Customer Database Research Articles

Customer Management at Gig's Batik MSMEs to Build Customer Loyalty

This community service activity aims to: (1). Increase partners' understanding of the importance of building customer loyalty, (2). Upgrade partners' knowledge and skills in managing customer databases so that they can be used for implementing further marketing programs such as: providing information on new products or to promote products, and (3). Broaden partners' insights in managing customer loyalty as one of the bases to support improving MSMEs business performance. The method used in this community service activity is through outreach activities, training and monitoring or mentoring program implementation. The results of the implementation of the community service program indicate an increase in partners' knowledge regarding the importance of building customer loyalty, managing customer data and an increase in partners' skills in documenting customer databases. Besides that, partners also have additional knowledge about managing customer loyalty Based on the programs that have been implemented, it can be concluded that customer relationship management is an important key to building customer loyalty. For this reason, entrepreneurs need to focus on consumers so that they feel satisfied and are willing to make repeated purchases of the products offered by MSMEs.

A Survey Paper on Data-Driven CRM: Unearthing Opportunities with the Power of Data Mining

Abstract: In the contemporary landscape of marketing, Customer Relationship Management (CRM) has emerged as a pivotal strategy for businesses to ensure sustainable growth by leveraging customer knowledge. Central to this approach is the utilization of Data Mining (DM) techniques, which enable the extraction of intricate insights from extensive customer databases. This research paper delves into the fundamental role of Data Mining within the realm of CRM and elucidates its significance in shaping effective marketing strategies. Through this analysis, the paper underscores the indispensable synergy between CRM and Data Mining as a potent avenue for businesses to enhance customer engagement, tailor marketing approaches, and ultimately foster sustainable business growth.

Internet of things application in digital marketing to improve the efficacy of a company

The expansion of digital marketing at the international level has been so fast and the benefits associated with it are clearly increasing day by day that developing countries are strongly encouraged to use it and each of them has specific programs to implement it. After telecommunication networks of computer, Internet and mobile phone, Internet of things (IOT) is considered as the third development in the global information industry, which has attracted the attention of many organizations and customers. This technology, relying on the intelligentization of objects and the use of internet platforms, is able to create wide and diverse services in e-commerce. This is while the demands of users for more diverse and better-quality services through the Internet are increasing. In this paper, application of IOT in digital marketing has been introduced and the effects of using it to increase efficiency and create innovation in the company have been discussed. The statistical sample in this research included all the managers of small and medium companies in Baghdad, which was determined as the statistical sample size of 275 based on the Krejcie Morgan table. Data analysis was done by the method of structural rates, which was used in this article by the method of least squares. The results showed that the use of IOT and electronic commerce had a positive and significant impact on the performance of companies (financial, internal processes, customers, development and innovation). The results of this research show that IOT technology has provided the basis for improving performance and providing better services in digital marketing by creating an integrated and strong database of suppliers, manufacturers, distributors, customers and products. Also, in the last part of the article, the implementation framework of this technology in e-commerce for the use of the country’s managers in various industries is presented.

Analysis of the Customer Churn Prediction Project in the Hotel Industry Based on Text Mining and the Random Forest Algorithm

The ability of hotels to differentiate themselves from competitors and continue to operate profitably depends on their ability to retain their customers by building long-term and permanent customer relationships. Technological developments in recent years have made it possible for companies to predict their customers’ behavior by accessing their opinions faster and preventing them from churning. Managing customer churn prediction projects has become an important issue today, especially in the hotel industry. Therefore, this research seeks to analyze projects that predict the churn of hotel customers to provide a model to help hotel managers in this field. In this research, an approach based on text mining on customers’ comments in the Persian language is presented, which uses the random forest algorithm for classification that was considered the most effective method to solve this problem. In this model, to increase the efficiency of the proposed method in compare with existing works, the gravitational search algorithm was used to select the useful features, and the differential evolution algorithm was used to adjust the parameters of the classification method. The dataset of this research is the collected data from the customer database on social networks and hotels’ websites, especially the hotels on Kish Island in Iran. The results of this research showed that after the implementation of the preprocessing operations, the method of adjusting the parameters and removing the unimportant features, the model’s accuracy increased significantly. The precision, recall, F1, and accuracy criteria were 0.77, 0.76, 0.76, and 0.77, respectively.

Roles of Telemarketing in Marketing of Marketplace at PT. LTP South Tangerang

This research was conducted to determine the role of telemarketing in job marketplace marketing at PT LTP South Tangerang, the main purpose of this study was to determine the role of telemarketing in marketing the installation of job vacancy information at PT LTP South Tangerang, Telemarketing obstacles in the marketing process of installing job vacancy information, and solutions carried out to overcome obstacles that occur during the marketing process of installing job vacancy information. This research was conducted using descriptive qualitative methods, with data collection methods carried out, namely observation, interviews, and literature studies. Based on the results of the study, it can be concluded that the role of telemarketing in job marketplace marketing at PT LTP South Tangerang is to increase the number of customer databases, develop customer relationships by telephone, conduct digital marketing to increase the use and branding of job marketplaces, influence prospective customers to be interested in posting job vacancy information ads, direct and assist the process of posting job vacancy information. There are still obstacles experienced including inadequate telephone facilities, poor telephone networks, not directly connected to the target telephone recipient, and invalid database contact numbers. Then solutions were obtained to overcome existing obstacles, including solutions for inadequate telephone facilities, namely routinely cleaning the chace, preparing cellphone storage reserves and adding telephone facilities. The bad network solution is to change the provider, the solution if it is not directly connected to the target telephone recipient, namely by increasing the number of databases to be called and follow up and ask for HRD contact information so that it can be contacted directly, Then the solution to invalid contact numbers is to update the database with more relevant sources.

Holistic Landscape Involving the Banking Industry and the Ultra Micro Community

Ministry of State-Owned Enterprise of the Republic of Indonesia (BUMN) recently created Ultra Micro Holding BUMN consisting of PT BRI (Bank Rakyat Indonesia), PT Pegadaian and PT PNM Permodalan Nasional Madani. Permodalan Nasional Madani (PNM) and PT Pegadaian are subsidiaries of PT Bank Rakyat Indonesia (Persero) Tbk (BBR) as part of the establishment of Ultra Micro Holdings (UMi) with BRI as the holding company. The two BUMNs officially became BRI's subsidiaries after the government officially transferred its Series B shares in PNM and Pegadaian to BRI so that the government's shares directly remained only Series A shares in PNM and Pegadaian. When the government issued PP Number 73/2021 concerning the Investment of the State of the Republic of Indonesia into the Share Capital of the Limited Liability Company (Persero) PT Bank Rakyat Indonesia Tbk, this regulation regulates the formation of the Ultra Micro holding, which involves three BUMN entities, namely BRI, Pegadaian, and PNM, until it is finally realized with the joining of the two BUMNs to BRI. The implementation of the integration of these three companies in the field is expected to provide efficiency in the company's operations. In simple terms, it is hoped that aspects of risk and operational costs can be minimized by collaboration and digitalization, for example, by utilizing co-location and optimizing the current huge customer database. This research is aimed to help PT Bank Rakyat Indonesia to analyze the Politic, Economy, Social, Technology, Environment and Legal (PESTEL) landsacape of banking industry in Indonesia in ultra-micro segment.

DISTRIBUTION SERVICE PERFORMANCE OPTIMIZATION OF PDAM TIRTA TAMAN BONTANG CITY EAST KALIMANTAN PROVINCE

To achieve the level of service performance from PDAM Tirta Taman Kota Bontang , obtained based on user perceptions of PDAM Taman Tirta obtained from the results of a questionnaire with a Likert scale using the Importance Performance Analysis (IPA) method. From the results of the IPA analysis, interviews were then conducted using the Strength Weakness Opportunities Threats (SWOT) method . The results of the IPA analysis were used in quadrant I, namely service to the registration process (x11), survey of prospective customer locations (x12), time of survey implementation (x13) , Payment orders before installation (x15), Notice the length of the installation process (X15). Registration up to installation (X16), the supplied water meets health standards, attributes (X21 ), the quality of the supplied water (color, smell, taste) (X22) , report to PDAM Tirta Taman if there is a disturbance or it doesn't work smoothly (x 33 ), the duration of handling the damage house connection (x 43 ), customer or prospective customer database of PDAM Tirta Taman (x 71 ). Then the SWOT quadrant matrix with the SO ( Strengths-Opportunities ) strategy, namely development with IT and with social media Periodic pipe rejuvenation to avoid pipe leaks that can affect quality, Providing Customer Service via WhatsApp for service notifications, disruptions and payment orders, Issuing SOPs new and regular schedule for maintenance., Continue to perform security updates on the database storage system , Use of official forms for prospective customers with the interest of installing a new connection

Optimizing main spectra profiles for development of customer databases by using a small heat shock in the standard MALDI-TOF MS protocol

In the last decade, MALDI-TOF MS has been proven as a solid option for microbial identification through the comparison of its profiles of protein spectra with those represented in a commercial library. The capabilities of this method for fast and accurate identification, depend mainly on the content of the protein spectral libraries that are used in the comparison.Commercial MALDI machines currently includes thousands of mass spectrum profiles in their databases. Despite this, the platforms have some difficulties to correctly identify some groups of microorganisms, generally due to the scarce or null representativeness in the commercial databases.That is the most important reason in the development of a custom MALDI Main Spectrum Profile (MSPs) in complementary libraries, including new microorganisms not represented before or local circulating species.In Argentina, within the framework of the National Network of Identification by Mass Spectrometry (ReNaEM, in spanish) the protein profiles of several isolates are created constantly to complement the Bruker Biotyper libraries, in order to improve the accuracy of identifications at species level for difficult bacterial and fungi of clinical relevance. These incorporations are transferred and installed in every platform around the country to ensure a timely and homogeneous diagnosis.From the National Reference Laboratory, we have modified the standard protocol, adding a simple step, which has significantly improved the characteristics of protein profiles obtained from difficult isolates, generating in our case 19 new MSPs with better quality, that means higher number of peaks present with higher frequency in each spectra of the profile, allowing their incorporation into the additional libraries faster than the original protocol.

Development of a geographic information system for monitoring work with customers for the supply, maintenance and automation of elevator equipment for LLC «Expert-Agro»

As part of the production practice in LLC «Expert-Agro» developed a geographic information system (GIS) for the supply and maintenance of the produced elevator equipment. In the MS Access system, a database of customers has been formed that contains the names of enterprises, addresses and coordinates of their location, contact information, information on orders (purchase, delivery and installation of equipment, maintenance of existing equipment, repair work, etc.). At the same time, a message is automatically generated when the day of completion of the order approaches, which allows you to control the efficiency of working with customers and, if necessary, extend the lead time of the order. In the MS Visual Studio integrated environment, using the gmap.Net library, geolocation was implemented to display customers on the map, which makes it possible to assess the geography of LLC «Expert-Agro» and plan further expansion of interaction. Controlling the location of customers also provides a solution to logistical problems for the supply of equipment. The system additionally provides for the selection of process parameters sensors, actuators, control controllers with input / output modules and other devices for automating the supplied equipment. At present, the GIS database is being filled with information on manufactured equipment and devices that are used in standard automation projects.

From customer intelligence to sustainability: management feature of SMEs in Almaty City

ABSTRACT The aim of this study is to obtain data on the perception and use level of customer intelligence (CI) tools, including customer database, customer journey map, customer feedback from Kazakhstan’s small and medium-sized enterprises (SME). Furthermore, this study aims to examine the impact of these tools on the marketing activity effectiveness through indicators of marketing performance, and, as a result, on the SME’s sustainability in Kazakhstan. Expert interviews (owners and managers of middle and top levels) with 25 Kazakhstani companies and a literature review are conducted to achieve the research objectives. This research presents how SME experts understand and apply CI features, estimate the potential and probability of changes and the agents restraining these changes in marketing activities from the CI lens, and enumerate marketing and business performance indicators. Based on the findings, the model of SMEs’ value and the importance of CI applications in marketing activity is created and presented.

Application of quantum technologies in banking

Aim. IThe presented study aims to identify current trends and key directions for the introduction of quantum technologies into the management practices of Russian credit institutions to improve their performance in the medium term.Tasks. The authors comparatively analyze current trends in the application of quantum technologies in the banking business; forecast key trends in their development in the medium term in the context of the Russian banking sector.Methods. The authors use the methods of comparative and system analysis, scientific abstraction, and hypothesis.Results. Practical examples of the introduction of modern quantum technologies in the foreign and Russian banking business are provided. As a result, priority directions and areas of their application are identified with an emphasis on the domestic banking sector: credit scoring, assessment of the value and risk of investment, diversification of investment portfolios, financial forecasting, crisis prediction, fraud detection, protection of banking and customer databases from the quantum threat, and increasing the level of banking cybersecurity in general.Conclusions. Despite the novelty of quantum technologies in the banking business, the role they will play in banking in the near future is difficult to overestimate. Quantum computers can significantly improve the performance of banking IT systems by solving computational tasks that even super-powerful conventional computers are not able to tackle on their own. They significantly increase the efficiency of modeling complex systems and processes; accelerate the soultion of problems associated with resource optimization, logistics, finance, and trading; simplify work with big data using artificial intelligence (AI) and machine learning models in neural networks; help to combat cyber attacks and fraud in financial markets.

Persuasive Determinants in the Hotel Industry’s Newsletter Opening Rates

Email marketing plays a key role in business communications and is one of the most widely used applications by consumers. The literature review points to several determinants that, when applied, increase the open rate of newsletters. This research evaluates the impact of six determinants of persuasion on the opening rate of a newsletter in the hotel industry. The determinants are the day of sending, the time of sending, subject line personalization, scarcity appeal, curiosity appeal, and authority figure. The chosen methodology focused on real experiments, using a high-end luxury hotel, and the respective customer database. The newsletter was sent to the subscriber list, where one part received the control and the other part received a variant with the test version. Ten A/B tests were conducted for each determinant. The results obtained were not in line with what is indicated in the literature review. Although the literature review yielded results that showed that the application of determinants increased the open rate of newsletters, this study obtained findings to the opposite and did not confirm what was prescribed by the reviewed literature. The results of the A/B tests were conclusive and revealed that the determinants did not increase the open rate of newsletters.

Glosa do wyroku Naczelnego Sądu Administracyjnego w Warszawie z 9 lutego 2023 r., sygn. akt III OSK 3945/21

Judgment of the Supreme Administrative Court in Warsaw of February 9, 2023, III OSK 3945/21 concerns the decision of the President of the UODO regarding inadequate security measures used by the Morele.net online store, which resulted in unauthorized access to the store’s customer database. One of the disputed issues resolved is whether the President is competent to independently assess whether the technical and organizational measures used by a party to administrative proceedings to protect personal data were “adequate”, which undoubtedly requires special knowledge. The court’s position is that the President should not ascribe expertise to himself just by virtue of being a public administration body, even with a special status. The judgment should prompt the President to develop an effective methodology for its control activities. Otherwise, the authority won’t be able to refute the accusation of subjectively created objectivity shaped in jurisprudence, as well as the selective equality of administrators.

Roles of Customer Databases and Database Marketing in Customer Relationship Management

Development in information technology helps companies to build customer databases, perform database marketing, and do relationship management. The study discusses the various aspects of customer databases and database marketing and their roles in relationship management. It discusses the ways in which a customer database can be used to achieve best results. The study discusses the various issues of database marketing, ways of overcoming the issues, internal changes in an organization which should be made for implementing database marketing, and emphasizes that database marketing is not the solution to every issue. Organizations should analyze all these issues during CRM implementation. It also provides a direction for achieving the goals in relationship management. Organizations should be aware of and should consider all these aspects of customer databases and database marketing to develop customer relationships, to do CRM implementation, to achieve business excellence, and to succeed in the long run.

A COMPARISON OF COX PROPORTIONAL HAZARD AND RANDOM SURVIVAL FOREST MODELS IN PREDICTING CHURN OF THE TELECOMMUNICATION INDUSTRY CUSTOMER

The Cox Proportional hazard model is a popular method to analyze right-censored survival data. This method is efficient to use if the proportional hazard assumption is fulfilled. This method does not provide an accurate conclusion if these assumptions are not fulfilled. The new innovative method with a non-parametric approach is now developing to predict the time until an event occurs based on machine learning techniques that can solve the limitation of CPH. The method is Random Survival Forest, which analyzes right-censored survival data without regard to any assumptions. This paper aims to compare the predictive quality of the two methods using the C-index value in predicting right-censored survival data on churn data of the telecommunication industry customers with 2P packages consisting of Internet and TV, which are taken from all customer databases in the Jabodetabek area. The results show that the median value of the C-index of the RSF model is 0.769, greater than the median C-index value of the CPH model of 0.689. So the prediction quality of the RSF model is better than the CPH model in predicting the churn of the telecommunications industry customer.

Web-Based Customer Services Management Implementation For The Sales Division

With the growing business at PT Mastersystem Infotama, more and more customers and orders have been obtained. As time goes by, many sales go in and out, and staff change, so the customer database cannot be maintained and updated correctly. All leads and opportunities cannot be monitored and appropriately managed, and the daily activity of the sales division is also not monitored. Implementation of Customer Relationship Management (CRM) helps maintain customer data and can be continuously updated to maintain good relations with all customers. Prospects and opportunities can be managed and monitored, the daily activities of the sales division are neatly scheduled, and customer observations can be gathered, all of which can be done in one application, CRM. With this implementation, sales at PT Mastersystem Infotama experienced a 20% increase in sales in 2018. This research uses the waterfall model, which has the advantage of being a gradual and more detailed method to minimize errors. This CRM implementation produces a web-based CRM application that can be accessed by all employees wherever they are connected to a LAN. Employees can access CRM according to each division's capacity to make work easier.

ASSOCIATION RULE MINING UNTUK PROMO WHATSAPP BLAST PADA PRODUK ACE HARDWARE JAMBI PRIMA MALL

Customer service staff at the Ace Hardware Jambi Prima Mall company with one of their jobs is to manage customer databases that are used for marketing strategies, one of which is whatsapp blast, but the customer database is not widely managed, therefore the purpose of this data mining analysis thesis report is to use association rules on the method a priori to describe promos addressed to customers based on shopping history. Association rules were formed with the help of the weka tools through a case study of promotional facilities at Ace Hardware Jambi Prima Mall, the development of this website application using the PHP programming language and the phpMyAdmin database. Weka tools are used for the process of finding the best association rules from training data or customer transaction data and the website application is used to display promo predictions from the results of association rules on weka tools. The inputs needed in this application are customer data, transaction data, product data and promo data with a promo prediction process and whatsapp blast status. From the input and the previous process, it will generate reports or customer outputs who will get promos based on shopping history.

Modeling and Applying Implicit Dormant Features for Recommendation via Clustering and Deep Factorization.

E-commerce systems experience poor quality of performance when the number of records in the customer database increases due to the gradual growth of customers and products. Applying implicit hidden features into the recommender system (RS) plays an important role in enhancing its performance due to the original dataset's sparseness. In particular, we can comprehend the relationship between products and customers by analyzing the hierarchically expressed hidden implicit features of them. Furthermore, the effectiveness of rating prediction and system customization increases when the customer-added tag information is combined with hierarchically structured hidden implicit features. For these reasons, we concentrate on early grouping of comparable customers using the clustering technique as a first step, and then, we further enhance the efficacy of recommendations by obtaining implicit hidden features and combining them via customer's tag information, which regularizes the deep-factorization procedure. The idea behind the proposed method was to cluster customers early via a customer rating matrix and deeply factorize a basic WNMF (weighted nonnegative matrix factorization) model to generate customers preference's hierarchically structured hidden implicit features and product characteristics in each cluster, which reveals a deep relationship between them and regularizes the prediction procedure via an auxiliary parameter (tag information). The testimonies and empirical findings supported the viability of the proposed approach. Especially, MAE of the rating prediction was 0.8011 with 60% training dataset size, while the error rate was equal to 0.7965 with 80% training dataset size. Moreover, MAE rates were 0.8781 and 0.9046 in new 50 and 100 customer cold-start scenarios, respectively. The proposed model outperformed other baseline models that independently employed the major properties of customers, products, or tags in the prediction process.

The Roles of Customer Databases and Database Marketing in Marketing Intelligence

Customer databases and database marketing play important roles in marketing intelligence and in building and developing customer relationships for organizations. Development of customer databases and performing database marketing are made possible mainly by the advancements in information technology. The study discusses various aspects of customer databases and database marketing and their roles in marketing intelligence and in building customer relationships. It discusses the ways in which companies can use customer databases effectively to achieve the best results. The study discusses the issues of database marketing, ways of overcoming them, internal changes in an organization required for the implementation of database marketing, and emphasizes that maintenance of customer databases and performing database marketing are not the solutions to every problem in building customer relationships. It will help practitioners and researchers in finding a direction for generating customer insights, achieving the goals in relationship management, and in achieving business excellence.

Assessing the needs of those who serve the underserved: A national survey among cancer care clinicians.

175 Background: In 2009, ASCO confirmed that addressing cancer care disparities is critical for the Society and committed to approaches to eliminate such disparities. Yet, gaps remain in identifying the best approaches to do so. It remains unknown which cancer care providers serve patients from “underserved populations'' (defined as individuals who have historically received inadequate health care and health care services), what unmet needs they experience in their cancer care delivery, and how best to engage and support these providers. The objectives of this study were to explore challenges faced by providers serving underserved patients to inform development of a broader online survey and identify solutions that ASCO can implement to better support these providers. Methods: A multi-phase mixed-methods approach was utilized. Phase 1 involved key informant semi-structured interviews with 12 oncology providers caring for adult patients in the US from April to May 2021. Phase 2 involved survey development based on themes identified in Phase 1. The survey assessed: provider needs; processes for eliciting, documenting, and addressing social and economic needs of patients; and how ASCO could best support these providers. Phase 3 involved email distribution of the online survey in May 2022 to 5800 individuals identified through ASCO’s customer database. Eligibility criteria included providing care for adults with cancer in the US and prior consent to receive ASCO survey communications. Results: Of 477 respondents, the majority were ASCO members (88%), in an academic practice (57%), medical oncologists (77%), non-Hispanic (89%) and/or Caucasian/White (67%) and had > 15 years’ clinical experience (57%). A majority (60%) provided ≥25% of their clinical time providing cancer care to underserved populations and routinely engaged with administration to secure resources (61%) and local community organizations to obtain services (42%) for patients. Most (43-77%) indicated that a social worker/case manager was primarily responsible for addressing patient social needs. The majority reported that identification and dissemination of best practices (55%) and development of a return-on-investment business model (60%) would best help address patient needs. Some respondents expressed a desire to collaborate with ASCO on policy reform (32%) and for ASCO to help build or strengthen partnerships with local initiatives (29%). Conclusions: This is the first US-based survey assessing barriers and solutions to delivering cancer care among underserved populations. The findings from this work provide insights about how ASCO can help equip practices to address the social needs of their patients. Further work will be conducted to develop and implement suggested solutions.