Brand Association and Sales Growth: A Study of Nigeria the Flour Milling Industry

Branding has developed in the minds of customers a strong and positive perception of a company's products or services. However, most of these businesses struggle to use branding strategy to differentiate themselves from competition and grow sales. The goal of this study is to assess the impact of brand association tactics on the sales growth of flour milling enterprises. The major technique of data collection was administered questionnaire to the sales and marketing employees of the selected flour milling enterprises in Lagos State. The findings indicated that brand connections have a positive and considerable impact on sales growth. The study recommends that brand managers should also ensure that customers' interactions with the brand remain consistent in order to generate sales growth.

The impact of big data on innovation and value generation in pharmaceutical sales and marketing

Using Big Data in the pharmaceutical industry is a relatively new technology, and the benefits and applications are yet to be understood. There are some cases currently being piloted, but others have already been adopted by some pharmaceutical organizations, proving the unmet need in a field that is still in its infancy. This paper aims to understand how and if Big Data can contribute to commercial innovation, as well as future trends, investment opportunities. Participants from 26 pharmaceutical companies participated in different focus groups where topics were grouped by individuals and evaluation areas were discussed to discover any potential connections between Big Data and Innovation in commercial pharmaceutical environments. This study used the collected data to analyze and draw conclusions about how many life sciences leaders and professionals already know about Big Data and are identifying examples and processes where Big data is supporting and generating innovation. In addition, we were able to understand that the industry is already comfortable with Big Data, and there were some very accurate research results regarding the most pertinent application fields and key considerations moving forward. Using the network analysis findings and the relationships and connections explained by respondents, we can reveal how Big Data and innovation are interconnected.

A Review of Urdu Sentiment Analysis with Multilingual Perspective: A Case of Urdu and Roman Urdu Language

Research efforts in the field of sentiment analysis have exponentially increased in the last few years due to its applicability in areas such as online product purchasing, marketing, and reputation management. Social media and online shopping sites have become a rich source of user-generated data. Manufacturing, sales, and marketing organizations are progressively turning their eyes to this source to get worldwide feedback on their activities and products. Millions of sentences in Urdu and Roman Urdu are posted daily on social sites, such as Facebook, Instagram, Snapchat, and Twitter. Disregarding people’s opinions in Urdu and Roman Urdu and considering only resource-rich English language leads to the vital loss of this vast amount of data. Our research focused on collecting research papers related to Urdu and Roman Urdu language and analyzing them in terms of preprocessing, feature extraction, and classification techniques. This paper contains a comprehensive study of research conducted on Roman Urdu and Urdu text for a product review. This study is divided into categories, such as collection of relevant corpora, data preprocessing, feature extraction, classification platforms and approaches, limitations, and future work. The comparison was made based on evaluating different research factors, such as corpus, lexicon, and opinions. Each reviewed paper was evaluated according to some provided benchmarks and categorized accordingly. Based on results obtained and the comparisons made, we suggested some helpful steps in a future study.

Penerapan Asosiasi Algoritma Apriori Pada Data Penjualan Alat-Alat Listrik Dan Tekhnik

The incompatibility of information in reporting productsthat are sold, and data storage is very large, business people, especially in the sales business are required to find an appropriate strategy that can increase sales and marketing of products sold, one of which is by using electronic product sales data. Therefore, anapplication is needed that is able to sort and select data, so that information can be obtained that is useful for users, namely data mining. Associate patterns can be used to place products that are often purchased together into an area that is close together so as to facilitate the customer in finding the desired product and designing the appearance of products in the catalog. The method used is theApriori Algorithm method, with the help ofTanagra 1.4.50 tools and processing transaction data using Microsoft Excel 2007.

Recommendations for improving the export efficiency of domestic enterprises

Introduction. One of the prerequisites for deciding on foreign economic activity (FEA) is its effectiveness. It is determined by comparing the economic result (profit, revenue) with the costs incurred by the enterprise to obtain such a result. Analysis of the effectiveness of foreign trade by the company provides an opportunity to make an informed management decision in the field of exports: which product is better to sell abroad, with which counterparties it is more profitable to cooperate, in what quantity, on what terms. The purpose of the paper is to study the main problems of improving the efficiency of exports of domestic enterprises, providing recommendations on the technology of finding intermediaries. Results. Many problems can arise when a company aims to increase the efficiency of its exports. The focus was on the problem of low efficiency of exports due to inflated prices for the services of intermediaries in foreign markets. The recommended technology of search and involvement of intermediaries was provided, which consists of the following stages: determining the purpose of finding an intermediary, determining the resource capabilities of the enterprise (personnel, financial, material), determining the type of intermediary (distributor, agent, representative, etc.), determining evaluation criteria, search for intermediaries on Internet resources (Europages, SME Internationalization Portal, etc.) or through own contacts, evaluation and comparison of intermediaries according to previously defined criteria and choosing one of them, meeting with an intermediary in the context of foreign business travel or video communication and discussing all the details of the agreement, signing the contract with the mediator and starting work with him. Conclusion. Implementation of the proposed recommendation will have a positive impact on the enterprise and will achieve the following effects: economic, due to reduced costs of sales, marketing, transportation, which will pass to the intermediary, as well as due to increased sales by increasing the company's visibility in foreign markets; social, due to the reduction of the burden on employees of sales and marketing departments, as some of their responsibilities will be transferred to the intermediary.

Analisis Penerapan Enterprise Resource Planning (ERP) Pada PT Sinar Sosro Palembang

PT. Sinar Sosro which is the first ready to drink bottled company in Indonesia and in the world. In developing its business, PT. Sinar Sosro has distributed sales throughout the archipelago, through sales branch offices spread throughout the archipelago. PT. Sinar Sosro in its company management has implemented the Enterprise Resource Planning System, the ERP system built by Sosro's management allows access to data from Sosro's branch offices. Functional area at PT. Sinar Sosro covers: Sales and marketing, Manufacturing, Finance, Accounting, Logistics, Distribution, Inventory, Invoice. In the grip of this functional area, PT. Sinar Sosro uses SAP as its ERP program. The distribution system is capable of handling the company's manufacturing, logistics, inventory, shipping, invoicing, and accounting processes. This system helps control business activities such as sales, delivery, production, inventory management, quality management, and human resources. The modules used in SAP are inventory management, plant maintenance, production, finance and accounting, human resource management.

Sistem Rekomendasi Menggunakan Algoritma Apriori Pada Aplikasi E-Commerce Toko Sudirman Sport

The System of selling and marketing products at the Sudirman Sport store which is still done conventionally causes the problem of lack of sales transactions obtained by the store because it only relies on buyers who come directly to the store. Meanwhile, many stores in Indonesia have implemented any system e-commerce in stores. The solution to this problem is to build a website-e-commerce application based for sales and marketing of products sold by the Sudirman Sport store and implement a marketing strategy, namely the System Recommendation Product attract buyers to buy products that have been offered by the Sudirman Sport store and combined with the a priori algorithm to get accuracy in the data processing process to help stores predict buyer interest in an item and then recommend it in order to attract buyers and increase product sales at the Sudirman sport store.

Implementasi Customer Relationship Management (CRM) di Atria Hotel Malang

Atria Hotel Malang adalah salah satu hotel bintang empat yang terletak di Kota Malang, tepatnya berada di jantung kota Malang. Pihak manajemen hotel perlu menerapkan strategi pemasaran berupa Customer Relationship Management (CRM) untuk menciptakan kepuasan pelanggan terhadap pelayanan yang diberikan. Dalam melaksanakan strategi CRM, ada empat implementasi untuk menciptakan dan mengelola hubungan dengan pelanggan, yaitu: (1) identifikasi; (2) diferensiasi; (3) interaksi; (4) Customize. Metode penelitian yang digunakan peneliti adalah metode penelitian kualitatif. Berdasarkan hasil penelitian dapat disimpulkan bahwa Implementasi Customer Relationship Management (CRM) pada sales and marketing department dalam memelihara dan menjaga hubungan baik dengan pelanggan sudah dilaksanakan dengan baik dalam pengembangan brand awareness kepada publik, namun dalam penerapan customer relationship management masih belum dilakukan secara efektif karena masih terdapat banyak database pelanggan pada corporate segment yang menumpuk dan tidak valid lagi akibat dari pengelolaan hubungan yang tidak merata kepada pelanggan. Atria Hotel Malang memerlukan ide yang kreatif dan inovatif di setiap tahunnya agar mampu meningkatkan kualitas produk dan citra perusahaan di hadapan konsumen.

Implementation of C4.5 Method and Artificial Neural Networks to Predict Sales

Technology and communication is currently growing along with the increasing needs of each individual in various fields such as: business, education, agriculture, health and technology. With the development of technology today, everyone can communicate and obtain and convey various information needed anytime and anywhere quickly, accurately and dynamically.Sales is an activity of buying and selling products or goods carried out between sellers and buyers, can interact within the same scope or online by using legal payment transactions. Building materials are materials used to design buildings such as houses, mosques, schools etc. For buildings, many natural materials are used such as: clay, sand, wood or bamboo, stone and others. In this study, the implementation of the c45 method and an artificial neural network to predict sales for the next year. The sale of building materials at the prayer shop, whose sales are not yet computerized by designing a computerized sales system. Toko Doa Mama is a building shop that sells various building materials such as: sand, paint, wood, or bamboo, saws, cement, roof tiles, gravel, nails, bricks, and others. But sales and marketing are still not computerized which results in frequent errors in calculating sales transactions, data collection of incoming goods and outgoing goods which are still in the form of archives, resulting in accumulation and lack of data security. Therefore, we need a computerized where the computer can help a job to be more effective and efficient

Construction of the Luxury Marketing Model Based on Machine Learning Classification Algorithm

China has become the world’s largest luxury goods consumer market due to its population base. In view of the bright prospects of the luxury consumer market, major companies have entered and want to get a share. For the luxury goods industry, traditional mass marketing methods are not able to serve corporate sales and marketing strategies more effectively, and targeted marketing is clearly much more efficient than randomized marketing. Therefore, in this paper, based on consumer buying habits and characteristics data of luxury goods, the paper uses a machine learning algorithm to build a personalized marketing strategy model. And the paper uses historical data to model and form deductions to predict the purchase demand of each consumer and evaluate the possibility of customers buying different goods, including cosmetics, jewelry, and clothing.