The importance of customer's value expectations in customer acquisition

Pro gradu –tutkielman tavoitteena on tutkia asiakasarvoa ja sitä, miten asiakasarvoa voidaan käyttää hyväksi uusasiakashankinnassa. Tällä hetkellä kirjallisuudessa on pinnalla muutos tuotekeskeisyydestä asiakaskeskeiseen näkökulmaan, joka tunnistaa asiakasarvon tärkeyden bisnes suhteissa. Tämä tutkimus osallistuu kyseiseen keskusteluun muodostamalla tavan mitata asiakasarvoa, ja peilaamalla saavutettuja tuloksia uusasiakashankinta prosessiin. Empiirinen tutkimus on toteutettu kahdessa osassa: kvalitatiivisessa sekä kvantitatiivisessa. Ensimmäisessä osassa haastateltiin kahdeksaa potentiaalista asiakasta, minkä jälkeen saadut tulokset vietiin suurempaan skaalaan toteuttamalla kysely suurelle joukolle potentiaalisia asiakkaita. Lopulliset tulokset osoittavat, että asiakasarvon käyttäminen hyväksi uusasiakashankinnassa on erittäin tehokas ja käyttökelpoinen metodi. Asiakasarvoon perustuvat asiakassegmentit mahdollistavat oikeiden arvojen kommunikoinnin oikeille segmenteille. Se antaa yritykselle myös mahdollisuuden valita houkuttelevimmat asiakasryhmät ja vahvistaa asiakaskantaansa.

Myyjien tietämyksen jakaminen organisaatiolle osana myyntiprosessia

Diplomityön tavoitteena on tutkia myyjien tietämyksen jakamista ja sen yhteyttä myyntiprosessiin. Tutkimus on toteutettu systemaattisena kirjallisuuskatsauksena. Työssä pyritään löytämään kirjallisuuden pohjalta yhteydet myyntiprosessin vaiheiden ja vaatimusten sekä myyjien tietämyksen jakamisen väliltä. Teoreettisena taustana esitellään myyntiprosessin kuvauksia, vaiheita ja haasteita yleisellä tasolla, jotta löydetään tehokkaan prosessin edellyttämät tekijät. Lisäksi tutkitaan tietämyksen vaikutusta myyntitehokkuuteen ja etsitään tietämyksen jakamiseen ja hyödyntämiseen vaikuttavia tekijöitä yleisesti ja myyntityöhön liittyen. Työn soveltavassa osuudessa tarkasteltiin tietämyksen kannalta tärkeitä myyntiprosessin vaiheita: asiakasvalinta, esivalmistelu, presentaatio ja neuvottelu sekä kaupan päättäminen. Jokaisessa vaiheessa todettiin olevan hyötyä myyjien tietämyksen jakamisesta. Läpikäydyn aineiston pohjalta tehtiin kaksi keskeistä huomiota. Ensinnäkin myyjien tietämyksen jakaminen on johdettavissa suoraan osaksi myyntiprosessia ja tietämyksellä on merkittävä rooli myyntityössä. Toiseksi myyntiprosessi ja myyjien tietämyksen jakaminen edellyttävät monia samoja asioita. Asiakas ja asiakkaan tarpeet ovat molemmissa keskiössä ja molempiin linkittyy henkilökuntaa yli osastorajojen. Tietoa on olemassa paljon joten on tärkeää suunnata resurssit oleelliseen. Tietotekniikan kehitys auttaa myyntitoiminnan jäsentämisessä ja tietämyksen jakamisessa, mutta on syytä pitää mielessä, että tietotekniikan rooli on tukitoiminto. Molemmat ovat turhia jos sovittuja pelisääntöjä ei noudateta. Lisäksi onnistunut implementointi edellyttää johdon sitoutumista ja riittävän laajaa henkilökunnan osallistamista.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Impact of online channel use on customer revenues and costs to serve:considering product portfolios and self-selection

Developing a strategy for online channels requires knowledge of the effects of customers' online use on their revenue and cost to serve, which ultimately influence customer profitability. The authors theoretically discuss and empirically examine these effects. An empirical study of retail banking customers reveals that online use improves customer profitability by increasing customer revenue and decreasing cost to serve. Moreover, the revenue effects of online use are substantially larger than the cost-to-serve effects, although the effects of online use on customer revenue and cost to serve vary by product portfolio. Self-selection effects also emerge and can be even greater than online use effects. Ignoring self-selection effects thus can lead to poor managerial decision-making.

Appraisal ratings, halo, and selection: A study using sales staff

Supervisor ratings are useful criteria for the validation of selection instruments but maybe limited because of the presence of rating errors, such as halo. This study set out to show that supervisor ratings which are high in halo remain successful criteria in selection. Following a thorough job analysis, a customer service questionnaire was designed to assess the potential of retail sales staff on three orthogonal subscales labelled Dealing with people, Emotions and energy, and Solitary style. These subscales were uncorrelated with supervisor ratings made about 8 weeks later. However, the supervisor ratings were correlated with an overall scale derived from the three scales of the customer service questionnaire. These results support the view that supervisor ratings generally consist of global impressions and suggest that these global impressions are useful measures of overall performances. This field study confirms laboratory results that halo does not necessarily reduce rating accuracy.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

Implementação de um sistema de customer relationship management na broaden information solutions

Dissertação de mestrado em Sistemas de Informação

Assessment of Customer Needs in Fine Coal Dewatering

Työn tavoitteena on kartoittaa ja arvioida asiakastarpeita hienojakoisen hiilen ja nesteen erotuksessa. Aluksi työssä kuvataan hiiliteollisuutta, jonka jälkeen syvennytäänhiilen ja nesteen erotukseen. Tämän jälkeen keskitytään asiakastarpeiden kartoittamiseen. Jo olemassaolevan tiedon keräämiseen käytetään haastatteluja ja kysymyslomakkeita. Saatyn AHP-mallia hyödynnetään asiakastarpeiden arvioinnissa. Yksi suurimmista haasteista puhtaan hiiliteknologian käytössä on kustannustehokas nesteen ja hienojakoisen hiilen erotus, joka on tärkeää rahtauskustannusten minimoinnin, laatuvaatimusten täyttämisen ja prosessiveden kierrättämisen kannalta. Tekniset ominaisuudet ja kustannukset ovat tärkeimmät ominaisuudet hiilen ja veden suodatinratkaisussa asiantuntijoiden mukaan. Asiakkaan mukaan laatu, tekniset ominaisuudet ja tukipalvelut ovat tärkeitä.Sekä asiakkaan että asiantuntijoiden mielestä korkea yksikkökapasiteetti, matala lopputuotteen kosteus ja luotettavuus ovat tärkeimmät tekniset ominaisuudet. Investointikustannukset ovat noin kolme kertaa tärkeämpiä kuin käyttökustannukset. Asiakkaan mukaan laitetoimittajan ominaisuudet ovat tärkeämpiä kuin teknologiset ominaisuudet.

Supply chain integration: studies on linking customer responsiveness and operational efficiency in logistics policy planning

Abstract The research problem in the thesis deals with improving the responsiveness and efficiency of logistics service processes between a supplier and its customers. The improvement can be sought by customizing the services and increasing the coordination of activities between the different parties in the supply chain. It is argued that to achieve coordination the parties have to have connections on several levels. In the framework employed in this research, three contexts are conceptualized at which the linkages can be planned: 1) the service policy context, 2) the process coordination context, and 3) the relationship management context. The service policy context consists of the planning methods by which a supplier analyzes its customers' logistics requirements and matches them with its own operational environment and efficiency requirements. The main conclusion related to the service policy context is that it is important to have a balanced selection of both customer-related and supplier-related factors in the analysis. This way, while the operational efficiency is planned a sufficient level of service for the most important customers is assured. This kind of policy planning involves taking multiple variables into the analysis, and there is a need to develop better tools for this purpose. Some new approaches to deal with this are presented in the thesis.The process coordination context and the relationship management context deal with the issues of how the implementation of the planned service policies can be facilitated in an inter-organizational environment. Process coordination includes typically such mechanisms as control rules, standard procedures and programs, but inhighly demanding circumstances more integrative coordination mechanisms may be necessary. In the thesis the coordination problems in third-party logistics relationship are used as an example of such an environment. Relationship management deals with issues of how separate companies organize their relationships to improve the coordination of their common processes. The main implication related to logistics planning is that by integrating further at the relationship level, companies can facilitate the use of the most efficient coordination mechanisms and thereby improve the implementation of the selected logistics service policies. In the thesis, a case of a logistics outsourcing relationship is used to demonstrate the need to address the relationship issues between the service provider andthe service buyer before the outsourcing can be done.The dissertation consists of eight research articles and a summarizing report. The principal emphasis in the articles is on the service policy planning context, which is the main theme of six articles. Coordination and relationship issues are specifically addressed in two of the papers.

Modelling requirements of supplier selection for benchmarking service provision

Supplier selection has a great impact on supply chain management. The quality of supplier selection also affects profitability of organisations which work in the supply chain. As suppliers can provide variety of services and customers demand higher quality of service provision, the organisation is facing challenges for making the right choice of supplier for the right needs. The existing methods for supplier selection, such as data envelopment analysis (DEA) and analytical hierarchy process (AHP) can automatically perform selection of competitive suppliers and further decide winning supplier(s). However, these methods are not capable of determining the right selection criteria which should be derived from the business strategy. An ontology model described in this paper integrates the strengths of DEA and AHP with new mechanisms which ensure the right supplier to be selected by the right criteria for the right customer's needs.

Consciousness, Action Selection, Meaning and Phenomenic Anticipation

Phenomenal states are generally considered the ultimate sources of intrinsic motivation for autonomous biological agents. In this article, we will address the issue of the necessity of exploiting these states for the design and implementation of robust goal-directed artificial systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent "understands" the informational flows entering the agent and its very own action possibilities. This abstract model of consciousness and understanding will be based in the analysis and evaluation of phenomenal states along potential future trajectories in the state space of the agents. This implies that a potential strategy to follow in order to build autonomous but still customer-useful systems is to embed them with the particular, ad hoc phenomenality that captures the system-external requirements that define the system usefulness from a customer-based, requirements-strict engineering viewpoint.

Customer value based entry decision in International markets the concept of International Added Customer Equity

Market entry decisions are some of a firm's most important long-term strategic choices. Still, the international marketing literature has not yet fully incorporated the idea of relationship marketing in general, and the customer value concept in particular, as a basis for market entry decisions. This article presents some conceptual ideas about a customer value based market selection model. The metric International Added Customer Equity (IACE), a straightforward decision criterion derived from the customer equity concept is presented as an additional decision criterion for export market selection and ultimately market entry.

Managing customer relationship management projects:the case of a large French telecommunication company

Customer relationship management (CRM) implementation projects reflect a growing conceptual shift from the traditional engineering view of projects. Such projects are complex and risky because they call for both organisational and technological changes. This requires effective project management across various phases of the implementation process. However, few empirical researches have dealt with these project management issues. The aim of this research is to investigate how a “project team” manages CRM implementation projects successfully, across the different phases of the implementation process. We conducted an in-depth case study of the “Firm-Clients Branch” of a large telecommunications company in France. The findings show that, to manage CRM implementation projects successfully, an integrated and balanced approach is required. This involves appropriate system selection, effective process re-engineering and further development of organizational structures. We highlight the need for a “technochange approach” to achieve successful organisational transition and effective CRM implementation. The study reveals that the project team plays a central role throughout the implementation phases. Furthermore the effectiveness of technochange depends on project team performance, technology efficiency and close coordination with stakeholders.

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.