparing the results of a single-class solution with finite mixture results confirms the existence of unobserved customer segments. The three segments found are characterized as "rationalists", "functionalists" and "value maximizers". These results point the way for value-based segmentation in loyalty initiatives and reflect the importance of a multidimensional conceptualization of perceived value, comprising cognitive and affective components. The present results substantiate the fact that assuming a homogeneous value-loyalty link provides a misleading view of the market. The paper derives implications for marketing research and practice in terms of segmentation, positioning, loyalty programs and strategic alliances. (authors' abstract)

Cílem práce je nastínit možnosti využití analytického CRM k zvyšování ziskovosti společnosti. Analytický CRM se zabývá analýzou zákaznických dat, které slouží jako podpora pro operativní a strategické rozhodování firmy. Teoretická část práce se zabývá různými způsoby segmentace zákazníků, zákaznickými metrikami a způsoby, jak si udržet dobré zákazníky ve společnosti. Pro ucelený obraz o analytickém CRM také nastiňuje jeho technickou stránku, ve které popisuje nejčastěji využívané techniky při získávání dat. Praktická část práce byla vyhotovena ve spolupráci se společností Makro Cash & Carry. Popisuje nejdůležitější změny, které byly podniknuty k přeměně Makra z produktově na zákaznicky orientovanou společnost, a podrobněji se věnuje práci kontrolorů, jež se analytickým CRM ve firmě zabývají.

Bakgrund: Majoriteten av e-handelsföretagen verksamma inom klädbranschen når inte lönsamhet vilket till viss del beror på den höga returandelen som i dagsläget ligger mellan 20-50 procent. Returandelen har ökat under de senaste åren och tros öka även i framtiden. Genom att minska sina returer med ett fåtal procent skulle e-handelsföretag kunna spara flera miljoner, dock kan kundlojaliteten gå förlorad om inte företaget möter kundens förväntningar gällande returhanteringen. Syfte: Syftet är att identifiera olika kunders returbeteenden för att förstå hur företagens returhantering kan anpassas till olika kundgrupper. Metod: I studien har författarna använt sig av en kvalitativ undersökningsmetod med ett hermeneutiskt förhållningssätt och tillämpat en explorativ samt deduktiv ansats. Resultat: Studien har identifierat två olika typer av kundgrupper med olika köp- och returbeteenden, således bör företagen segmentera kunderna utifrån dessa faktorer för att skapa en väl utförd returhantering. Företagen kan förbättra sin lönsamhet genom att kundanpassa sin returhantering eftersom en kundanpassad returhantering medför en ökad kundtillfredsställelse, ett ökat mervärde och en förbättrad kundlojalitet, vilket resulterar i en ökad lönsamhet hos företagen. / Background: The majority of the e-commerce companies in the retail industry are not profitable which is partly due to the high percentage of returned goods, which in the current situation is between 20-50 percent. In recent years the proportion of returned goods has increased and is also believed to increase in the future. By lowering the returns of goods with a few percent the e-commerce companies could save several millions, however customer loyalty can be lost unless the companies meets the customers’ expectations regarding the returns process. Purpose: The purpose is to identify the difference in customers’ returning behaviors in order to understand how companies' returns management can be adapted to different customer segmentations. Research method: The authors of the thesis have used a qualitative research method with a hermeneutic approach and applied both an explorative and a deductive approach. Results: The study has identified two different types of customer groups with different purchase and returns behaviors, thus companies should segment the customers based on these factors and the customers should be treated differently by the companies when it comes to returns management. The companies can improve their profitability by customizing their returns management because it generates greater customer satisfaction, increased added value and improved customer loyalty which results in increased profitability for the companies.

This thesis has been carried out during second semester 2010 at University College of Borås in Collaboration with Halens AB. Halens Holding AB is one of Sweden’s leading e-commerce companies. The company contains of four subsidiaries which together create Halens Holding AB. The concern includes Halens AB, Cellbes AB, Time Finans AB and New Bubbleroom Sweden AB. The main office of Halens Holding AB is located in Borås, the company has a turnover of 1.1 billion SEK and employs 300 people. Halens Holding AB has a wide range of products; fashion, home textile, furniture’s, home electronics and beauty- and health products. Halens has recently expanded their market, and now have Swedish, Norwegian, Finnish, Danish, Estonian, Latvian, Czech, Polish, Slovakian, Russian, Swiss, Slovenian and Turkish customers.The purpose of this thesis was to investigate customer requirements and demands on e-commerce. Furthermore, the intention was also to compare customers from the different subsidiaries. The purpose could be concluded with following three bullets;Identify customer demand on; product, lead-time, service and cost. Investigate differences in customer demand at two of the subsidiaries; Halens and Cellbes. Determine different consequences to the identified customer demand; purchase, non-purchase, purchase followed by return, uncollected package. A survey was made in order to find real time information about customer behavior. The objective of the survey was to understand customers’ demands of e-commerce in general. The next step was to investigate if Halens and Cellbes fulfilled those requirements. Moreover, observations were made in order to capture the customers’ use of the web-pages. These observations provided a deeper insight of the customer requirements and demands. With survey answers and observations as a base, different customer segments could be spotted. Furthermore, the task was to find problem areas or errors from the customers’ point of view in order to improve the system. Suggested areas for improvement were presented in order to get a better match between customer demand and customer experience. During this project, a clear view of the demand and requirements of Halens and Cellbes customers has been obtained. There were not major difference between the two subsidiaries, to the contrary; the results showed that there were very similar. It can be concluded that Halens and Cellbes can improve their businesses with smaller changes. Several proposals for improvement have been developed in order to better fulfill customer demand.

Master of Agribusiness / Department of Agricultural Economics / Aleksan Shanoyan / In recent years across the United States, product sales have seen a downward trend when compared to the robust sales figures posted around the 2010 time period across the major players in the product manufacturing space. Due to depressed commodity prices, large product sales have caused a lot of the dealers to shift in its prioritization of sales from a predominant large product business model, to a more diverse large product and small product strategy portfolio to stay profitable amidst economic headwinds. This study will look into ways that the Company A dealer channel could pivot their internal processes around targeting customers who are engaged in the purchase funnel of purchasing small products and how Company A could change the way the company equips their trusted dealer channel to combat competition in this segment. This study will examine new strategies that may be executed through the Company A dealer network and their subsequent retail showrooms to increase sales by focusing on key product differentiating characteristics, unique technical selling points, dealer facility positioning in high potential Metropolitan Statistical Areas, and new retail digital marketing technologies that should be leveraged throughout the sales process to improve market share. Company B is considered to be the primary rival competitor in this small product market, as this firm is one of the fiercest competitors to Company A’s quest for total product sales superiority. This study conducted a mixed method survey to ascertain what areas of marketing and promotional assistance should be prioritized by Company A, to outfit the company’s existing dealer channel with the right tools to combat Company B and other competitors in the U.S. small product market. Additionally new retail showroom technologies and strategies were based upon existing market research studies, focused on which customer’s and product characteristics were the most impactful for positively impacting small product sales in the United States.

Abstract Title: Typology of Prague Fitness Center's Clients Goals: The main target of thesis is creating specify typology of prague fitness center's clients. Methods: For thesis was used Quantitative marketing research, number of respondent was 1004. In synthetic part, there was applicated latent class analysis. Results: Results from research are presented in the analytical part of the work, verify predetermined hypotheses and are an important source for synthetic part, where we used latent class analysis for individual client's typology. Men's type are student, go-getter and resident. Women's type are managers, hunter and student. Keywords: fitness, segmentation, typology, customer, marketing, marketing research

In this thesis, the process of developing an application for segmenting customers with the use of machine learning is described. The project was carried out at a company which provides a booking platform for beauty and health services. Data about customers were analyzed and processed in order to train two classification models able to segment customers into three different customer groups. The performance of the two models, a Logistic Regression model and a Support Vector Classifier, were evaluated with different numbers of features and compared to classifications made by human experts working at the company. The results shows that the logistic regression model achieved an accuracy of 71% when classifying users into the three groups, which was more accurate than the experts manual classification. A web API where the model is provided has been developed and presented to the company. The results of the study showed that machine learning is a useful technique for performing customer segmentation based on behavioral data. Even in the case where the classes are not naturally divisible, the application provides valuable insights on user behaviour that can help the company become more data-driven.

The importance of a satisfactory logistics system is becoming increasingly apparent as a consequence of growing competition and rising customer requirements regarding, amongst others, lead times, flexibility and delivery dependability. The increasing demands reduce profit margins and increase logistics costs, accelerating the  importance of a well-functioning logistics system. A way to meet the increased customer demands is to tailor the logistics solution by segmenting customers according to their unique needs. Segmenting the customers has the potential to reduce a company's logistics costs, partly because delivery service can be bespoke to the customers' different requirements, instead of offering all customers the best possible performance. When making changes to a logistics system, it is therefore also important to take customer satisfaction into account, as reduced customer satisfaction otherwise risks leading to lost sales. A company that faces challenges with increased customer demands regarding the logistics solution in parallel with a quest for reduced logistics costs is ASSA ABLOY, a company that manufactures and sells security solutions and security systems worldwide. Based on the above situation, the research purpose of the study is to \textit{through customer segmentation develop strategy proposals to reduce the total cost of ASSA ABLOY's logistics solution, taking customer satisfaction into account}. To create an understanding of the building blocks of the research purpose: logistical change, total cost analysis, customer segments and customer satisfaction, literature was examined in the mentioned areas. To link the study to ASSA ABLOY's unique situation, multiple unstructured and semi-structured interviews were conducted with people at, among others, ASSA ABLOY with good insight into the logistics solution. Based on the interview outcomes, a list of six strategy proposals for customer segmentation was produced. Based on additional interviews as well as the study's frame of reference, the list of strategic proposals was shortened to three strategies based on implementability. The total cost of the strategy proposals and the customer satisfaction impact were analyzed using empirical data in the form of data from interviews as well as order and cost data for 2021. During the analysis, constant discussions were held with supervisors at ASSA ABLOY to ensure the analysis' connection to reality. The results of the study were summarized into three strategy proposals that through data analysis could be demonstrated to lead to potential cost savings. The customer segmentation option \textit{accepted lead time} showed the by far largest potential cost saving, followed by \textit{geographical position} which also showed great savings potential. For both alternatives, customer satisfaction was estimated to slightly be improved. The third analyzed strategy proposal, customer segmentation based on \textit{average order value} indicated the lowest cost-saving and with a slight deterioration in customer satisfaction, which is why it was considered to be the worse of the three analysed strategic alternatives.

The retail industry is continuously transforming due to digitalization, globalization, urbanization, and automatization. These factors contribute to new and more transparent retail with new customer behaviors, business models, and international competition. Literature mentions that the customers have more power to influence the retail industry today. Retailers must listen carefully to what their customers say to stay relevant and adopt data-driven strategies to meet evolving customer values. Therefore, it is essential to know customer behavior and value so that the company can target the groups of customers and thus lead their measures toward selected segments. There is a diversified growth in the tastes and likes of customers. To survive in competitive industries, a company needs to be more concerned with Customer Relationship Management. A central problem in Customer Relationship Management (CRM) is clustering customers into meaningful segments. This challenge is typical in retail, where various products are available. When it comes to segmenting customers, segmentation models provide purchasing patterns of customers, whereas clustering is the segmentation of data in several applications by grouping extensive data into groups with similar patterns. This experimental study focuses on customer segmentation, a typical customer analytics technique, and a traditional concept in marketing. The thesis aimed to perform an experiment by efficiently segmenting Swedish pharmacy retail dataset by combining segmentation models and clustering algorithms. Finally, the determined customer segments were profiled and named using a customer profiling technique. To support this aim, the research questions are “Which combination of mentioned segmentation models and clustering algorithms performs best for segmentation of a Swedish pharmacy retail company’s customers?” and “How can extracted customer segments be profiled?” This study was conducted with a Swedish retail software providing company, Extenda Retail, to gain better insight into customer behavior by analyzing experimental dataset of customer transactions of a Swedish pharmacy chain. K-means, Agglomerative and Mean-Shift clustering algorithms were paired with the segmentation models RFM, LRFM and LRFMP to generate the customer segments. This experiment showed that both K-means and Agglomerative clustering algorithms with the LRFMP model are the most suitable solution for customer segmentation for the dataset used in this study. Both combinations: the LRFMP with K-means and the LRFMP with Agglomerative clustering generated two customer segments which are then profiled as: "low-contribution customers" and "high-contributing loyal customers."