Application of artificial neural network in market segmentation: A review on recent trends

Despite the significance of Artificial Neural Network (ANN) algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000-2010 and proposed a classification scheme for the articles. One thousands (1000) articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.Comment: 24 pages, 7 figures,3 Table

Production of semi real time media-GIS contents using MODIS imagery

[Abstract]: Delivering environmental disaster information, swiftly, attractively, meaningfully, and accurately, to public is becoming a competitive task among spatial data visualizing experts. Basically, the data visualization process has to follow basics of spatial data visualization to maintain the academic quality and the spatial accuracy of the content. Here, “Media-GIS”, can be promoted as a one of the latest sub-forms of GIS, which targets mass media. Under Media-GIS, “Present” or the fist component of three roles of data visualization takes the major workload compare to other two, “Analysis” and “Explore”. When present contents, optimizing the main graphical variables like, size, value, texture, hue, orientation, and shape, is vital with regard to the target market (age group, social group) and the medium (print, TV, WEB, mobile). This study emphasizes on application of freely available MODIS true colour images to produce near real time contents on environmental disasters, while minimizing the production cost. With the brake of first news of a significant environmental disaster, relevant MODIS (250m) images can be extracted in GeoTIFF and KLM (Keyhole Markup Language) formats from MODIS website. This original KML file can be overlayed on Google Earth, to collect more spatial information of the disaster site. Then, in ArcGIS environment, GeoTIFF file can be transferred into Photoshop for production of the graphics of the target spot. This media-friendly Photoshop file can be used as an independent content without geo-references or imported into ArcGIS to convert into KLM format, which has geo-references. The KLM file, which is graphically enhanced content with extra information on environmental disaster, can be used in TV and WEB through Google Earth. Also, sub productions can be directed into print and mobile contents. If the data processing can be automated, system will be able to produce media contents in a faster manner. A case study on the recent undersea oil spill occurred in Gulf of Mexico included in the report to highlight main aspects discussed in the methodology

Creative User-Centered Visualization Design for Energy Analysts and Modelers

We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open – enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design

Datamining for Web-Enabled Electronic Business Applications

Web-Enabled Electronic Business is generating massive amount of data on customer purchases, browsing patterns, usage times and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for web-enabled electronic-business

SEGSys: A mapping system for segmentation analysis in energy

Customer segmentation analysis can give valuable insights into the energy efficiency of residential buildings. This paper presents a mapping system, SEGSys that enables segmentation analysis at the individual and the neighborhood levels. SEGSys supports the online and offline classification of customers based on their daily consumption patterns and consumption intensity. It also supports the segmentation analysis according to the social characteristics of customers of individual households or neighborhoods, as well as spatial geometries. SEGSys uses a three-layer architecture to model the segmentation system, including the data layer, the service layer, and the presentation layer. The data layer models data into a star schema within a data warehouse, the service layer provides data service through a RESTful interface, and the presentation layer interacts with users through a visual map. This paper showcases the system on the segmentation analysis using an electricity consumption data set and validates the effectiveness of the system

Visual decisions in the analysis of customers online shopping behavior

The analysis of the online customer shopping behavior is an important task nowadays, which allows maximizing the efficiency of advertising campaigns and increasing the return of investment for advertisers. The analysis results of online customer shopping behavior are usually reviewed and understood by a non-technical person; therefore the results must be displayed in the easiest possible way. The online shopping data is multidimensional and consists of both numerical and categorical data. In this paper, an approach has been proposed for the visual analysis of the online shopping data and their relevance. It integrates several multidimensional data visualization methods of different nature. The results of the visual analysis of numerical data are combined with the categorical data values. Based on the visualization results, the decisions on the advertising campaign could be taken in order to increase the return of investment and attract more customers to buy in the online e-shop

Building a Customer Value Proposition for a Game Analytics Company

This thesis was carried out for a game analytics company to improve their customer value proposition by identifying the needs of different user segments of their service and finding out how the service can provide value to fulfill these needs. The first objective of the thesis was to identify the needs of the user segments inside the game developer companies; designers, analysts and management. The second objective was to find out compatibility between the service and user segments’ needs. Third objective was to visualize the different user segments’ needs, relevance of each need and the compatibility between the case company’s service and customer needs. The research was carried out through individual interviews and a workshop. The core of the knowledge base for this thesis consists of theories about segmentation, targeting, positioning (STP) and value propositions. As a support for the core theories, more specific theories about the context were studied. The outputs for this thesis were Value Proposition Canvases and tables for each user segment visualizing 1) what their needs inside a typical game development company are, 2) how the case company’s service fulfills those needs and 3) which of them are important to tackle based on their relevancies. Canvases and the tables acted as a proposal which the case company can use in support for sales as they give clearly visualized points to be used as sales hooks to point out the value in the service for different segments. It describes what gain creators and pain relievers should be emphasized when selling the service to specific segments. Proposal can also be used to support the development of the service to meet the customers’ needs even better.Insinöörityö tehtiin pelianalytiikkayritykselle parantamaan sen arvolupausta asiakkailleen. Työssä identifioitiin eri asiakassegmenttien tarpeet pelianalytiikkapalveluja kohtaan sekä selvitettiin, kuinka juuri tämä palvelu voi tarjota arvoa eri asiakkaille. Insinöörityön ensimmäinen tavoite oli kartoittaa eri käyttäjäsegmenttien tarpeet pelinkehittäjäyritysten sisällä. Näihin sisäisiin segmentteihin kuuluivat pelisuunnittelijat, analyytikot sekä johtotason henkilöt. Toinen tavoite oli löytää ja kartoittaa, miten nämä tarpeet sekä kohdeyrityksen palvelun tuoma arvo kohtaavat. Kolmantena tavoitteena oli visualisoida eri käyttäjäsegmenttien tarpeet tärkeysjärjestyksessä, sekä se, miten kohdeyrityksen palvelu kohtaa nämä tarpeet. Tutkimus toteutettiin tekemällä yksittäisiä haastatteluita ja työpaja kohdeyrityksen johdon kanssa. Insinöörityön teoriapohjan ydin muodostui STP-teoriasta (segmentation, targeting, positioning) sekä arvolupausteoriasta. Näitä teorioita tukemaan tutkittiin myös tähän kontekstiin liittyvää teoriaa. Insinöörityön lopputuotoksena olivat Value Proposition Canvas sekä taulukko jokaiselle segmentille, jotka visualisoivat 1) mitä tyypillisessä pelinkehitysyrityksessä olevien käyttäjäsegmenttien tarpeet ovat, 2) miten hyvin kohdeyrityksen palvelu täyttää nämä tarpeet sekä 3) mitkä tarpeista ovat tärkeimpiä taklata. Kohdeyritys voi hyödyntää lopputuotoksessa visualisoituja faktoja myynnin tukena. Lopputuotoksesta voidaan nähdä, mitä eri palvelun arvoa tuottavia asioita on hyvä painottaa, kun palvelua myydään eri segmenteille. Lopputuotosta voidaan myös käyttää kehitettäessä palvelua vastaamaan paremmin asiakkaan tarpeita

Market Segmentation Analysis and Visualization Using K-Mode Clustering Algorithm for E-Commerce Business

Today all business organizations are adopting data driven strategies to generate more revenue out of their business. Growing startups are investing a lot of money in data economy to maximize profits of business organizations by developing intelligent tools backed by machine learning and artificial intelligence. The nature of BI tool depends on factor like business goals, size, model, technology etc. In this paper architecture of business intelligence tool and decision process has been discussed with a focus on market segmentation, based on user behavior analysis using k-mode clustering algorithm and user geographical distributions. The proposed toolkit also incorporates interactive visualizations and maps