Customer Segmentation in Industrial Markets - CASE: Labelstock Company

The aim of this thesis is to study segmentation in industrial markets and develop a segmenting method proposal and criteria case study for a labelstock manufacturing company. An industrial company is facing many different customers with varying needs. Market segmentation is a process for dividing a market into smaller groups in which customers have the same or similar needs. Segmentation gives tools to the marketer to better match the product or service more closely to the needs of the target market. In this thesis a segmentation tool proposal and segmenting criteria is case studied for labelstock company’s Europe, Middle East and Africa business area customers and market. In the developed matrix tool different customers are planned to be evaluated based on customer characteristic variables. The criteria for the evaluating matrix are based on the customer’s buying organizations characteristics and buying behaviour. There are altogether 13 variables in the evaluating matrix. As an example of variables there are loyalty, size of the customer, estimated growth of the customer purchases and customer’s decision-making and buying behaviour. These characteristic variables will help to identify market segments to target and the customers belonging to those segments.

Visual customer segmentation and behavior analysis : a SOM-based approach

Ett ämne som väckt intresse både inom industrin och forskningen är hantering av kundförhållanden (CRM, eng. Customer Relationship Management), dvs. en kundorienterad affärsstrategi där företagen från att ha varit produktorienterade väljer att bli mera kundcentrerade. Numera kan kundernas beteende och aktiviteter lätt registreras och sparas med hjälp av integrerade affärssystem (ERP, eng. Enterprise Resource Planning) och datalager (DW, eng. Data Warehousing). Kunder med olika preferenser och köpbeteende skapar sin egen ”signatur” i synnerhet via användningen av kundkort, vilket möjliggör mångsidig modellering av kundernas köpbeteende. För att få en översikt av kundernas köpbeteende och deras lönsamhet, används ofta kundsegmentering som en metod för att indela kunderna i grupper utgående från deras likheter. De mest använda metoderna för kundsegmentering är analytiska modeller konstruerade för en viss tidsperiod. Dessa modeller beaktar inte att kundernas beteende kan förändras med tiden. I föreliggande avhandling skapas en holistisk översikt av kundernas karaktär och köpbeteende som utöver de konventionella segmenteringsmodellerna även beaktar dynamiken i köpbeteendet. Dynamiken i en kundsegmenteringsmodell innefattar förändringar i segmentens struktur och innehåll, samt förändringen av individuella kunders tillhörighet i ett segment (s.k migrationsanalyser). Vardera förändringen modelleras, analyseras och exemplifieras med visuella datautvinningstekniker, främst med självorganiserande kartor (SOM, eng. Self-Organizing Maps) och självorganiserande tidskartor (SOTM), en vidareutveckling av SOM. Visualiseringen anteciperas underlätta tolkningen av identifierade mönster och göra processen med kunskapsöverföring mellan den som gör analysen och beslutsfattaren smidigare. Asiakkuudenhallinta (CRM) eli organisaation muuttaminen tuotepainotteisesta asiakaskeskeiseksi on herättänyt mielenkiintoa niin yliopisto- kuin yritysmaailmassakin. Asiakkaiden käyttäytymistä ja toimintaa pystytään nykyään helposti tallentamaan ja varastoimaan toiminnanohjausjärjestelmien ja tietovarastojen avulla; asiakkaat jättävät jatkuvasti piirteistään ja ostokäyttäytymisestään kertovia tietojälkiä, joita voidaan analysoida. On tavallista, että asiakkaat poikkeavat toisistaan eri tavoin, ja heidän mieltymyksensä kuten myös ostokäyttäytymisensä saattavat olla hyvinkin erilaisia. Asiakaskäyttäytymisen monimuotoisuuteen ja tuottavuuteen paneuduttaessa käytetäänkin laajalti asiakassegmentointia eli asiakkaiden jakamista ryhmiin samankaltaisuuden perusteella. Perinteiset asiakassegmentoinnin ratkaisut ovat usein yksittäisiä analyyttisia malleja, jotka on tehty tietyn aikajakson perusteella. Tämän vuoksi ne monesti jättävät huomioimatta sen, että asiakkaiden käyttäytyminen saattaa ajan kuluessa muuttua. Tässä väitöskirjassa pyritäänkin tarjoamaan holistinen kuva asiakkaiden ominaisuuksista ja ostokäyttäytymisestä tarkastelemalla kahta muutosvoimaa tiettyyn aikarajaukseen perustuvien perinteisten segmentointimallien lisäksi. Nämä kaksi asiakassegmentointimallin dynamiikkaa ovat muutokset segmenttien rakenteessa ja muutokset yksittäisten asiakkaiden kuulumisessa ryhmään. Ensimmäistä dynamiikkaa lähestytään ajallisen asiakassegmentoinnin avulla, jossa visualisoidaan ajan kuluessa tapahtuvat muutokset segmenttien rakenteissa ja profiileissa. Toista dynamiikkaa taas lähestytään käyttäen nk. segmenttisiirtymien analyysia, jossa visuaalisin keinoin tunnistetaan samantyyppisesti segmentistä toiseen vaihtavat asiakkaat. Visualisoinnin tehtävänä on tukea havaittujen kaavojen tulkitsemista sekä helpottaa tiedonsiirtoa analysoijan ja päättäjien välillä. Visuaalisia tiedonlouhintamenetelmiä, kuten itseorganisoivia karttoja ja niiden laajennuksia, käytetään osoittamaan näiden menetelmien hyödyllisyys sekä asiakkuudenhallinnassa yleisesti että erityisesti asiakassegmentoinnissa.

Supplier Segmentation for Nordic Petrochemical Industry

Objective of this thesis was to map possibilities for systematic supplier management in field of chemical process industry. Through this study it was aimed to develop a tool for supplier management that could be integrated with operations in business unit. With developed tool suppliers should be able to be segmented based on their willingness and capability, and segmentation could be applied in purchasing decisions. In this thesis there was made a survey of methods that are recognized in literature to manage and allocate suppliers. This thesis recognizes segmentation as a method to group and select suppliers in procurement. Based on literature, a proposal for segmentation framework and evaluation criteria factors will be constituted. Based on theoretical proposal, in an expertise workshop a final segmentation framework was constituted, which covers segments with descriptions and evaluation part. Evaluation part includes an evaluation framework which helps to score suppliers with selected factors and leads to total grades in willingness and capability. These total grades will be the coordinates and they determine the segment where the supplier under evaluation belongs. In this thesis segments definitions, objectives, and road maps will be described.

Effects of obtained benefits on willingness to pay and word-of-mouth behavior in newspaper industry

The purpose of this master’s thesis was to investigate the effects which benefits obtained from reading a newspaper and using its website have on behavioral outcomes such as word-of-mouth behavior and willingness to pay. Several other antecedents of willingness to pay have been used as the control variables. However, their interrelations haven’t been hypothesized. The empirical part focused on a case company – Finnish regional newspaper. Empirical research has been conducted using a quantitative method and data was collected via online survey placed on newspaper’s website during 2010. 1001 responses have been collected. The results showed that benefits obtained both from traditional printed newspaper and from online one have positive effects on the word-of-mouth about this newspaper and its website. However, it has been revealed that benefits obtained from reading the newspaper don’t have effect on the willingness to pay for this newspaper. Additionally, only interpersonal and convenience benefits obtained from using the newspaper’s website influence on the willingness to pay for it. Finally, willingness to pay for the bundle of printed newspaper and its website access is affected positively only by the information/learning benefits obtained from reading the newspaper and by the interpersonal benefits obtained from using the newspaper’s website.

Segmentation of overlapping convex objects

This thesis presents a framework for segmentation of clustered overlapping convex objects. The proposed approach is based on a three-step framework in which the tasks of seed point extraction, contour evidence extraction, and contour estimation are addressed. The state-of-art techniques for each step were studied and evaluated using synthetic and real microscopic image data. According to obtained evaluation results, a method combining the best performers in each step was presented. In the proposed method, Fast Radial Symmetry transform, edge-to-marker association algorithm and ellipse fitting are employed for seed point extraction, contour evidence extraction and contour estimation respectively. Using synthetic and real image data, the proposed method was evaluated and compared with two competing methods and the results showed a promising improvement over the competing methods, with high segmentation and size distribution estimation accuracy.

Supplier segmentation and development in project business

The purpose of this study was to expand the applicability of supplier segmentation and development approaches to the project-driven construction industry. These practices are less exploited and not well documented in this operational environment compared to the process-centric manufacturing industry. At first, portfolio models to supply base segmentation and various supplier development efforts were investigated in literature review. A step-wise framework was structured for the empirical research. The empirical study employed multiple research methods in three case studies in a large Finnish construction company. The first study categorized the construction item classes into the purchasing portfolio and positioned suppliers to the power matrix by investigating buyer-supplier relations. Using statistical tests, the study also identified factors that affect suppliers’ performance. The final case study identified improvement areas of the interface between a main contractor and one if its largest suppliers. The final results indicate that only by assessing the supply base in a holistic manner and the power circumstances in it, buyers comprehend how to best establish appropriate supplier development strategies in the project environment.

Statistical segmentation methods and color variance analysis of retinal images

In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Novel word learning ability in chronic post-stroke aphasia : variability and modality effects

Novel word learning has been rarely studied in people with aphasia (PWA), although it can provide a relatively pure measure of their learning potential, and thereby contribute to the development of effective aphasia treatment methods. The main aim of the present thesis was to explore the capacity of PWA for associative learning of word–referent pairings and cognitive-linguistic factors related to it. More specifically, the thesis examined learning and long-term maintenance of the learned pairings, the role of lexical-semantic abilities in learning as well as acquisition of phonological versus semantic information in associative novel word learning. Furthermore, the effect of modality on associative novel word learning and the neural underpinnings of successful learning were explored. The learning experiments utilized the Ancient Farming Equipment (AFE) paradigm that employs drawings of unfamiliar referents and their unfamiliar names. Case studies of Finnishand English-speaking people with chronic aphasia (n = 6) were conducted in the investigation. The learning results of PWA were compared to those of healthy control participants, and active production of the novel words and their semantic definitions was used as learning outcome measures. PWA learned novel word–novel referent pairings, but the variation between individuals was very wide, from more modest outcomes (Studies I–II) up to levels on a par with healthy individuals (Studies III–IV). In incidental learning of semantic definitions, none of the PWA reached the performance level of the healthy control participants. Some PWA maintained part of the learning outcomes up to months post-training, and one individual showed full maintenance of the novel words at six months post-training (Study IV). Intact lexical-semantic processing skills promoted learning in PWA (Studies I–II) but poor phonological short-term memory capacities did not rule out novel word learning. In two PWA with successful learning and long-term maintenance of novel word–novel referent pairings, learning relied on orthographic input while auditory input led to significantly inferior learning outcomes (Studies III–IV). In one of these individuals, this previously undetected modalityspecific learning ability was successfully translated into training with familiar but inaccessible everyday words (Study IV). Functional magnetic resonance imaging revealed that this individual had a disconnected dorsal speech processing pathway in the left hemisphere, but a right-hemispheric neural network mediated successful novel word learning via reading. Finally, the results of Study III suggested that the cognitive-linguistic profile may not always predict the optimal learning channel for an individual with aphasia. Small-scale learning probes seem therefore useful in revealing functional learning channels in post-stroke aphasia.

Cognitive performance of young and elderly subjects on the free word recall memory test: effect of presentation order on recall order

The influence of aging on memory has been extensively studied, but the importance of short-term memory and recall sequence has not. The objective of the current study was to examine the recall order of words presented on lists and to determine if age affects recall sequence. Physically and psychologically healthy male subjects were divided into two groups according to age, i.e., 23 young subjects (20 to 30 years) and 50 elderly subjects (60 to 70 years) submitted to the Wechsler Adult Intelligence Scale-Revised and the free word recall test. The order of word presentation significantly affected the 3rd and 4th words recalled (P < 0.01; F = 14.6). In addition, there was interaction between the presentation order and the type of list presented (P < 0.05; F = 9.7). Also, both groups recalled the last words presented from each list (words 13-15) significantly more times 3rd and 4th than words presented in all remaining positions (P < 0.01). The order of word presentation also significantly affected the 5th and 6th words recalled (P = 0.05; F = 7.5) and there was a significant interaction between the order of presentation and the type of list presented (P < 0.01; F = 20.8). The more developed the cognitive functions, resulting mainly from formal education, the greater the cognitive reserve, helping to minimize the effects of aging on the long-term memory (episodic declarative).

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.