What is the Baitul Maal wat Tamwil Inbound Marketing Model in Indonesia?

This study intends to describe practical models of inbound marketing at Baitul Maal Wat Tamwil (BMT). This research is an observational descriptive study on BMT in Indonesia, using the triangulation method. The total subjects recruited in the study were 50 BMT. This study uses primary data obtained based on structured interviews and in-depth interviews with BMT managers. Data analysis uses descriptive and qualitative analysis and is displayed in descriptive form. The findings of this study conclude that BMTs in Indonesia have used inbound marketing to inform and communicate with customers. Social media that is often used is Facebook, Whatsapp, Instagram, TikTok, and Twitter. The platform is quite effectively used in informing BMT products and interacting directly with customers. The benefit most felt by BMT is that communication with customers and customers is more intensive and effective and efficient because they can communicate directly in full and real-time. The strategy for implementing inbound marketing has proven to have a positive impact on BMT and its customers, inbound marketing has been able to increase sales of fundraising and financing products at BMT

Using SVM for Smart Direct Marketing (SDM): A case of predicting bank customers interested in the Term Deposits

Abstract: The objective of this study is to reveal how important and necessary it has become to adopt the new methods and technical of Data Mining derived from artificial intelligence (AI), and this in the process of marketing banking products and precisely that of Term Deposit (TD). Therefore, in our research study we adopted the Support Vector Machine (SVM) method, and we succeeded through the process of modeling borrowed by the techniques of Data Mining (DM) to build a model that will allow us to predict the behavior of bank customers toward term deposits, for this the SVM method has been applied on a database of customers of a bank which includes historical responses of customers during a marketing campaign of the product DT. For the manipulation tool we used, we chose the Python programming language, recognized by its power in modeling and exploiting DM techniques. For the methodology adopted, we started with a pre-treatment and cleaning of the data to keep only the significant explanatory variables and also for any extreme or aberrant variables, subsequently the modeling was carried out by adopting the DM process, at the end of this process we were able to measure the perfection and the level of predictability of our obtained model, thus we obtained the accuracy of 93% using the metric Accuracy, Thus according to the ROC curve we have that AUC=98, this reflects the performance of our obtained model. So, we were able to build a model that will help bankers make decisions in terms of predicting customers interested in the term deposit product.   JEL Classification : C02, C19, C35, C55, C6, M31,G2 Paper type: Empirical researchAbstract: The objective of this study is to reveal how important and necessary it has become to adopt the new methods and technical of Data Mining derived from artificial intelligence (AI), and this in the process of marketing banking products and precisely that of Term Deposit (TD). Therefore, in our research study we adopted the Support Vector Machine (SVM) method, and we succeeded through the process of modeling borrowed by the techniques of Data Mining (DM) to build a model that will allow us to predict the behavior of bank customers toward term deposits, for this the SVM method has been applied on a database of customers of a bank which includes historical responses of customers during a marketing campaign of the product DT. For the manipulation tool we used, we chose the Python programming language, recognized by its power in modeling and exploiting DM techniques. For the methodology adopted, we started with a pre-treatment and cleaning of the data to keep only the significant explanatory variables and also for any extreme or aberrant variables, subsequently the modeling was carried out by adopting the DM process, at the end of this process we were able to measure the perfection and the level of predictability of our obtained model, thus we obtained the accuracy of 93% using the metric Accuracy, Thus according to the ROC curve we have that AUC=98, this reflects the performance of our obtained model. So, we were able to build a model that will help bankers make decisions in terms of predicting customers interested in the term deposit product.   JEL Classification : C02, C19, C35, C55, C6, M31,G2 Paper type: Empirical researc

Analysis of the ergonomics of interfaces of popular e-marketing tools

This article analyses the ergonomics of the interfaces of selected e-marketing tools. The main aim of the study was to verify whether all the examined tools have a similar user interface quality. The research was conducted using the cogni-tive walkthrough method, a modified LUT list with WUP scores, and a questionnaire for assessing tool usability based on Nielsen heuristics. Three tools designed for Internet monitoring were analysed - Brand24, Mention and Awario. The experiment showed that, in terms of the ergonomics of the solutions, not all tools have a similar interface quality. For two of the analysed tools, similar results and ratings were obtained, while one of them presented a noticeably lower level

Machine learning in digital marketing.

Marketers use machine learning to find patterns in user activities on a website or on a mobile application. This helps them predict the further behavior of users and quickly optimize advertising offers. In this paper, we present a novel algorithm based on Machine Learning used in the Information System for optimizing advertising services, attracting customers, growing sales, adapting the promotional offers that correspond to the hobbies of users, and for setting up a spam filter in the email or the Facebook service. Our framework demonstrates the feasibility of the approach to manage advertising campaigns to produce better results

Internet personalization as a marketing trend

The market is a key entity that sets the pace of change in various areas of business, not least marketing. The changes that have been taking place in the market over the last three decades mean that marketers need to stay up-to-date and in step with the developments of the times. This means, in particular, following the development of technology and its implementation in business activities. In marketing, new marketing trends have been applied as businesses have dealt with the impact of the pandemic crisis associated with COVID-19. The coronavirus crisis accelerated a fundamental change in the communication of businesses, organisations, governments, etc. The trend is towards personalised, active communication towards the customer, made possible by the rapid development of information technology and its computing power. This paper deals with the personalization of web pages and their use in the marketing processes of a company with emphasis on the current trends in this area. However, it also mentions past and anticipated future trends in Internet personalization. The aim of the text is then to provide a theoretical comparison of current web personalization techniques for marketing processes and to propose a framework for their use in practice. The paper presents research questions and uses secondary data analysis in the form of a literature review and content analysis. The text contributes to the discussion by identifying the practical application of the defined web personalization techniques and their position in marketing process strategies designed for online activities

A influência do big data nas estratégias de marketing digital

Big data, internet das coisas, tecnologia, análise preditiva, ferramentas digitais e social media são alguns dos conceitos que serão mencionados repetidamente ao longo da dissertação. Tal se deve ao facto de serem conceitos primordiais para a caraterização do tema. Na realidade, a indústria 4.0 veio mostrar que a tecnologia está continuamente a evoluir e cabe às empresas compreender a sua importância e o impacto que pode ter no seu negócio e, a partir daí, aproveitar da melhor forma as potencialidades trazidas pelo big data. Neste estudo procura-se explorar o conceito do big data e a influência dessa tecnologia em marketing digital. Para isso optou-se metodologicamente pela revisão sistemática da literatura por permitir recolher os documentos mais relevantes sobre a questão em estudo e assim fornecer uma perspetiva científica de valor. Como resultado surgiram vinte e dois documentos separados posteriormente em três clusters nomeadamente: os sistemas apresentados pelas empresas para a recolha e análise dos dados, as capacidades exigidas às organizações para lidarem com as mudanças tecnológicas e o impacto disso no comportamento do consumidor. Em conclusão, verifica-se que a transformação digital trouxe inevitavelmente mudanças nas empresas, obrigando-as a adaptarem-se e a desenvolverem soluções mais eficientes e automatizadas que as ajudem a destacar-se da concorrência num ambiente fortemente competitivo. Os estudos enfatizam a ideia de que estas devem priorizar as ferramentas analíticas para a tomada de decisão mais consciente e mais direcionada para as exigências do seu público.Big data, internet of things, technology, predictive analytics, digital tools and social media are some of the concepts that will be mentioned repeatedly throughout the dissertation. They are the primordial concepts to the characterization of the subject. In fact, industry 4.0 has come to show that technology is continually evolving and is the responsibility of enterprises to understand the importance and the impact that technology can have on their business and, from then on, take the advantage of the potential brought by big data. This study seeks to explore the concept of big data and the influence of that technology on digital marketing. For that, a systematic literature review was methodologically chosen for allowing the collection of the most relevant documents about the main question and thus provides a scientific perspective. As a result, twenty-two documents separated into three clusters including the systems presented by companies for the collection and analysis of data, the required capabilities of organizations to deal with technological changes and the impact of this on consumer behavior. In conclusion, the digital transformation inevitably brought changes to companies, forcing them to adapt and develop more efficient and automated solutions that help them to stand out in a highly competitive environment. The studies emphasize the idea that they should prioritize analytical tools for more conscious decision-making and more focused on their audience’s demands

Aplicação de machine learning na classificação de termos de pesquisa em campanhas publicitárias digitais

O presente estudo relaciona machine learning e marketing digital, através de um estudo da aplicação de um algoritmo de machine learning em termos de pesquisa gerados por uma campanha de mídia paga. O objetivo é identificar os termos de pior performance através de um algoritmo de clusterização, simplificando um processo manual e não assertivo. Utilizou-se um modelo de clusterização K-Means para identificar padrões dentro de um grande banco de dados, gerado diariamente por pesquisas feitas na plataforma de busca Google. Obteve-se como resultado um modelo, baseado em dados históricos, que segmenta a base em 7 diferentes clusters, onde analisou-se o cluster de pior performance para a negativação de termos de pesquisa em uma campanha. Com um algoritmo desenvolvido em Python e a partir de uma análise da performance dos estratos, foi possível, portanto, desenvolver um modelo que identificasse os termos de pior performance a serem negativados

Segmentación de mercado: Machine Learning en marketing en contextos de covid-19

La crisis sanitaria covid-19 ha provocado cambios jamás vistos en el comportamiento de los consumidores, quienes compran de manera diferente y por medios también diferentes. Los consumidores están mirando y valorando los productos a través de dispositivos electrónicos, configurando movimientos en segmentos de consumidores. El objetivo del presente estudio fue aplicar el modelo de clustering con recursos de Machine Learning en el análisis de conglomerados como recurso para la segmentación de consumidores, como un componente importante para la gestión del marketing empresarial. Para dicho propósito, se suministró un cuestionario de 6 preguntas a 506 personas de entre 18 y 65 años para recoger sus percepciones sobre el hecho de salir a comprar. Con los datos recogidos se organizó una dataset para procesarlo en el software RapidMiner Studio 9.10. Como resultado, se obtuvo la cantidad óptima de conglomerados y sus componentes a partir del indicador de performance procurado por Machine Learning

The Agility Model of the Banking Industry in Digital Marketing

The developments of digital marketing in the banking industry have affected the speed of changing customer demands. Therefore, the ability to quickly and agilely adapt to changes plays a key role in creating competitive advantages. Despite the significant role of agility in responding to changes, so far there is no research that identifies the agility components of the banking industry in digital marketing. Thus, based on the designing methods of qualitative research, and investigating digital marketing experimentally and theoretically, this study presents a new model for digital marketing agility in the banking industry. In this research, the key theoretical dimensions of digital marketing agility are identified and some suggestions for facilitating the model implementation are provided. The findings of this study include important results for marketing managers in the banking industry and indicate what strategic measures are needed to establish agile practices in the structure, processes and communications of their digital marketing from a practical perspective in the context of agile digital marketing

IMPLIKASI DIGITAL MARKETING DAN LITERASI EKONOMI SYARIAH DALAM MENINGKATKAN PENDAPATAN PELAKU INDUSTRI KECIL DAN MENENGAH DI PROVINSI LAMPUNG MELALUI E-COMMERCE

ABSTRAK Digital marketing dianggap salah satu faktor yang mampu meningkatkan kenaikan pendapatan bagi pelaku IKM di Provinsi Lampung melalui e-commerce. Namun, kebanyakan orang tidak melek ekonomi dan tidak terbiasa dengan konsep ekonomi maka akan berdampak pada pendapatan mereka. Dengan adanya transformasi dukungan digital marketing di imbangi dengan dukungan literasi ekonomi akan mampu meningkatkan pendapatan bagi pelaku IKM. Dalam penelitian ini, peneliti menggunakan istilah literasi ekonomi syariah. Penelitian ini merupakan penelitian yang menggunakan pendekatan kualitatif. Teknik pengumpulan data yang digunakan adalah wawancara dan observasi. Informan yang digunakan sebanyak 12 pelaku IKM di Provinsi Lampung. Hasil wawancara menunjukkan bahwa, seluruh informan sebanyak 12 pelaku IKM menggunakan digital marketing dan sudah menerapkan literasi ekonomi syariah. Seluruh pelaku IKM mengakui adanya peningkatan pendapatan dengan menggunakan digital marketing berdasarkan literasi ekonomi syariah. Hanya saja, ada beberapa pelaku IKM yang lebih fokus melayani konsumen yang membeli secara offline dalam skala besar. Kata Kunci : Digital Marketing, Literasi Ekonomi Syariah, IKM ii iv ABSTRACT Digital marketing is considered one of the factors that can increase the increase in income for Small and Medium Industries in Lampung Province through e-commerce. However, most people are not economic literate and are not familiar with economic concepts it will have an impact on their income. With the transformation of digital marketing support, balanced with the support of economic literacy, it will be able to increase income for Small and Medium Industry In this study, researchers used the term Islamic economic literacy. This research is a research that uses a qualitative approach. Data collection techniques used are interviews and observation. The informants used were 12 Small and Medium Industry in Lampung Province. The results of the interview show that all of the informants as many as 12 Small and Medium Industries use digital marketing and have implemented Islamic economic literacy. All Small and Medium Industry players acknowledge an increase in income by using digital marketing based on sharia economic literacy. However, there are several Small and Medium Industry players who are more focused on serving consumers who buy offline on a large scale. Keywords : Digital Marketing, Sharia Economic Literacy and Small and Medium Industr