Sales Process Research Articles

Innovative Global Sales Solution in The SAP enterprise business application

This paper explores the development of an innovative global sales solution within the SAP enterprise business application framework. By leveraging SAP's capabilities, organizations can create a comprehensive sales management platform that integrates real-time data analytics, customer relationship management enhancements, and automated sales processes. Key components include a centralized dashboard for performance tracking, AI-driven insights for customer engagement, and mobile solutions for field sales efficiency. The solution emphasizes compliance with global regulations and localization for diverse markets, while also integrating advanced analytics for predictive sales forecasting. Furthermore, it fosters collaboration through enablement tools and social selling features, ensuring that sales teams are well-equipped to meet customer needs. With a focus on sustainability and corporate social responsibility, this innovative approach not only enhances operational efficiency but also strengthens customer loyalty and brand reputation. Ultimately, this solution provides a scalable framework that positions organizations for success in a competitive global marketplace.

Machine Learning Applications in Salesforce CPQ Transforming Sales

This paper aims to understand the innovative disposals of machine learning applications on Salesforce Configure, Price, Quote (CPQ) applications more precisely how these innovations are revolutionizing software development. Salesforce CPQ is an ideal solution for organizations that want a modern tool to help them with their sales processes, and adding machine learning elements significantly improves the system. For example, the study analyses different cases where and how machine learning algorithm is utilised in the application of the following areas: pricing strategy, product configuration and sales forecasting. Upon collection of historical data, machine learning models are able to make computations of patterns that enables businesses to make quick analysis of the best strategies to use in an offer of various prices to the customers in an effort to enhance customer satisfaction. Furthermore, the application of I/A in the context of CPQ decreases the time engaged in manual configurations, liberating software development teams to work on other priorities essentially. These difficulties and strategies are enumerated in the paper: data quality issues and the impossibility of the Machine learning successful implementation without cooperation with other departments, specifically with Salesforce CPQ teams. In addition, it shares its vision on the tendencies in application of machine learning in CPQ systems with reference to software development paradigms. Finally, the scope of this research is as follows: The study will examine how the utilization of machine learning applications in Salesforce CPQ has changed traditional software development practices in today’s dynamic market environment by increasing efficiency and accuracy effectively, improving competitiveness within the market.

A Study on Key Performing Indicator and their Impact on Sales at MYBAE BAGS

Key Performance Indicators (KPIs) play an important role in the sales process in a competitive business environment. This study highlights the importance of KPIs in providing a structured way to measure, evaluate and optimize sales performance. KPIs, which include metrics such as sales revenue, conversion rates, customer acquisition costs, sales growth, and average transaction value, provide valuable insight into aspects of the sales process. Based on organizational goals and industry standards, these metrics help companies make data-driven decisions, reinforce accountability, and drive continuous improvement. This study explores the bag industry, divided into fashion, travel, sports, business and specialty bags. Advances in technology have led to the use of lighter and stronger materials and the inclusion of features such as RFID blocking sensors and integrated circuits. This industry is global and has a significant contribution to the economies of the world and India. Research methods include the collection of primary and secondary data using data analysis techniques to determine market size and forecast. A PESTEL analysis of an industry examines the political, economic, social, technological, environmental and legal issues affecting the industry. The report also provides an overview of MYBAE BAGS, highlighting its business segments, revenue growth, and market strategies. This study highlights the importance of KPIs in driving strategic change and achieving sustainable growth, positioning KPIs as important tools for organizations seeking to improve sales performance and good management

Digital Transformation Framework in Consumer Goods Wholesale Industry SMEs : Case Study in Wholesale SMEs of Babelan Districk

Small and Medium Industry (SMEs) is one type of business that has experienced a fairly developed growth valuation. Consumer goods wholesale SMEs have experienced rapid growth in the sales sector, specifically in the Babelan sub-district the consumer goods wholesale industry still uses a manual control system in running its business. The sales process with the Conventional System is carried out starting from stock control, sales activity control, sales process, cashier and revenue generation is still done manually. The manual control process causes a slow counting process, and a long process of re- ordering goods and losing assets. The solution needed at this time is the creation of a framework for Digital Transformation Steps in the sales process to facilitate the control of wholesale consumer goods business processes. The digital transformation framework is expected to modernize the sales process starting from the cashier system, revenue control system, sales activity control process and make it easier for wholesalers to order goods. This applied research is expected to be able to provide suggestions for wholesale consumer goods businesses in running their business in a more efficient and practical direction and can be a recommendation to be able to carry out a digitally transformed sales process.

The Role of Apttus CPQ in Modern CRM Systems: Implementation Challenges and Solutions

The advent of Configure, Price, Quote (CPQ) solutions has significantly transformed the landscape of Customer Relationship Management (CRM) systems, enhancing their ability to streamline sales processes, improve accuracy, and boost overall efficiency. Apttus CPQ, a prominent player in the CPQ market, offers a robust solution that integrates seamlessly with modern CRM systems to address complex pricing and quoting challenges. This research paper explores the role of Apttus CPQ in contemporary CRM environments, focusing on its implementation challenges and potential solutions. Apttus CPQ provides an advanced framework for managing product configurations, pricing strategies, and quote generation processes. By automating these critical aspects, Apttus CPQ aims to reduce manual errors, accelerate sales cycles, and improve the accuracy of quotes. Its integration with CRM systems, such as Salesforce, leverages existing customer data to generate accurate and customized quotes, enhancing the overall sales experience. However, despite its advanced capabilities, the implementation of Apttus CPQ presents several challenges that organizations must navigate.

Improving realty management ability based on big data and artificial intelligence decision-making.

Realty management relies on data from previous successful and failed purchase and utilization outcomes. The cumulative data at different stages are used to improve utilization efficacy. The vital problem is selecting data for analyzing the value incremental sequence and profitable utilization. This article proposes a knowledge-dependent data processing scheme (KDPS) to augment precise data analysis. This scheme operates on two levels. Data selection based on previous stagnant outcomes is performed in the first level. Different data processing is performed in the second level to mend the first level's flaws. Data processing uses knowledge acquired from the sales process, amenities, and market value. Based on the knowledge determined from successful realty sales and incremental features, further processing for new improvements and existing stagnancy mitigation is recommended. The stagnancy and realty values are used as knowledge for training the data processing system. This ensures definite profitable features meeting the amenity requirements under reduced stagnancy time. The proposed scheme improves the processing rate, stagnancy detection, success rate, and training ratio by 8.2%, 10.25%, 10.28%, and 7%, respectively. It reduces the processing time by 8.56% compared to the existing methods.

IMPLEMENTATION OF A DYNAMIC PRICING SYSTEM IN RETAIL: AN ANALYTICAL REVIEW OF THE PRACTICES OF RUSSIAN COMPANIES

Over the past few years, the conditions and nature of doing business for Russian companies have changed dramatically. The processes of procurement, logistics, product sales, accounting and other business processes are automated. The development of artificial intelligence technology and the growing volume of data are additional growth drivers for the company. Within the framework of this article, an analytical review of the practices of applying the pricing system in retail of Russian companies was conducted. The pricing process is key, which allows you to directly influence the main economic indicators of the company’s activities, since sales volume, profit, demand for products, inventories of inventory resources can be regulated by means of competent changes in prices for goods. Dynamic pricing is gaining great popularity among retailers, which leads to the expansion of patent activities in terms of software and models for automating pricing, including using machine learning. In this article, the authors reviewed some of the most popular offers on the market for the introduction of dynamic pricing systems and analyzed them, revealed the main features and identified common features of building automated dynamic pricing models. The practices of implementing dynamic pricing systems in Russian companies were also investigated. The results obtained allow us to draw conclusions about the importance of using automated pricing systems in retail in modern conditions, their capabilities and application problems.

(Invited) Trials and Tribulations on Scaling Metal Recovery Technology from Lab to Market

PowerTech Water, Inc. d/b/a ElectraMet (ElectraMet) is a cleantech company founded in 2014 in Lexington, KY with the goal of applying carbon and electrochemistry to solve fundamental challenges in wastewater and process water applications. There exists a broad array of separation applications that could be tackled through electrochemical routes, and ElectraMet has worked on many of them.Early in ElectraMet’s history, focus was directed towards salt removal applications such as salt-free water softening, brackish water desalination, and ultra-pure water production. While some traction was found in these spaces, penetration of a new technology versus entrenched incumbents such as reverse osmosis and distillation made the sales process difficult. Limitations in what the technology could and could not do were also determined. Therefore, within the first few years of operation, focus shifted towards particular customer pain points, specifically metals separation applications. Problematic metals concentrations are present in drinking water, industrial effluents, and storm runoff, just to name a few. As a growing but still small business, it is important to choose a beachhead market where you can have the strongest value proposition, and electrochemical separations of metals offered a unique opportunity to solve challenges in the metals separation space. Therefore, considerable work has gone into developing these separation processes for specific metals and specific markets.In this talk, the early history of the company will be reviewed, including technology, funding, and market applications. The impact of strategic advisors and early successes will be discussed with regards to the direction of the company. Ultimately, product-market-fit and the strategies and struggles in building a small business will be presented. Efforts will be made to highlight possible pitfalls, roadblocks, and opportunities as seen through this particular journey.

ANALISA DAN PERANCANGAN UI/UX APLIKASI PENJUALAN BESI BETON MENGGUNAKAN METODE DESIGN THINKING

The world of technology today greatly affects human life. Technological advances, especially in the field of information technology, are increasing every year. PT Sumber Jaya Maju Gemilang provides a variety of reinforced concrete products to meet the needs of different consumers for projects, factories, and other construction. During the sales process, it is still done manually, which hinders business because it takes a lot of time and causes errors in processing and reporting transaction data. Because of these problems, a new design for the Sales of Reinforced Concrete website must be designed using the design thinking method. The purpose of this study is to assist in creating sales applications that meet user needs and improve user experience. The results of the study show that the empathy stage, namely determining and observing previous cases, one of the problems that can be concluded from the empathize process is the company's low level of awareness of their service users. In the previous stage, the idea was to create an application that could handle the problems of people who wanted to order iron and delivery of goods but did not have much time or did not want to queue for a long time. At this stage, the prototype must rearrange the flow of iron sales and delivery of goods so that it is easier, and create a pattern for creating features in the application. In the final stage, the application trial process is carried out using the digital prototype in the Figma Application.

Web-based Palm Oil Seedling Sales Information System (Case Study: CV. XYZ)

Oil palm seedling sales are one of the important aspects of the agricultural industry in Indonesia. However, conventional sales processes often encounter various obstacles, such as limited access to information for consumers, difficulties in inventory management, and low operational efficiency. To overcome these problems, this study aims to develop a Web-based Oil Palm Seedling Sales Information System at CV. XYZ. We designed this system to offer a comprehensive solution for sales management, encompassing stock recording and real-time transaction processing. This study uses a system development method with the waterfall method, in which the development stages include requirements, system design, implementation, verification, and maintenance. We collected data through direct observation at CV XYZ, interviews with management and customers, and related literature studies. Users then tested the prototype to identify potential problems and gather feedback for system improvement. According to the study's findings, the implementation of this web-based information system has resulted in increased efficiency in sales and inventory management. Users can easily access product information, place orders, and track the status of their orders. In addition, this system also allows integration with payment gateways, so that the transaction process becomes faster and safer. This system simplifies customer data management, sales recording, and financial report analysis from a management standpoint. At CV. XYZ, the development of the Web-based Palm Oil Seedling Sales Information System positively impacted operational efficiency and effectiveness. This system not only increases customer satisfaction by providing faster and more transparent services, but it also helps management make more accurate decisions based on available data. We need to add more advanced data analysis features to forecast sales trends and market demands, and integrate the system with e-commerce platforms to broaden our market reach.

Tinjauan Yuridis tentang Peran Notaris dalam Penyusunan Akta Jual Beli Tanah di Indonesia

The aim of this research is to look from a juridical perspective on the role of Notaries in making land sale and purchase deeds in Indonesia. The background to this problem is that the land sale and purchase deed is very important as proof of the validity of the transaction and the existence of legal certainty in the land sale and purchase process. The research method used is normative juridical, namely reviewing related laws and regulations and reviewing legal literature and documents. Research shows that notaries play an important role in ensuring the validity of land sale and purchase deeds. The notary is tasked with checking the validity of supporting documents, ensuring that transactions are carried out voluntarily and without coercion, as well as recording and storing deeds for future use. This research found that the presence of a Notary plays an important role in the process of making a sale and purchase deed.

Development of a POS System with Computer Vision for Automated Retail Checkout

A Point-of-Sale (POS) is a computerized system of hardware and software utilized by businesses to complete sales transactions. In conventional POS setups, cashiers manually scan individual product barcodes, before processing the totals. This manual procedure is laborious and often leads to long queues and waiting times, especially during peak hours, ultimately affecting customer experience and retention. This work seeks to automate the product scanning procedure with a computer vision approach, thereby expediting the sales process. An efficient YOLOv4 object detection model was trained on a custom dataset of common products found in Malaysian retail stores. 550 images were initially acquired and split 80:20 into training and validation groups; further augmentation tripled the size of the training group to 1,320 images. Training was conducted for 10,000 epochs, at 0.0013 learning rate. During training, the model achieved 99.19% mAP, 87.42% average IoU, and a 0.40 average loss. Subsequently, the model was deployed on a low-power single-board computer running a transaction notification program. To evaluate its performance, 10 instances of shopping carts with random product combinations were processed using the system. The system autonomously identified and quantified all products through its video feed, generating itemized bills in real-time. Fixed with a 0.9 confidence threshold, the system yielded a 98% average accuracy across all object classes. On average, transactions, from product detection to delivering the itemized bill to the system administrator, were processed in just 14 seconds. This POS system holds potential for integration with unmanned stores, offering a seamless shopping experience.

Optimalisasi Kemasan Produk Untuk Memperkuat Minat Pasar dan Brand UMKM Lokal Desa Mekarmukti Bandung Barat

The product packaging and brand of the local UMKM in Mekarmukti Cihampelas Village, West Bandung Regency has a big influence on the customer's perspective in choosing products, and with the implementation of the digital economy, this can help business income and if this business runs well, it can continue to increase the income of the Village's Local UMKM. Mekarmukti Cihampelas, West Bandung Regency. The role of the Digital Economy in terms of product packaging and branding in local UMKM in Mekarmukti Cihampelas Village, West Bandung Regency, simplifies the sales process, facilitates payment transactions and helps product marketing. Specifically for UMKM in this research, the local UMKM in Mekarmukti Cihampelas Village, Bandung Regency, are not yet economically independent and are not yet effective in using technology in managing and marketing products. Local UMKM in Mekarmukti Cihampelas Village, West Bandung Regency are still limited.

Perancangan Aplikasi Penjualan Furniture Berbasis Android

Furniture has high added value and significant global competitiveness, largely due to the diversity of natural raw materials available in Indonesia, such as wood, rattan, and bamboo, as well as distinctive and high-quality designs. This advantage is supported by the skills and competence of the available human resources, making Indonesian furniture superior to products from other countries. Product quality is a key element in winning market competition, as it impacts customer satisfaction and loyalty. Masnur Joglo, a furniture company located on Jl. Muara Karya, specializes in producing various types of furniture from high-quality woods such as super mahogany and red teak. However, the purchasing system, which requires customers to visit the store directly and manually record prices, results in inefficiencies in terms of time and transportation costs. Customers often need to visit multiple stores to find the desired product, which is an inefficient process. To address these challenges, this study proposes the development of an Android-based sales application as a solution. This application is designed to expand Masnur Joglo's market reach and facilitate online ordering of furniture products, anytime and anywhere. The study aims to design and develop an Android-based sales information system that can enhance operational efficiency and streamline the sales process while better meeting customer needs. The application development method employs the waterfall model and uses MySQL and Firebase databases.

Improving the sales process of profitable perishable goods: an inventory control strategy in a planned economy

PurposeThe purpose is to have appropriate planning for reducing costs during the procurement process and increasing profits during the sales period in a supply cycle at a retail store. To make the proposed model practical, efforts have been made to implement the existing constraints in a business environment and legal factors.Design/methodology/approachTo achieve the objectives of this research, a mixed-methods approach was employed. Initially, sales data was collected, and industry experts were consulted to identify key products. A mathematical model and a particle swarm optimization algorithm were utilized for simulation and optimization. Furthermore, time series forecasting techniques were employed to estimate demand accurately.FindingsThe findings of this research emphasize the importance of considering all factors affecting costs simultaneously when utilizing tools to reduce costs during the planning period. It was observed that certain tools, which individually have a favorable effect on costs, may collectively result in an increase in costs over the examined period. This highlights the need for a comprehensive and integrated approach to planning.Research limitations/implicationsThe business environment and legal factors in each country are among the factors that affect the performance of retailers, which has received less attention in previous research. This research aimed to address this gap by considering various factors. However, it is important to note that the proposed model has been investigated in research in hypermarkets and is applicable, but it cannot be generalized to other retailers.Originality/valueApplicability and consideration of new limitations in simulation along with consideration of the complete process from buying to selling goods.

Sales Trend Analysis With Machine Learning Linear Regression Algorithm Method

The development of online business in Indonesia is now very rapid, with the process being done by ordering goods through resellers or distributors using one of the social media. Item purchases are made based on product information, prices, discounts and inventory quantities using a decision model. In the sales process, Toko Serbu Aek Batu usually releases several different items to be offered to the market at different prices, but not all items are in high demand. Multiple linear regression is an analysis that describes the relationship between dependent variables and factors that affect more than one independent variable. The purpose of this study is to analyze sales trends using a linear regression method using rapidminer. The results of this study are prediction calculations using manual calculations with rapidminer the same results, predicting the price desired by buyers using a linear regression algorithm with the original price is not much different and rapidminer is very accurate to be used in predicting sales trends at the price desired by customers, so that sellers can pay more attention to things that are very influential in the sales process.

Comparison Of Exponesial Smoothing With Linear Regression Predicting Amount Of Goods Sales

A trading business is a business that operates in the sales sector with the aim of obtaining maximum profits through sales activities. To be able to sell efficiently, a prediction system is needed, so that there is no excess or shortage of inventory and the sales process can run smoothly. Human limitations in solving prediction problems without using tools that apply prediction methods are one of the obstacles in finding the right prediction value. Therefore, we need a prediction system that can help find accurate and fast values. So the problem formulation is how to design and build a sales prediction system using exponential smoothing and linear regression methods, then compare the two and find out which method is the best, both of which use periodic data prediction models. The data collection method used is secondary data from previous research and journals, as well as combining library study methods, namely information obtained from books, references and scientific works related to predictions. The tool used to build applications is MS-Visual Studio 2010 and WEB based system

An Analytical Solution for Sales of Seafood in District Karang Agung Ilir

The advent of internet technology has profoundly transformed information dissemination and commerce by providing continuous, global access. For Small and Medium Enterprises (UMKM) such as the Seafood District of Karang Agung Ilir—specializing in seafood products like shrimp, crabs, and squid—reliance on traditional market-based sales methods limits customer reach and hampers growth potential. This paper investigates the development of an innovative online-based sales information system aimed at modernizing and significantly improving the operational efficiency of the Seafood District. To evaluate the effectiveness of the proposed system, a System Usability Scale (SUS) test was conducted with 50 participants. The results yielded an average SUS score of 72, indicating that the system offers good usability but also highlights areas requiring further enhancement. The online platform is designed to provide 24/7 accessibility, optimize the sales process, and broaden the customer base beyond the local market. The anticipated advantages of this digital transition include reduced operational costs, enhanced customer service, and increased sales volume. By adopting online technology, the Seafood District of Karang Agung Ilir stands to strengthen its market presence and boost its competitiveness on a global scale

Web-Based Inventory Management System Using First In First Out Algorithm

<p>PT. Agung Selaras Group is a property company that operates in the business of selling houses. With a good sales management system, the property company can support its work activities. The aim of this research is to develop a system that can simplify stock management and minimize the risk of loss in the sales process. The data source for this research was obtained from direct observation and interviews with PT. Agung Selaras Group. In this system the author will combine the First In First Out method in managing incoming and outgoing product stock. The results of this research are that the system that has been designed can make it easier for managers to collect data on incoming and outgoing goods so that the risk of managing product stock can be minimized, and with computerized reports it can provide more precise, accurate and fast information. From the results of black box testing, the percentage of this application system can run well.</p>

The Recipe for the Perfect Sales Call

Abstract: Sales calls are an essential part of any sales process as the beginning of the sales pipeline for any business. A sales call is an opportunity to connect with prospects, understand their needs and challenges, and offer solutions to help them achieve their goals. Salespeople need to make a good impression during the first sales call to ensure a strong start to the sale. This document offers the perfect recipe for a successful sales call. In this document, you will have detailed knowledge on how to make phone calls, how to deal with people, especially women, how people respond to your calls, and a new technique that I have created myself for making successful calls, and will help you not sound like a normal sales person call for your customer so you don't have to hold the phone. I took advantage of this and made over 50 successful calls out of 331 during my internship at a financial consulting firm. Objective: The main objective of this document is to help freshers make a successful sales call. This document contains some techniques that will help any beginner to make a sales call