Targeted Marketing and Market Share Analysis on POS Payment Data Using DW and OLAP
01 Jan 2019-pp 189-199
TL;DR: This paper proposes to process these huge transactional data using ETL process and thereafter construction of a data warehouse (DW) which enables the POS provider to employ certain analytical processing for business gain.
Abstract: Point of Sales (POS) terminals are provided by the banking and financial institutes to perform cashless transactions. Over the time due to different conveniences, use of digital money and online card transactions increased many folds. After each successful payment transaction at the POS terminals, a transaction log is sent to the POS terminal provider with payment-related financial data such as date and time, amount, authorization service provider, cardholder’s bank, merchant identifier, store identifier, terminal number, etc. These data are useful for analytical processing which are useful for business. This paper proposes to process these huge transactional data using ETL process and thereafter construction of a data warehouse (DW) which enables the POS provider to employ certain analytical processing for business gain such as knowing own market share as well as position in market with respect to card payments, geographic location-wise business profiling, own as well as competitor’s customer segmentation based on monthly card usage, monthly amount spent, etc.
Citations
More filters
TL;DR: The authors propose a novel hybrid multi-attribute data mining approach for rule extraction and the service operations benchmarking approach by combining data mining tools with a multilayer decision-making approach that has been implemented in a large-scale problem in the financial services industry.
Abstract: PurposeCustomer differences and similarities play a crucial role in service operations, and service industries need to develop various strategies for different customer types. This study aims to understand the behavioral pattern of customers in the banking industry by proposing a hybrid data mining approach with rule extraction and service operation benchmarking.Design/methodology/approachThe authors analyze customer data to identify the best customers using a modified recency, frequency and monetary (RFM) model and K-means clustering. The number of clusters is determined with a two-step K-means quality analysis based on the Silhouette, Davies–Bouldin and Calinski–Harabasz indices and the evaluation based on distance from average solution (EDAS). The best–worst method (BWM) and the total area based on orthogonal vectors (TAOV) are used next to sort the clusters. Finally, the associative rules and the Apriori algorithm are used to derive the customers' behavior patterns.FindingsAs a result of implementing the proposed approach in the financial service industry, customers were segmented and ranked into six clusters by analyzing 20,000 records. Furthermore, frequent customer financial behavior patterns were recognized based on demographic characteristics and financial transactions of customers. Thus, customer types were classified as highly loyal, loyal, high-interacting, low-interacting and missing customers. Eventually, appropriate strategies for interacting with each customer type were proposed.Originality/valueThe authors propose a novel hybrid multi-attribute data mining approach for rule extraction and the service operations benchmarking approach by combining data mining tools with a multilayer decision-making approach. The proposed hybrid approach has been implemented in a large-scale problem in the financial services industry.
7 citations
13 Mar 2019
TL;DR: This paper proposes an innovative delivery model to serve the remote areas by opening edge-hubs at selected places and employing local daily commuters for last mile delivery by using telecom call detail record (CDR) location data as an alternate way of identifying the hubs in real time with much less cost and time.
Abstract: A very important issue with the e-commerce delivery service in most of the emerging economies including India is the last mile connectivity. Delivering products, booked online to the remote tier-2 and tier-3 cities remained “costly”. It is observed from firsthand experience with some well-known e-commerce brands in India that their delivery service partners tend to cancel orders that are far away from their tier-2 logistics hubs with the reason shown as “address out of delivery range”. Due to low order density in the far flanges of tier-2 and tier-3 cities arranging vehicles and delivery personnel become costly. In this paper, we propose an innovative delivery model to serve the remote areas by opening edge-hubs at selected places and employing local daily commuters for last mile delivery. Identifying the edge-hubs for opening distribution centers is a costly business if done using traditional field surveys. Here we propose the use of telecom call detail record (CDR) location data as an alternate way of identifying the hubs in real time with much less cost and time.
2 citations
Cites background from "Targeted Marketing and Market Share..."
...A typical work-flow at an Point-of-Sale counter in retail stores are discussed in [9]....
[...]
TL;DR: In this article, the authors analyse outstanding payment cards in India by examining the number of cards in operation and the value of transaction in the past decade, and find that credit card penetration has increased by threefold with average growth of 15% YoY and debit cards increased by more than threefold, while asymmetry between debit cards holders and credit card holders exists in India indicating credit card is still a niche product.
Abstract: A paradigm shift in the modus operandi of commerce across the globe has been significantly influenced by the payment card industry with brisk strides in digital technology. The blooming payment card industry has escorted the prosperity in economic growth of most of the countries. Besides, there exists a divergent level in subsuming card payment by different countries due to distinct social, economic and cultural background. In India, excessive use cash payments are due to offbeat business models and varied distinction in literacy levels. This paper aims to analyse outstanding payment cards in India by examining the number of cards in operation and the value of transaction in the past decade. Data from RBI source is collected to analyse for a period of eight years (2011-2019). The research finds that credit card penetration has increased by threefold with average growth of 15% YoY and debit cards increased by more than threefold with average growth of 19% YoY during the period of analysis. Yet, asymmetry between debit cards holders and credit card holders exists in India indicating credit card is still niche product. This provides platform for the payment card industry to unleash the potential to tap market in India.
TL;DR: In this article, the authors analyse outstanding payment cards in India by examining the number of cards in operation and the value of transaction in the past decade, and find that credit card penetration has increased by threefold with average growth of 15% YoY and debit cards increased by more than threefold, while asymmetry between debit cards holders and credit card holders exists in India indicating credit card is still a niche product.
Abstract: A paradigm shift in the modus operandi of commerce across the globe has been significantly influenced by the payment card industry with brisk strides in digital technology. The blooming payment card industry has escorted the prosperity in economic growth of most of the countries. Besides, there exists a divergent level in subsuming card payment by different countries due to distinct social, economic and cultural background. In India, excessive use cash payments are due to offbeat business models and varied distinction in literacy levels. This paper aims to analyse outstanding payment cards in India by examining the number of cards in operation and the value of transaction in the past decade. Data from RBI source is collected to analyse for a period of eight years (2011–2019). The research finds that credit card penetration has increased by threefold with average growth of 15% YoY and debit cards increased by more than threefold with average growth of 19% YoY during the period of analysis. Yet, asymmetry between debit cards holders and credit card holders exists in India indicating credit card is still niche product. This provides platform for the payment card industry to unleash the potential to tap market in India.
References
More filters
TL;DR: The authors reviewed major marketing strategy alternatives that are available to planners and merchandisers of products in an environment characterized by imperfect competition and found that diversity or heterogeneity had become the rule rather than the exception.
Abstract: URING the decade of the 1930's, the work of Robinson and Chamberlin resulted in a revitalization of economic theory. While classical and neoclassical theory provided a useful framework for economic analysis, the theories of perfect competition and pure monopoly had become inadequate as explanations of the contemporary business scene. The theory of perfect competition assumes homogeneity among the components of both the demand and supply sides of the market, but diversity or heterogeneity had come to be the rule rather than the exception. This analysis reviews major marketing strategy alternatives that are available to planners and merchandisers of products in an environment characterized by imperfect competition.
1,667 citations
Book•
15 May 2011TL;DR: A Dictionary of Marketing as discussed by the authors is an accessible and wide-ranging A-Z, providing over 2,600 entries on topics spanning terms for traditional marketing techniques (from strategy, positioning, segmentation, and branding, to all aspects of marketing planning, research, and analysis), as well as leading marketing theories and concepts.
Abstract: A Dictionary of Marketing is an accessible and wide-ranging A-Z, providing over 2,600 entries on topics spanning terms for traditional marketing techniques (from strategy, positioning, segmentation, and branding, to all aspects of marketing planning, research, and analysis), as well as leading marketing theories and concepts. Both classic and modern marketing techniques are covered. Entries reflect modern changes in marketing practice, including the use of digital and multi media, the impact of the world wide web on advertising, and the increased influence of social media, search engine optimization, and global marketing. Also included is a time line of the development of marketing as a discipline and the key events that impacted the development, as well as over 100 relevant web links, accessed and updated via a companion website. In addition, the main appendix provides greater depth on the subject, including advertising and brand case studies with a strong international focus. These are arranged thematically, e.g. automobile industry, food and drink, luxury goods, and focus on iconic brands, marketing campaigns, and slogans of the 20th century that have permeated our collective consciousness, exploring how the ideas defined in the main text of the book have been utilised successfully in practice across the globe. This dictionary is an indispensable resource for students of marketing and related disciplines, as well as a practical guide for professional practitioners.
34 citations
TL;DR: This paper focuses on integrating XML data based on multiple related XML schemas, to an equivalent data warehouse schemas based on relational online analytical processing (ROLAP) and a new data structure, Schema Graph has been proposed in the process.
Abstract: Data Warehouse is one of the most common ways for analyzing large data for decision based system. These data are often sourced from online transactional system. The transactional data are represented in different formats. XML is one of the worldwide standards to represent data in web based system. Numbers of organizations use XML for e-commerce and internet based applications. Integration of XML and data warehouse for the innovation of business logic and to enhance decision making has therefore emerged as a demanding area of research interest. This paper focuses on integrating XML data based on multiple related XML schemas, to an equivalent data warehouse schemas based on relational online analytical processing (ROLAP). This work bears a high relevance towards standardizing of the ETL phase (Extraction, Transformation, and Loading) of the OLAP projects. The novelty of the work is that more than one data warehouse schemas could be identified from a single related XML schema and each of them could be categorized as star schema or snowflake schema. Moreover if the individual schemas are found to be related according to the analysis, fact constellation could be identified. A new data structure, Schema Graph has been proposed in the process.
15 citations
TL;DR: This research work dynamically finds the most cost effective path from the lattice structure of cuboids based on concept hierarchy to minimize the query access time.
13 citations
TL;DR: An operational approach to the construction of a Bayesian network BN to predict purchase behaviour is proposed and a non-monotonic relationship between purchase behaviour and stay time is revealed.
Abstract: The prediction of consumers' purchase behaviour has been extensively investigated because accurate predictions assist managers and retailers in meeting customer needs and achieving profitability. This article presents two contributions to the consumer purchase behaviour research. First, the author describes new in-store behaviour data - radio frequency identification RFID data. An RFID tag attached to a customer's shopping cart can monitor and record the in-store behaviour e.g., location coordinates and elapsed time of that customer at any time. This article refers to in-store behaviour as 'stay time' and applies it to a time-based prediction of purchase behaviour. Second, the author reveals a non-monotonic relationship between purchase behaviour and stay time. For this purpose, the author proposes an operational approach to the construction of a Bayesian network BN to predict purchase behaviour. This article experiments a new perspective on the improvement of purchase decision-making predictions in contrast with the traditional hypothesis.
13 citations